NQF

Agenda Synopsis

Full Agenda

Measure Index

• Ambulatory Breast Procedure Surgical Site Infection (SSI) Outcome Measure (Public comments received:1; MUC ID: MUC16-155)
  
  
• Hospital Visits after Orthopedic Ambulatory Surgical Center Procedures (Public comments received:1; MUC ID: MUC16-152)
  
  
• Hospital Visits after Urology Ambulatory Surgical Center Procedures (Public comments received:1; MUC ID: MUC16-153)
  
  

• Hemodialysis Vascular Access: Long-term Catheter Rate (Public comments received:3; MUC ID: MUC16-309)
  
  
• Hemodialysis Vascular Access: Standardized Fistula Rate (Public comments received:2; MUC ID: MUC16-308)
  
  
• Standardized Transfusion Ratio for Dialysis Facilities (Public comments received:2; MUC ID: MUC16-305)
  
  

• Alcohol & Other Drug Use Disorder Treatment Provided or Offered at Discharge and Alcohol & Other Drug Use Disorder Treatment at Discharge (Public comments received:3; MUC ID: MUC16-180)
  
  
• Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention (Public comments received:3; MUC ID: MUC16-178)
  
  
• Alcohol Use Screening (Public comments received:4; MUC ID: MUC16-179)
  
  
• Appropriate Documentation of a Malnutrition Diagnosis (Public comments received:3; MUC ID: MUC16-344)
  
  
• Communication about Pain During the Hospital Stay (Public comments received:2; MUC ID: MUC16-263)
  
  
• Communication about Treating Pain Post-Discharge (Public comments received:4; MUC ID: MUC16-264)
  
  
• Completion of a Malnutrition Screening within 24 Hours of Admission (Public comments received:4; MUC ID: MUC16-294)
  
  
• Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition within 24 Hours of a Malnutrition Screening (Public comments received:2; MUC ID: MUC16-296)
  
  
• Follow-Up After Hospitalization for Mental Illness (Public comments received: 0; MUC ID: MUC16-165)
  
  
• Hospital-Wide Risk Standardized Mortality Measure (Public comments received:3; MUC ID: MUC16-260)
  
  
• Measure of Quality of Informed Consent Documents for Hospital-Performed, Elective Procedures (Public comments received:1; MUC ID: MUC16-262)
  
  
• Nutrition Care Plan for Patients Identified as Malnourished after a Completed Nutrition Assessment (Public comments received:14; MUC ID: MUC16-372)
  
  
• Patient Panel Smoking Prevalence IQR (Public comments received:1; MUC ID: MUC16-068)
  
  
• Safe Use of Opioids – Concurrent Prescribing (Public comments received:2; MUC ID: MUC16-167)
  
  

• Influenza Immunization (IMM-2) (Public comments received:1; MUC ID: MUC16-053)
  
  
• Tobacco Use Screening (TOB-1) (Public comments received:1; MUC ID: MUC16-050)
  
  
• Tobacco Use Treatment Provided or Offered (TOB-2)/Tobacco Use Treatment (TOB-2a) (Public comments received:1; MUC ID: MUC16-051)
  
  
• Tobacco Use Treatment Provided or Offered at Discharge (TOB-3)/Tobacco Use Treatment at Discharge (TOB-3a) (Public comments received:3; MUC ID: MUC16-052)
  
  
• Use of Antipsychotics in Older Adults in the Inpatient Hospital Setting (Public comments received: 0; MUC ID: MUC16-041)
  
  

• Median Time from ED Arrival to ED Departure for Discharged ED Patients (Public comments received:7; MUC ID: MUC16-055)
  
  
• Median Time to Pain Management for Long Bone Fracture (Public comments received:2; MUC ID: MUC16-056)
  
  
• Safe Use of Opioids – Concurrent Prescribing (Public comments received:4; MUC ID: MUC16-167)
  
  

• Communication about Pain During the Hospital Stay (Public comments received:3; MUC ID: MUC16-263)
  
  
• Communication about Treating Pain Post-Discharge (Public comments received:3; MUC ID: MUC16-264)
  
  

• Identification of Opioid Use Disorder (Public comments received:4; MUC ID: MUC16-428)
  
  
• Medication Continuation following Inpatient Psychiatric Discharge (Public comments received: 0; MUC ID: MUC16-048)
  
  
• Medication Reconciliation at Admission (Public comments received: 0; MUC ID: MUC16-049)
  
  

• Localized Prostate Cancer: Bowel function (Public comments received: 0; MUC ID: MUC16-375)
  
  
• Localized Prostate Cancer: Sexual function (Public comments received: 0; MUC ID: MUC16-377)
  
  
• Localized Prostate Cancer: Urinary Frequency, Obstruction, and/or Irritation (Public comments received: 0; MUC ID: MUC16-379)
  
  
• Localized Prostate Cancer: Urinary Incontinence (Public comments received: 0; MUC ID: MUC16-380)
  
  
• Localized Prostate Cancer: Vitality (Public comments received: 0; MUC ID: MUC16-381)
  
  
• PRO utilization in in non-metastatic prostate cancer patients (Public comments received:2; MUC ID: MUC16-393)
  
  
• Proportion of patients who died from cancer admitted to hospice for less than 3 days (Public comments received:2; MUC ID: MUC16-274)
  
  
• Proportion of patients who died from cancer admitted to the ICU in the last 30 days of life (Public comments received:1; MUC ID: MUC16-273)
  
  
• Proportion of patients who died from cancer not admitted to hospice (Public comments received:3; MUC ID: MUC16-275)
  
  
• Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of life (Public comments received:1; MUC ID: MUC16-271)
  
  

Full Measure Information

Measure Specifications

• NQF Number (if applicable): 3025
  
  
• Description: This measure is for the risk-adjusted Standardized Infection Ratio (SIR) for all Surgical Site Infections (SSIs) following breast procedures conducted at ambulatory surgery centers (ASCs) among adult patients (ages 18 - 108 years) and reported to the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN). The measure compares the reported number of surgical site infections observed at an ASC with a predicted value based on nationally aggregated data. The measure was developed collaboratively by the CDC, the Ambulatory Surgery Center Quality Collaboration (ASC QC), and the Colorado Department of Public Health and Environment. CDC is the measure steward.
  
  
• Numerator: Surgical site infections (SSIs) during the 30-day (superficial SSI) and 90-day (deep and organ/space SSI) postoperative periods following breast procedures in Ambulatory Surgery Centers. SSI is defined in accordance with the CDC's National Healthcare Safety Network (NHSN) surveillance protocol as an infection, following a breast procedure, of either the skin, subcutaneous tissue and breast parenchyma at the incision site (superficial incisional SSI), deep soft tissues of the incision site (deep incisional SSI), or any part of the body deeper than the fascial/muscle layers that is opened or manipulated during the operative procedure (organ/space SSI).
  
  
• Denominator: Breast procedures, as specified by the operative codes that comprise the breast procedure category of the NHSN Patient Safety Component Protocol, performed at ambulatory surgery centers. These (Current Procedural Terminology, i.e. CPT) codes are 11970, 19101, 19112, 19120, 19125, 19126, 19300, 19301, 19302, 19303, 19304, 19305, 19306, 19307, 19316, 19318, 19324, 19325, 19328, 19330, 19340, 19342, 19350, 19355, 19357, 19361, 19364, 19366, 19367, 19368, 19369, 19370, 19371, 19380
  
  
• Exclusions: Hospital inpatients and hospital outpatient department patients, pediatric patients (younger than 18 years) and very elderly patients (older than 108 years), and brain-dead patients whose organs are being removed for donor purposes.
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: National Healthcare Safety Network
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Disease Control and Prevention
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is a fully developed measure and is currently under review by the Patient Safety Standing Committee for NQF endorsement. The Committee recommended the measure for endorsement. The measure should complete the consensus development process (CDP) and receive NQF endorsement.
  • Impact on quality of care for patients:Improved care and a decrease in the number of surgical site infections (SSIs) for patients undergoing breast procedures at ambulatory surgical care centers.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses making care safer by reducing harm caused in the delivery of care
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes . In the current literature, the rates of SSI in ambulatory surgery centers is relatively low; however, aggregate numbers of infections can still cause a substantial burden, as those often result in post-surgical visits and morbidity.
  
  
• Does the measure address a quality challenge? Yes. During the time period of 2010-2013, a total of 67,150 ASC procedures were reported to NHSN. Of those ASC procedures 30,787 (45.9%) were breast procedures. There were 142 SSIs reported from ASCs during that same time period, 78 (54.9%) were related to breast procedures, indicating an SSI risk of 0.25%, illuminating the fact that breast procedures presented the highest volume and SSI risk out of all outpatient ASC procedures reported in the timeframe.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure is not duplicative of another measure in the ASCQR program.
  
  
• Can the measure can be feasibly reported? Yes. The CDC's National Healthcare Safety Network (NHSN) will serve as the platform for surgical site infection (SSI) data collection, analysis, and measure results reporting. ASCs are instructed to follow a standardized data collection procedure (specified by the NHSN protocol and definitions). Patient-level data is reported for each procedure and infection, and the NHSN platform has proven to be secure.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes . This measure has been submitted to NQF and is currently under review by NQF’s Patient Safety Standing Committee. The Committee agreed that the reliability and validity testing results meet NQF criteria.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. This is a new measure and has never been used in a program. The developer stated that no unintended consequences have occurred, however, gaming the data by providers and an inappropriate focus on what is measured at the expense of other important aspects of healthcare were noted as potential consequences.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? No.
  
  

Rationale for measure provided by HHS
Breast SSIs contribute a substantial portion of SSI in inpatient settings, and also have the one of the highest risk of any procedure type in outpatient settings. In the Netherlands, the rate of SSI following mastectomies in 2006 was 61% as determined by a study in 2006 (Mannien, 2006). A case control study performed in 2004 reported SSI rates following breast surgeries to be 25.8% (Vilar-Compte, 2004). One study of breast SSI risk in an HOPD reported an overall risk of 5.2%, with procedure-specific risks of 12.4% following mastectomy with immediate implant reconstruction, 6.2% following mastectomy with immediate reconstruction using a transverse rectus abdominis myocutaneous flap, 4.4% following mastectomy only, and 1.1% following breast reduction surgery (Olsen, 2008). Another study of SSI following breast cancer-related procedures reported a risk of 18.9% (Vilar-Compte, 2009). The cost incurred by each breast SSI attributable to the SSI was estimated by one analysis to be $4,901 per patient (Olsen, 2008). Though these estimates of risk vary from 1% to over 30% depending on procedure type, sample population, and definition of SSI, it is clear that breast procedure-related SSIs are a large burden to outpatient healthcare facilities. From 1980-1995, a significant trend in surgery was the transition from inpatient settings to outpatient ambulatory surgery settings due to advances in surgical techniques and economic incentives for ambulatory surgery (Kozak, 1999). In the current literature, the rates of SSI in ambulatory surgery centers is relatively low—however, aggregate numbers of infections can still cause a substantial burden, as those often result in post-surgical visits and morbidity. ASCs have been shown to have a lower SSI rate than inpatient settings; in one study, SSI morbidity and recurrence rates in ambulatory surgery were half the rates in inpatient surgery. A 5-year study of SSIs in ambulatory surgery centers showed a rate of 2.8 SSI per 100 surgeries (Vilar-Compte, 2001). These rates are relatively consistent- another study reported a risk of SSI after outpatient surgery to be 3.5% (Grøgaard, 2001). Aside from morbidity alone, postsurgical visits due to SSI acquired during surgery contribute much to the cost burden on healthcare facilities. A study on postsurgical acute care visits for SSIs in ASCs demonstrated a rate of 3.09 SSI-related visits per 1000 procedures at 14 days after surgery and 4.84 per 1000 at 30 days after surgery (Owens, 2014). References Mannien, J., Wille, J. C., Snoeren, R. L., & Hof, S. V. (2006). Impact of Postdischarge Surveillance on Surgical Site Infection Rates for Several Surgical Procedures: Results From the Nosocomial Surveillance Network in The Netherlands. Infection Control and Hospital Epidemiology Infect Control Hosp Epidemiol, 27(8), 809-816. Volkow, P., Vilar-Compte, D., Jacquemin, B., & Robles-Vidal, C. (2004). Surgical Site Infections in Breast Surgery: Case-control Study. World Journal of Surgery, 28(3), 242-246. Vilar-Compte, D., Rosales, S., Hernandez-Mello, N., Maafs, E., & Volkow, P. (2009). Surveillance, Control, and Prevention of Surgical Site Infections in Breast Cancer Surgery: A 5-year Experience. American Journal of Infection Control, 37(8), 674-679. Olsen, M. A., et al. (2008). Hospital-Associated Costs Due to Surgical Site Infection After Breast Surgery. Arch Surg Archives of Surgery, 143(1), 53-60. Kozak LJ, McCarthy E, Pokras R. (1999). Changing Patterns of Surgical Care in the United States, 1980-1995. Health Care Financ Rev, 21(1), 31-49. Vilar-Compte D, Roldán R, Sandoval S, et al. (2001). Surgical Site Infections in Ambulatory Surgery: A 5-year Experience. American Journal of Infection Control, 29(2), 99-103. Grøgaard, B. (2001). Wound Infection in Day-surgery. Ambulatory Surgery, 9(2), 109-112. Owens PL, Barrett ML, Raetzman S, Maggard-Gibbons M, Steiner CA. (2014). Surgical Site Infections Following Ambulatory Surgery Procedures. Jama, 311(7), 709-716.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: **As of 12/2 testing for this measure has been completed**** The measure score is an ASC-level rate of unplanned hospital visits within 7 days of an orthopedic procedure performed at an ASC.
  
  
• Numerator: The outcome is any acute, unplanned hospital visit occurring within 7 days of the orthopedic surgical procedure performed at an ASC. Hospital visits include emergency department visits, observation stays, and unplanned inpatient admissions.
  
  
• Denominator: The cohort includes Medicare FFS patients aged 65 years and older undergoing orthopedic surgeries performed at ASCs. The measure includes only Medicare FFS patients who have 12 months of prior FFS enrollment. To identify eligible orthopedic surgeries, we first identified a list of procedures from Medicare’s 2013 ASC list of covered procedures, which includes procedures for which ASCs can be reimbursed under the ASC payment system. This list is publicly available and annually reviewed and updated via a transparent process by Medicare. This list of ASC procedures is available for download at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ASCPayment/ASC-Regulations-and-Notices-Items/CMS-1589-FC.html (download Addendum AA from website). We then focused on a subset of procedures - the “major” and “minor” global surgical package procedures - included on the list of covered ASC procedures. We identify “major” and “minor” using the global surgery indicator (GSI) values of 090 and 010, respectively, which identify surgeries of greater complexity and follow-up care based on Work Relative Value Units (RVUs). To aggregate procedure-specific codes into the orthopedic procedures cohort, we used the Clinical Classifications Software (CCS) developed by the Agency for Healthcare Research and Quality (AHRQ). The CCS is a tool for clustering procedures into clinically meaningful categories using Common Procedural Terminology (CPT) codes by operation site. We include only procedures typically performed by orthopedic surgeons. Examples of orthopedic procedures include treatment of toe deformities, arthroscopic knee procedures, therapeutic procedures on muscles, tendons, joints, and bones, and treatment of fractures.
  
  
• Exclusions: The measure surgeries for patients who survived at least 7 days, but were not continuously enrolled in Medicare FFS Parts A and B in the 7 days after the surgery are excluded. These patients are excluded to ensure all patients have full data available for outcome assessment.
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Claims, Other
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is fully developed and specified andaligns with NQF #2539: Rate of Risk-Standardized, All-Cause, Unplanned Hospital Visits within 7 Days of an Outpatient Colonoscopy Among Medicare Fee-for-Service (FFS) Patients Aged 65 Years and Older and MUC16-153: Hospital Visits following Urology Ambulatory Surgical Center Procedures. Testing results should demonstrate reliability and validity at the facility level in the ambulatory surgical setting. This measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:Improved care, care transitions and minimal unplanned hospital visits within 7 days following orthopedic procedures performed in the ambulatory surgical care setting.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses promoting effective communication and coordination of care to make care safer and reducing the harm caused in the delivery of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Measuring and reporting seven-day unplanned hospital visits following orthopedic procedures will incentivize ASCs to improve care and care transitions.
  
  
• Does the measure address a quality challenge? Yes. ASC facilities show variation in their outcome rates for orthepedic procedures which suggests that there is substantial room for quality improvement. The rate of unplanned hospital visits at or after ambulatory orthopedic surgery is about 6 per 1,000 patients and about 4 per 1,000 patients at 4 days post-procedure. The rate levels out to 2 per 1,000 patients at approximately 14 days after surgery. In addition, the Healthcare Cost and Utilization Project data from Florida and New York illustrated that the median unadjusted outcome rate is 1.7%, ranging from 0 to 11.4%; the 25th and 75th percentiles were 0.8% and 2.6%, respectively.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure’s specifications align with the outcome measure in the ASCQR program NQF #2539: Rate of Risk-Standardized, All-Cause, Unplanned Hospital Visits within 7 Days of an Outpatient Colonoscopy Among Medicare Fee-for-Service (FFS) Patients Aged 65 Years and Older and MUC16-153: Hospital Visits following Urology Ambulatory Surgical Center Procedures.This measure is also similar to #0265 All-Cause Hospital Transfer/Admission currently in the ASCQR program. However, #0265 is not procedure-specific, risk-adjusted and does not include the 7 day post-discharge period. In addition, NQF endorsement was removed from #0265 in February 2016.
  
  
• Can the measure can be feasibly reported? Yes. The data sources include Medicare administrative claims, as well as enrollment data. These data sources allow the linking of Medicare patient information across care settings to help identify and adjust facility outcome rates for patient comorbidities, and identify what happens to patients at or after they are discharged from the ASC.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is fully developed and specified. The measure is currently undergoing field testing. Testing results should demonstrate reliability and validity at the facility level in the ambulatory care setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is not currently in use. The developer noted that measuring unplanned hospital visits following procedures performed at ASCs may discourage ASCs from performing riskier procedures and/or performing procedures on patients who are inherently at higher risk of post-procedure hospital visits.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Improving the quality of care provided at ASCs is a key priority in the context of growth in the number of ASCs and procedures performed in this setting. More than 60% of all medical or surgical procedures were performed at ASCs in 2006 – a three-fold increase from the late 1990s (Cullen et al. 2009). In 2013, more than 3.4 million Fee-for-Service (FFS) Medicare beneficiaries were treated at 5,364 Medicare-certified ASCs, and spending on ASC services by Medicare and its beneficiaries amounted to $3.7 billion (Medicare Payment Advisory Commission 2015). The patient population served at ASCs has increased not only in volume but also in age and complexity, which can be partially attributed to improvements in anesthetic care and innovations in minimally invasive surgical techniques (Bettelli 2009; Fuchs 2002). ASCs have become the preferred setting for the provision of low-risk surgical and medical procedures in the US, as many patients experience shorter wait times, prefer to avoid hospitalization, and are able to return rapidly to work (Cullen et al. 2009). Therefore, in the context of growth in volume and diversity of procedures performed at ASCs, evaluating the quality of care provided at ASCs is increasingly important. As the number of orthopedic procedures increase in ASCs, it is important to evaluate the quality of care for patients undergoing these procedures. According to Medicare claims, approximately 7% of surgeries performed at ASCs were orthopedic in nature in 2007, which reflects a 77% increase in orthopedic procedures performed at ASCs from 2000 to 2007 (Goyal et al. 2016). Measuring and reporting seven-day unplanned hospital visits following orthopedic procedures will incentivize ASCs to improve care and care transitions. Many of the reasons for hospital visits are preventable. Patients often present to the hospital for complications of medical care, including infection, post-operative bleeding, urinary retention, nausea and vomiting, and pain. Martín-Ferrero et al. (2014) found that of 10,032 patients who underwent ambulatory orthopedic surgical procedures at an ambulatory surgery unit between June 1993 and June 2012, 121 (1.2%) patients needed attention in the emergency department during the first 24 hours after discharge because of pain (86 patients) or bleeding (35 patients). There were five subsequent hospitalizations for knee pain and swelling (Martín-Ferrero and Faour- Martín 2014). In conclusion, acute care visits following orthopedic surgery are an important and measurable outcome for surgeries and procedures performed at ASCs. Many of these unanticipated acute care visits occur at or after discharge and may not be readily visible to clinicians because patients often present to alternative facilities, such as emergency departments. Therefore, illuminating these events should facilitate efforts to improve patient outcomes following ASC procedures. Bettelli G. High risk patients in day surgery. Minerva anestesiologica. 2009;75(5):259-268. Cullen KA, Hall MJ, Golosinskiy A, Statistics NCfH. Ambulatory surgery in the United States, 2006. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics; 2009. Fuchs K. Minimally invasive surgery. Endoscopy. 2002;34(2):154-159. Goyal KS, Jain S, Buterbaugh GA, et al. The safety of hang and upper-extremity surgical procedures at a freestanding ambulatory surgical center. The Journal of Bone and Joint Surgery. 2016;90:600-4. Martín-Ferrero MÁ, Faour- Martín O. Ambulatory surgery in orthopedics: experience of over 10,000 patients. Journal of Orthopaedic Surgery. 2014;19:332-338. Medicare Payment Advisory Commission (MedPAC). Report to Congress: Medicare Payment Policy. March 2015; http://www.medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf?sfvrsn=0.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: **As of 12/2 testing for this measure has been completed**** The measure score is an ASC-level rate of unplanned hospital visits within 7 days of a urology procedure performed at an ASC.
  
  
• Numerator: The outcome is any acute, unplanned hospital visit occurring within 7 days of the urology procedure performed at an ASC. Unplanned hospital visits include emergency department visits, observation stays, and unplanned inpatient admissions.
  
  
• Denominator: The cohort includes Medicare FFS patients aged 65 years and older undergoing urology procedures performed at ASCs. The measure includes only Medicare FFS patients who have 12 months of prior FFS enrollment. To identify eligible urology surgeries, we first identified a list of procedures from Medicare’s 2013 ASC list of covered procedures, which includes procedures for which ASCs can be reimbursed under the ASC payment system. This list is publicly available and annually reviewed and updated via a transparent process by Medicare. This list of ASC procedures is available for download at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/ASCPayment/ASC-Regulations-and-Notices-Items/CMS-1589-FC.html (download Addendum AA from website). We then focused on a subset of procedures - the “major” and “minor” global surgical package procedures - included on the list of covered ASC procedures. We identify “major” and “minor” using the global surgery indicator (GSI) values of 090 and 010, respectively, which identify surgeries of greater complexity and follow-up care based on Work Relative Value Units (RVUs). We include cystoscopy with intervention – minor procedures identified with the GSI value of 000 – in the urology measure cohort since this is a common procedure, often performed for therapeutic intervention by surgical teams, and has an outcome rate similar to other procedures in the urology measure cohort. To identify eligible urology procedures, we used the Clinical Classifications Software (CCS) developed by the Agency for Healthcare Research and Quality (AHRQ). The CCS is a tool for clustering procedures into clinically meaningful categories using Common Procedural Terminology (CPT) codes by operation site. We include only procedures typically performed by urologists. Examples of urology procedures include treatment or removal of all or part of the prostate gland, laser surgery of the prostate, therapeutic cystoscopy (scope used to examine the inside of the bladder), and fragmenting of kidney stones.
  
  
• Exclusions: The measure excludes surgeries for patients who survived at least 7 days, but were not continuously enrolled in Medicare FFS Parts A and B in the 7 days after the surgery are excluded. These patients are excluded to ensure all patients have full data available for outcome assessment.
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Claims, Other
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is fully developed and specified andaligns with NQF #2539: Rate of Risk-Standardized, All-Cause, Unplanned Hospital Visits within 7 Days of an Outpatient Colonoscopy Among Medicare Fee-for-Service (FFS) Patients Aged 65 Years and Older and MUC16-152: Hospital Visits following Orthopedic Ambulatory Surgical Center Procedures. Testing results should demonstrate reliability and validity at the facility level in the ambulatory surgical setting. This measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:Improved care, care transitions and minimal unplanned hospital visits within 7 days following urology procedures performed in the ambulatory surgical care setting.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses promoting effective communication and coordination of care to make care safer and reducing the harm caused in the delivery of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Measuring and reporting seven-day unplanned hospital visits following urology procedures will incentivize ASCs to improve care and care transitions.
  
  
• Does the measure address a quality challenge? Yes. ASC facilities show variation in their outcome rates for urology procedures which suggests that there is substantial room for quality improvement. The rate of unplanned hospital visits at or after ambulatory urology surgery is about 19 per 1,000 patients and about 6 per 1,000 patients at 7 days post-procedure. The rate levels out to 4 per 1,000 patients at approximately 23 days after surgery. In addition, the Healthcare Cost and Utilization Project data from Florida and New York illustrated that the median unadjusted outcome rate is 4.9%, ranging from 0 to 17.2%; the 25th and 75th percentiles were 3.4% and 7.0%, respectively.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes . This measure’s specifications align with the outcome measure in the ASCQR program NQF #2539: Rate of Risk-Standardized, All-Cause, Unplanned Hospital Visits within 7 Days of an Outpatient Colonoscopy Among Medicare Fee-for-Service (FFS) Patients Aged 65 Years and Older and MUC16-152: Hospital Visits following Orthopedic Ambulatory Surgical Center ProceduresThis measure is also similar to #0265 All-Cause Hospital Transfer/Admission currently in the ASCQR program. However, #0265 is not procedure-specific, risk-adjusted and does not include the 7-day post-discharge period. In addition, NQF removed endorsement from #0265 in February 2016.
  
  
• Can the measure can be feasibly reported? Yes. The data sources include Medicare administrative claims, as well as enrollment data. These data sources allow the linking of Medicare patient information across care settings to help identify and adjust facility outcome rates for patient comorbidities, and identify what happens to patients at or after they are discharged from the ASC.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is fully developed and specified. The measure is currently undergoing field testing. Testing results should demonstrate reliability and validity at the facility level in the ambulatory care setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is not currently in use. The developer noted that measuring unplanned hospital visits following procedures performed at ASCs may discourage ASCs from performing riskier procedures and/or performing procedures on patients who are inherently at higher risk of post-procedure hospital visits.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Improving the quality of care provided at ASCs is a key priority in the context of growth in the number of ASCs and procedures performed in this setting. More than 60% of all medical or surgical procedures are performed at ASCs in 2006 – a three-fold increase since the late 1990s (Cullen et al. 2009). In 2013, more than 3.4 million Fee-for-Service (FFS) Medicare beneficiaries were treated at 5,364 Medicare-certified ASCs, and spending on ASC services by Medicare and its beneficiaries amounted to $3.7 billion (Medicare Payment Advisory Commission 2015). The patient population served at ASCs has increased not only in volume but also in age and complexity, which can be partially attributed to improvements in anesthetic care and innovations in minimally invasive surgical techniques (Bettelli 2009; Fuchs 2002). ASCs have become the preferred setting for the provision of low-risk surgical and medical procedures in the US, as many patients experience shorter wait times, prefer to avoid hospitalization, and are able to return rapidly to work (Cullen et al. 2009). Therefore, in the context of growth in volume and diversity of procedures performed at ASCs, evaluating the quality of care provided at ASCs is increasingly important. As the number of urology procedures increases in ASCs, it is important to evaluate the quality of care for patients undergoing these procedures. A 1998 study found that urology procedures accounted for 4.8% of unanticipated admissions and was almost twice as likely as orthopedics, plastic surgery, or neurosurgery to have admissions (Fortier 1998). Similarly, a 2014 study found that outpatient urology surgery had an overall 3.7% readmission rate (Rambachan 2014). Using 5% national samples of Medicare FFS beneficiaries aged =65 years from 1998 to 2006, Hollingsworth et al. (2012) reported 30-day adjusted outcome rates for patients who underwent one of 22 common outpatient urologic procedures at ASCs. The 30-day adjusted rate of inpatient admission was 7.9% (0.4% same-day admission and 7.5% subsequent admission). Risk-adjustment variables included age, gender, race, comorbid status (assessed using an adaptation of the Charlson index), area of residence, and calendar year. Multivariable logistic regression analyses used robust variance estimators (Hollingsworth 2012). The study found that more frequent same-day admissions follow outpatient surgery at ASCs vs. hospitals. Since urology procedure in the ASC is a significant predictive factor for unanticipated admissions compared to other procedures (Fortier 1998), measuring and reporting seven-day unplanned hospital visits following urology procedures will incentivize ASCs to improve care and care transitions. Many of the reasons for hospital visits are preventable. Patients often present to the hospital for complications of medical care, including urinary tract infection, calculus of ureter, urinary retention, hematuria, and septicemia. However, patient and staff education is an opportunity to improve the success rate of urology procedures in the ASC (Paez 2007). Using data from the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP), Owens et al. (2014) reported unadjusted outcomes for low-risk patients undergoing five types of low- to moderate-risk surgical procedures, including urology procedures (Owens 2014). The outcomes of interest included 14- and 30-day all-cause acute care visit rates. Acute care visits included subsequent ambulatory surgery visits and inpatient admissions; the authors specifically excluded ED visits that did not result in hospitalization from the outcome. The 14- and 30-day rates of transurethral prostatectomy acute care visits were 0.11% and .18%, respectively. In conclusion, acute care visits following urology surgery are an important and measurable outcome for surgeries and procedures performed at ASCs. Many of these unanticipated acute care visits occur at or after discharge and may not be readily visible to clinicians because patients often present to alternative facilities, such as emergency departments. Therefore, illuminating these events should facilitate efforts to improve patient outcomes following ASC procedures. Bettelli G. High risk patients in day surgery. Minerva anestesiologica. 2009;75(5):259-268. Cullen KA, Hall MJ, Golosinskiy A, Statistics NCfH. Ambulatory surgery in the United States, 2006. US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Health Statistics; 2009. Fortier J. Unanticipated admission after ambulatory surgery--a prospective study. Can J Anaesth. 1998;45(7):612-9. Fuchs K. Minimally invasive surgery. Endoscopy. 2002;34(2):154-159. Hollingsworth JM. Surgical quality among Medicare beneficiaries undergoing outpatient urological surgery. The Journal of Urology. 2012;188(4):1274-1278. Medicare Payment Advisory Commission (MedPAC). Report to Congress: Medicare Payment Policy. March 2015; http://www.medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf?sfvrsn=0. Owens PLPL. Surgical site infections following ambulatory surgery procedures. JAMA : the journal of the American Medical Association. 2014;311(7):709-716. Paez A. Adverse events and readmissions after day-case urological surgery. International Braz J Urol. 2007;33(3):330-8. Rambachan A. Predictors of readmission following outpatient urological surgery Annals of the Royal College of Surgeons of England. Journal of Urology. 2014; 192(1):183-188.

Measure Specifications

• NQF Number (if applicable): 2978
  
  
• Description: Percentage of adult hemodialysis patient-months using a catheter continuously for three months or longer for vascular access.
  
  
• Numerator: The numerator is the number of adult patient-months in the denominator who were on maintenance hemodialysis using a catheter continuously for three months or longer as of the last hemodialysis session of the reporting month.
  
  
• Denominator: All patients at least 18 years old as of the first day of the reporting month who are determined to be maintenance hemodialysis patients (in-center and home HD) for the complete reporting month at the same facility.
  
  
• Exclusions: Exclusions that are implicit in the denominator definition include: -Pediatric patients (<18 years old) -Patients on Peritoneal Dialysis -Patient-months under in-center or home hemodialysis for less than a complete reporting month at the same facility In addition, the following exclusions are applied to the denominator: Patients with a catheter that have limited life expectancy: -Patients under hospice care in the current reporting month -Patients with metastatic cancer in the past 12 months -Patients with end stage liver disease in the past 12 months -Patients with coma or anoxic brain injury in the past 12 months
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Intermediate Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is intended to replace the existing vascular access type measure in the ESRD QIP. The measure is currently under review by the Renal Standing Committee. The Standing Committee and CSAC recommended the measure for endorsement
  • Impact on quality of care for patients:This measure provides dialysis patients with information about the long-term use of catheters for vascular access.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The evidence provided demonstrates an association between type of vascular access used for hemodialysis and the risk of patient mortality. The measure is intended to replace NQF #0256: Vascular Access Type – Catheter >=90 Days.
  
  
• Does the measure address a quality challenge? Yes. Analysis of CROWNWeb data from January 2014- December 2014 indicated the facility-level mean percentage of patient-months with a long-term catheter was 11.6% (SD=6.6%). Distribution: Min=0%, 1st quartile=7.0 %, median=10.5%, 3rd quartile=14.9%, Max=58.2%.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure will replace a current measure that is part of the ESRD QIP, Minimizing Use of Catheters as Chronic Dialysis Access - NQF# 0256. The new measure incorporates a more robust set of exclusions than NQF# 0256, reflecting the need for individualized treatment of patients for whom a fistula or graft access may not be feasible or appropriate. This measure is intended to be jointly reported with the Hemodialysis Vascular Access- Standardized Fistula Rate. These two vascular access quality measures, when used together, consider Arterial Venous (AV) fistula use as a positive outcome and prolonged use of a tunneled catheter as a negative outcome.
  
  
• Can the measure can be feasibly reported? Yes. Similar measure has been part of the ESRD QIP since 2013, and is publicly reported since 2012.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and specified. The Renal Standing Committee and CSAC recommended the measure for endorsement. The NQF Executive Committee is scheduled to review the measure in December 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The measure developers have not identified any unintended consequences in implementing the measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The 2006 Clinical Practice Guidelines for Vascular Access is an update to the original vascular access guidelines published in 1997 by the National Kidney Foundation. In the eight years that the literature review included for the update, there have been no randomized controlled trials for type of vascular access. Specifically, for the guideline used to support this measure, a total of 84 peer-reviewed publications are included in the body of evidence presented. While these are all observational studies, some are based on either national data such as the United States Renal Data System (USRDS) that includes all patients with end stage kidney disease in the US, or international data, such as the Dialysis Outcomes Practice Pattern Study (DOPPS) that provides a global perspective for US vascular access outcomes. The overall quality of evidence is moderately strong. All studies are in the target population of hemodialysis patients. Some studies have evaluated health outcomes such as patient mortality, but have limitations due to the observational nature of the design. Other studies have more rigorous design, but use surrogate outcomes such as access thrombosis. The 12 studies listed below highlight the core benefits associated with using an AV fistula or graft such as reduced mortality and morbidity relative to using a tunneled catheter. Specifically, AV fistula have: • Lowest Cost1-3: Compared to catheters, Medicare expenditures for AVF are approximately $17,000 less per person per year. • Lowest rates of infection: AV fistula have the lowest rates of infection followed by AV grafts and then tunneled dialysis catheters4. Vascular access infections are common, and represent the second most common cause of death for patients receiving hemodialysis.5 • Lowest mortality and hospitalization: Patients using catheters (RR=2.3) and grafts (RR=1.47) have a greater mortality risk than patients dialyzed with fistulae6-9. Other studies have also found that use of fistulae reduces mortality and morbidity10-12 compared to AV grafts or catheters. References: 1. Mehta S: Statistical summary of clinical results of vascular access procedures for haemodialysis, in Sommer BG, Henry ML (eds): Vascular Access for Hemodialysis-II (ed 2). Chicago, IL, Gore, 1991, pp 145-157 2. The Cost Effectiveness of Alternative Types of Vascular access and the Economic Cost of ESRD. Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 1995, pp 139-157 3. Eggers P, Milam R: Trends in vascular access procedures and expenditures in Medicare’s ESRD program, in Henry ML (ed): Vascular Access for Hemodialysis-VII. Chicago, IL, Gore, 2001, pp 133-143 4. Nassar GM, Ayus JC: Infectious complications of the hemodialysis access. Kidney Int 60:1-13, 2001 5. Gulati S, Sahu KM, Avula S, Sharma RK, Ayyagiri A, Pandey CM: Role of vascular access as a risk factor for infections in hemodialysis. Ren Fail 25:967-973, 2003 6. Dhingra RK, Young EW, Hulbert-Shearon TE, Leavey SF, Port FK: Type of vascular access and mortality in U.S. hemodialysis patients. Kidney Int 60:1443-1451, 2001 7. Woods JD, Port FK: The impact of vascular access for haemodialysis on patient morbidity and mortality. Nephrol Dial Transplant 12:657-659, 1997 8. Xue JL, Dahl D, Ebben JP, Collins AJ: The association of initial hemodialysis access type with mortality outcomes in elderly Medicare ESRD patients. Am J Kidney Dis 42:1013-1019, 2003 9. Polkinghorne KR, McDonald SP, Atkins RC, Kerr PG: Vascular access and all-cause mortality: A propensity score analysis. J Am Soc Nephrol 15:477-486, 2004 10. Huber TS, Carter JW, Carter RL, Seeger JM: Patency of autogenous and polytetrafluoroethylene upper extremity arteriovenous hemodialysis accesses: A systematic review. J Vasc Surg 38(5):1005-11, 2003 11. Perera GB, Mueller MP, Kubaska SM, Wilson SE, Lawrence PF, Fujitani RM: Superiority of autogenous arteriovenous hemodialysis access: Maintenance of function with fewer secondary interventions. Ann Vasc Surg 18:66-73, 2004 12. Pisoni RL, Young EW, Dykstra DM, et al: Vascular access use in Europe and the United States: Results from the DOPPS. Kidney Int 61:305-316, 2002

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Renal 2015-2017
  
  
• Review for Importance: 1a. Evidence: H-4; M-14; L-0; I-0; 1b. Performance Gap: H-4; M-14; L-0; I-0 Rationale: The Committee agreed the evidence establishes the relationship between improved processes of care and health outcomes of interest in this population, but some Committee members suggested that, as a measure of long-term catheter usage in dialysis facilities, the measure may be more appropriately considered a process measure rather than an intermediate clinical outcome. • The majority of evidence supporting this measure substantiates the importance of decreasing long-term catheter usage in the broader ESRD population, however, there are continued concerns about impact on subpopulations, such as the frail-elderly. The Committee encouraged the developer to continue to assess impact on special population groups. • The Committee agreed with the Developer that, in general, there is an association between the type of vascular access used for hemodialysis and patient mortality and passed the measure on evidence. • The Committee noted that data provided by the developer show a decline in chronic catheter use over time. Disparities data showed a number of population groups were more likely to have catheters; these include women, older patients (75 years and older) and those patients who with an ESRD diagnosis for less than a year and those diagnosed for more than 9 years. White patients were less likely to have catheters. • The Committee generally agreed that the data provided showed there was opportunity for improvement. • Committee members discussed the developer’s finding that 18-25 year olds have higher rates of catheter usage; some Committee members noted that this is also the population with the highest rate of intravenous drug usage, suggesting that surgeons’ hesitance to operate on this population may be one reason for their higher rate of catheter usage.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-8; M-8; L-1; I-0; 2b. Validity: H-3; M-13; L-2; I-0 Rationale: • To demonstrate reliability, the developer calculated the inter-unit reliability (IUR) for annual performance scores on the measure. This analysis included facilities with at least 11 patients during the entire year. The Committee agreed with the Developer’s conclusion that an IUR of 0.765 (76.5%) suggests a high degree of reliability. • The Developer provided clarification for Committee member concerns that missing fields and other unknown data were counted as catheters. o The developer suggested this was done to provide a strong incentive for providers and facilities to report access and make sure that records were kept up-to-date. • The Committee members took issue with not taking vintage (length of time on dialysis) and insurance coverage into consideration, noting that these factors can contribute to very meaningful differences between certain facilities in any given area. • The type of insurance a patient has and whether they are capitated to a group that will provide the service may have a significant impact on timely vascular access for that patient. • The Committee requested the developer clarify information regarding insurance status, noting that many commercial entities are not participating in coverage under the Affordable Care Act (ACA). The Developer suggested that the decision to not risk-adjust the measure was made to avoid giving facilities a pass on issues that may be in their control.
  
  
• Review for Feasibility: 3. Feasibility: H-14; M-4; L-0; I-0 (3a. Data generated during care; 3b. Electronic sources; and 3c. Data collection can be implemented (eMeasure feasibility assessment of data elements and logic) Rationale: • The Committee agreed that the data is feasible to collect and most has already been collected. Committee members also agreed that the data elements are generated as part of the care delivery process.
  
  
• Review for Usability: 4. Usability and Use: H-10; M-8; L-0; I-0 Rationale: • The Developer stated that, upon endorsement, CMS will consider retiring the currently-endorsed measure of catheter use (#0256) in favor of this new measure for implementation in the End Stage Renal Disease Quality Improvement Program (ESRD QIP) and Dialysis Facility Compare in future performance years.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • This measure is related to: o 0251: Vascular Access—Functional Arteriovenous Fistula (AVF) or AV Graft or Evaluation for Placement o 0256 - Hemodialysis Vascular Access- Minimizing use of catheters as Chronic Dialysis Access o 0257 - Hemodialysis Vascular Access- Maximizing Placement of Arterial Venous Fistula (AVF) o 2977: Hemodialysis Vascular Access: Standardized Fistula Rate • The Committee was unable to discuss related and competing measures during the in-person meeting and will have the opportunity to do so during the post-comment call.
  
  
• Endorsement Public Comments: 6. Public and Member Comment • Three commenters supported the Committee’s recommendation to endorse the measure.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-18; N-0
  
  

Measure Specifications

• NQF Number (if applicable): 2977
  
  
• Description: Adjusted percentage of adult hemodialysis patient-months using an autogenous arteriovenous fistula (AVF) as the sole means of vascular access.
  
  
• Numerator: The numerator is the adjusted count of adult patient-months using an AVF as the sole means of vascular access as of the last hemodialysis treatment session of the month.
  
  
• Denominator: All patients at least 18 years old as of the first day of the reporting month who are determined to be maintenance hemodialysis patients (in-center and home HD) for the entire reporting month at the same facility.
  
  
• Exclusions: Exclusions that are implicit in the denominator definition include: •Pediatric patients (<18 years old) •Patients on Peritoneal Dialysis •Patient-months with in-center or home hemodialysis for less than a complete reporting month at the same facility In addition, the following exclusions are applied to the denominator: Patients with a catheter that have limited life expectancy: •Patients under hospice care in the current reporting month •Patients with metastatic cancer in the past 12 months •Patients with end stage liver disease in the past 12 months •Patients with coma or anoxic brain injury in the past 12 months
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Intermediate Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is intended to replace the existing vascular access type measure in the ESRD QIP. The measure is currently under review by the Renal Standing Committee. The Standing Committee and CSAC recommended the measure for endorsement.
  • Impact on quality of care for patients:This measure provides dialysis patients with information about the use of autogenous arteriovenous fistula (AVF) as the sole means of vascular access.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The evidence provide demonstrates an association between type of vascular access used for hemodialysis and the risk of patient mortality. The measure is intended to be jointly reported with Hemodialysis Vascular Access: Long-termCatheter Rate. Used together, the two vascular access quality measures consider Arterial VenousFistula (AVF) use as a positive outcome and prolonged use of a tunneled catheter as a negativeoutcome.
  
  
• Does the measure address a quality challenge? Yes. Analysis of CROWNWeb data from January 2014- December 2014 indicated the facility level mean percentage of patient-months with a fistula was 64.6% (SD=10.4%). Distribution: Min=9.2%, 1st quartile=57.8%, median=64.8%, 3rd quartile=71.7%, Max=97.5%.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure is an updated measure that intends to replace a similar measure currently in the program – Maximizing Placement of Arterial Venous Fistula (AVF) - NQF #0257. This measure differs from the previous fistula measure in that it adjusts for certain factors that might indicate a patient is inappropriate for fistula placement, or are at high risk for failure to mature. The measure will capture a broad population of adults receiving dialysis treatment at the facility level.
  
  
• Can the measure can be feasibly reported? Yes. A similar measure is currently in use and there is not a history of implementation challenges.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and specified. The Renal Standing Committee and CSAC recommended the measure for endorsement. The NQF Executive Committee is scheduled to review the measure in December 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The measure developers did not identify any unintended consequences.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The 2006 Clinical Practice Guidelines for Vascular Access is an update to the original vascular access guidelines published in 1997 by the National Kidney Foundation. In the eight years that the literature review included for the update, there have been no randomized controlled trials for type of vascular access. Specifically, for the guideline used to support this measure, a total of 84 peer-reviewed publications are included in the body of evidence presented. While these are all observational studies, some are based on either national data such as the United States Renal Data System (USRDS) that includes all patients with end stage kidney disease in the US, or international data, such as the Dialysis Outcomes Practice Pattern Study (DOPPS) that provides a global perspective for US vascular access outcomes. The overall quality of evidence is moderately strong. All studies are in the target population of hemodialysis patients. Some studies have evaluated health outcomes such as patient mortality, but have limitations due to the observational nature of the design. Other studies have more rigorous design, but use surrogate outcomes such as access thrombosis. The 12 studies listed below highlight the core benefits such as reduced mortality and morbidity associated with using an AV fistula relative to either an AV graft or a tunneled catheter. Specifically, AV fistulae have: • Lowest risk of thrombosis: in a systematic review of 34 studies evaluating access patency, AVF were found to have superior primary patency at 18 months compared to AV grafts (51% vs. 33%).1 • Lowest rate of angioplasty/intervention: Procedure rates have been reported as 0.53 procedures/patient/year for AV fistula compared to 0.92 procedures/patient/year for AV grafts.2 • Longest survival: Case-mix adjusted survival analysis indicated substantially better survival of AV fistula compared with AV grafts in the US [risk ratios (RR) of failure 0.56, P < 0.0009]3 • Lowest Cost4-6: Based on 1990 costs to Medicare, graft recipients cost HCFA (CMS) $3,700 more than fistula patients when pro-rating graft reimbursements to the median fistula survival time.5 • Lowest rates of infection: AV fistula have the lowest rates of infection followed by AV grafts and then tunneled dialysis catheters7. Vascular access infections are common, and represent the second most common cause of death for patients receiving hemodialysis.8 • Lowest mortality and hospitalization: Patients using catheters (RR=2.3) and grafts (RR=1.47) have a greater mortality risk than patients dialyzed with fistulae9. Other studies have also found that use of fistulae reduces mortality and morbidity10-12 compared to AV grafts or catheters. References: 1. Huber TS, Carter JW, Carter RL, Seeger JM: Patency of autogenous and polytetrafluoroethylene upper extremity arteriovenous hemodialysis accesses: A systematic review. J Vasc Surg 38(5):1005-11, 2003 2. Perera GB, Mueller MP, Kubaska SM, Wilson SE, Lawrence PF, Fujitani RM: Superiority of autogenous arteriovenous hemodialysis access: Maintenance of function with fewer secondary interventions. Ann Vasc Surg 18:66-73, 2004 3. Pisoni RL, Young EW, Dykstra DM, et al: Vascular access use in Europe and the United States: Results from the DOPPS. Kidney Int 61:305-316, 2002 4. Mehta S: Statistical summary of clinical results of vascular access procedures for haemodialysis, in Sommer BG, Henry ML (eds): Vascular Access for Hemodialysis-II (ed 2). Chicago, IL, Gore, 1991, pp 145-157 5. The Cost Effectiveness of Alternative Types of Vascular access and the Economic Cost of ESRD. Bethesda, MD, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 1995, pp 139-157 6. Eggers P, Milam R: Trends in vascular access procedures and expenditures in Medicare’s ESRD program, in Henry ML (ed): Vascular Access for Hemodialysis-VII. Chicago, IL, Gore, 2001, pp 133-143 7. Nassar GM, Ayus JC: Infectious complications of the hemodialysis access. Kidney Int 60:1-13, 2001 8. Gulati S, Sahu KM, Avula S, Sharma RK, Ayyagiri A, Pandey CM: Role of vascular access as a risk factor for infections in hemodialysis. Ren Fail 25:967-973, 2003 9. Dhingra RK, Young EW, Hulbert-Shearon TE, Leavey SF, Port FK: Type of vascular access and mortality in U.S. hemodialysis patients. Kidney Int 60:1443-1451, 2001 10. Woods JD, Port FK: The impact of vascular access for haemodialysis on patient morbidity and mortality. Nephrol Dial Transplant 12:657-659, 1997 11. Xue JL, Dahl D, Ebben JP, Collins AJ: The association of initial hemodialysis access type with mortality outcomes in elderly Medicare ESRD patients. Am J Kidney Dis 42:1013-1019, 2003 12. Polkinghorne KR, McDonald SP, Atkins RC, Kerr PG: Vascular access and all-cause mortality: A propensity score analysis. J Am Soc Nephrol 15:477-486, 2004

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Renal 2015-2017
  
  
• Review for Importance: 1a. Evidence: H-5; M-14; L-0; I-0; 1b. Performance Gap: H-10; M-8; L-1; I-0 Rationale: • The Committee agreed that there is sufficient evidence for measuring this intermediate outcome: o There is a definite association between type of vascular access used for hemodialysis and the risk of patient mortality. o The developer provided results of a systematic review of the evidence, concluding that a number of epidemiologic studies consistently demonstrate reduced morbidity and mortality associated with greater use of AV fistulas for vascular access in maintenance hemodialysis. o The measure is intended to be jointly reported with Hemodialysis Vascular Access: Long-term Catheter Rate. Used together, the two vascular access quality measures consider Arterial Venous Fistula (AVF) use as a positive outcome and prolonged use of a tunneled catheter as a negative outcome. • Committee members agreed with the developer’s rationale that the gap in performance and for disparities is significant. The developer notes that interquartile differences in measure performance from CROWNWeb show substantial disparities across a variety of demographic categories.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-4; M-15; L-0; I-0; 2b. Validity: H-6; M-13; L-0; I-0 18 Rationale: • The Committee agreed that the developer’s testing results showed sufficient reliability, with an inter-unit reliability analysis showing that about 74 percent of variation in measure scores could be attributable to true differences in performance scores between facilities. • Validity was tested by assessing the degree to which scores on this measure were correlated with scores on the Standardized Mortality Ratio and Standardized Hospitalization Ratio. • This analysis showed that Standardized Fistula Rates had a significantly negative association with risks of mortality and hospitalization. • Some Committee members suggested that the exclusions needed to be defined more specifically (e.g., using specific codes); it was also noted that the rate of exclusions seemed to be low. • The Committee also expressed concern that exclusions can only be applied to Medicare patients. The developer noted that their analyses showed that facilities’ proportion of Medicare patients did not impact performance scores, suggesting there is minimal risk of bias.
  
  
• Review for Feasibility: 3. Feasibility: H-16; M-3; L-0; I-0 (3a. Data generated during care; 3b. Electronic sources; and 3c. Data collection can be implemented (eMeasure feasibility assessment of data elements and logic) Rationale: • Members of the Committee agreed that the data is feasible to collect and most has already been collected. The Committee also agreed that the data elements are generated as part of the care delivery process.
  
  
• Review for Usability: 4. Usability and Use: H-7; M-12; L-0; I-0 (4a. Accountability/transparency; and 4b. Improvement – progress demonstrated; and 4c. Benefits outweigh evidence of unintended negative consequences) Rationale: • The Developer stated that, upon endorsement, CMS will consider retiring the currently-endorsed measure of fistula use (#0257) in favor of this new measure for implementation in the End Stage Renal Disease Quality Improvement Program (ESRD QIP) and Dialysis Facility Compare in future performance years. • Though the measure is not yet implemented in a public reporting program, CMS expects implementation of the standardized fistula rate measure. • The Committee had concerns that there may be subsets of patients other than those excluded for which fistula use is not as well correlated with poor outcomes. Additionally, patient choice is not considered, potentially causing pressure for patients to undergo multiple procedures to establish fistulae.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • This measure is related to: o 0251: Vascular Access—Functional Arteriovenous Fistula (AVF) or AV Graft or Evaluation for Placement o 0256: Hemodialysis Vascular Access-Minimizing use of catheters as Chronic Dialysis Access o 0257: Hemodialysis Vascular Access-Maximizing Placement of Arterial Venous Fistula (AVF) o 2978: Hemodialysis Vascular Access: Long-term Catheter Rate • The Committee was unable to discuss related and competing measures during the in-person meeting and will have the opportunity to do so during the post-comment call.
  
  
• Endorsement Public Comments: 6. Public and Member Comment • The Kidney Care Partners has recommended the developer consider the following modifications to improve the measure going forward: o Stating that the specifications for #2977 are too imprecise, suggest the numerator specifies the 19 NQF VOTING DRAFT—Votes due by October 21, 2016 by 6:00 PM ET. 2977 Hemodialysis Vascular Access: Standardized Fistula Rate patient must be on maintenance hemodialysis “using an AVF with two needles and without a dialysis catheter present.” Additional, credit should be received for a patient who is using an AVF as the sole means of access, but who also may have a non-functioning AV graft present. o Suggest that two additional vasculature risk variables that could strengthen the model be added: a history of multiple prior accesses and the presence of a cardiac device. • The Committee discussed the comment submitted and the developer’s response. The Committee agreed with the suggestions and recommended that the developer work toward these goals for future iterations of this measure.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-19; N-0
  
  

Measure Specifications

• NQF Number (if applicable): 2979
  
  
• Description: The risk adjusted facility level transfusion ratio “STrR” is specified for all adult dialysis patients. It is a ratio of the number of eligible red blood cell transfusion events observed in patients dialyzing at a facility, to the number of eligible transfusion events that would be expected under a national norm, after accounting for the patient characteristics within each facility. Eligible transfusions are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.
  
  
• Numerator: Number of eligible observed red blood cell transfusion events: An event is defined as the transfer of one or more units of blood or blood products into a recipient’s blood stream (code set is provided in the numerator details) among patients dialyzing at the facility during the inclusion episodes of the reporting period. Inclusion episodes are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.
  
  
• Denominator: Number of eligible red blood cell transfusion events (as defined in the numerator statement) that would be expected among patients at a facility during the reporting period, given the patient mix at the facility. Inclusion episodes are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.
  
  
• Exclusions: All transfusions associated with transplant hospitalization are excluded. Patients are also excluded if they have a Medicare claim for: hemolytic and aplastic anemia, solid organ cancer (breast, prostate, lung, digestive tract and others), lymphoma, carcinoma in situ, coagulation disorders, multiple myeloma, myelodysplastic syndrome and myelofibrosis, leukemia, head and neck cancer, other cancers (connective tissue, skin, and others), metastatic cancer, and sickle cell anemia within one year of their patient time at risk. Since these comorbidities are associated with higher risk of transfusion and require different anemia management practices that the measure is not intended to address, every patient’s risk window is modified to have at least 1 year free of claims that contain these exclusion eligible diagnoses.
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has undergone substantial changes but details of the changes to the measure are not provided. The measure is currently under review by the Renal Standing Committee. The Standing Committee and CSAC recommended the measure for endorsement.
  • Impact on quality of care for patients:This measure encourages dialysis facilities to avoid blood transfusions when managing patients with anemia.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Reliance on achieved hemoglobin concentration as an indicator of successful anemia management in this population has been de-emphasized and use of other clinically meaningful outcomes, such as transfusion avoidance, have been recommended as alternate measures of anemia management.Best dialysis provider practice should include effective anemia management algorithms that focus on 1) prevention and treatment of iron deficiency, inflammation and other causes of ESA resistance, 2) use of the lowest dose of ESAs that achieves an appropriate target hemoglobin that is consistent with FDA guidelines and current best practices, and 3) education of patients, their families and medical providers to avoid unnecessary blood transfusion so that risk of allosensitization is minimized, eliminating or reducing one preventable barrier to successful kidney transplantation.
  
  
• Does the measure address a quality challenge? Yes. The distribution of standardized transfusion ratio (STrR) using Medicare claims data ranged from from a mean of 1.029 in 2011 to a mean of 1.034 in 2014. Data provided to the Renal Standing Committee demonstrated that approximately 93.0% of facilities are performing as expected, 0.4% better and 6.5% worse.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is not duplicative of other measures in the measure set, as it will be replacing the current measure that captures this event. Details outlining changes to the measure are not provided.
  
  
• Can the measure can be feasibly reported? Yes. Yes, the data for the measure are derived from an existing national ESRD patient database and has been publicly reported since 2014. Information on transfusions is obtained from Medicare Inpatient and Outpatient Claims Standard Analysis Files (SAFs).
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and specified. The Renal Standing Committee and CSAC recommended the measure for endorsement. The NQF Executive Committee is scheduled to review the measure in December 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The measure developers do not identify any unintended consequences of using the measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The Medicare ESRD Program requires Medicare certified dialysis facilities to manage the anemia of CKD as one of their responsibilities under the Conditions for Coverage (1). In addition, the Medicare ESRD Program has included payment for ESAs in dialysis facility reimbursement since 1989. It is notable that inclusion of ESAs in dialysis program payment was associated with a dramatic reduction in the use of blood transfusions in the US chronic dialysis population (2-3). Recently, reliance on achieved hemoglobin concentration as an indicator of successful anemia management in this population has been de-emphasized and use of other clinically meaningful outcomes, such as transfusion avoidance, have been recommended as alternate measures of anemia management (4-7). Best dialysis provider practice should include effective anemia management algorithms that focus on 1) prevention and treatment of iron deficiency, inflammation and other causes of ESA resistance, 2) use of the lowest dose of ESAs that achieves an appropriate target hemoglobin that is consistent with FDA guidelines and current best practices, and 3) education of patients, their families and medical providers to avoid unnecessary blood transfusion so that risk of allosensitization is minimized, eliminating or reducing one preventable barrier to successful kidney transplantation. The decision to transfuse blood is intended to improve or correct the pathophysiologic consequences of severe anemia, defined by achieved hemoglobin or hematocrit%, in a specific clinical context for each patient situation (8). Consensus guidelines in the U.S. and other consensus guidelines defining appropriate use of blood transfusions are based, in large part, on the severity of anemia (9-11). Given the role of hemoglobin as a clinical outcome that defines anemia as well as forms a basis for consensus recommendations regarding use of blood transfusion, it is not surprising that the presence of decreased hemoglobin concentration is a strong predictor of subsequent risk for blood transfusion in multiple settings, including chronic dialysis (12-21). For example, Gilbertson, et al found a nearly four-fold higher risk-adjusted transfusion rate in dialysis patients with achieved hemoglobin <10 gm/dl compared to those with >10 gm/dl hemoglobin. (19) In addition to achieved hemoglobin, other factors related to dialysis facility practices, including the facility’s response to their patients achieved hemoglobin, may influence blood transfusion risk in the chronic dialysis population (22, 25). In an observational study recently published by Molony, et al (2016) comparing different facility level titration practices, among patients with hemoglobin <10 and those with hemoglobin>11, they found increased transfusion risk in patients with larger ESA dose reductions and smaller dose escalations, and reduced transfusion risk in patients with larger ESA dose increases and smaller dose reductions (25). The authors reported no clinically meaningful differences in all-cause or cause-specific hospitalization events across groups. The Food and Drug Administration position defining the primary indication of ESA use in the CKD population is for transfusion avoidance, reflecting the assessment of the relative risks and benefits of ESA use versus blood transfusion. Several historical studies, and one recent research study reviewed by Obrador and Macdougall, document the specific risks of allosensitization after blood transfusion and the potential for transfusion-associated allosensitization to interfere with timely kidney transplantation. (23) A recent analysis demonstrated increased odds ratios for allosensitization associated with transfusion, particularly for men and parous women. That study also demonstrated a 28% reduction in likelihood of transplantation in transfused individuals, based on a multivariate risk-adjusted statistical model. (24)

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Renal 2015-2017
  
  
• Review for Importance: 1a. Evidence: Y-18; N-2; 1b. Performance Gap: H-2; M-12; L-5; I-1 Rationale: • The Committee discussed whether or not this measure would be more appropriately categorized as an intermediate outcome. The Committee discussed how the use of scarce resources, particularly when comparing an event to a non-event--even if it is a relatively scarce event-- is considered an appropriate health outcome metric for the healthcare system, but not for the individual patient. The Committee proceeded to evaluate the measure as an outcome measure. • The Committee passed the measure on evidence, agreeing that providers can take actions (e.g., utilization of treatments to increase blood cell production) to reduce the occurrence of transfusions. • Committee members noted that dialysis patients who are eligible for kidney transplant and are transfused risk the development of becoming sensitized to the donor pool, thereby leading to potential negative consequences for kidney transplantation. Monitoring the risk-adjusted transfusion rate at the dialysis facility level, relative to a national standard, allows for detection of treatment patterns in dialysis-related anemia management. • Some Committee members noted they found the evidence to be most convincing in terms of negative downstream implications for a kidney transplant; others noted that downstream effects are difficult to know, as are the appropriate number of transplants in terms of cost and patient outcomes. Overall, the Committee agreed that the national standard of practice is transfusion avoidance. • CROWNWeb and Medicare claims data for 2011-2014 showed that standardized transfusion ratios vary across facilities. Analyses of the standardized transfusion ratios (STrR) by race, sex and ethnicity indicate relatively little variation and no disparities substantial to the measure among these groups. The Committee agreed that opportunity for improvement for performance of this measure remains moderate.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-0; M-15; L-5; I-0; 2b. Validity: H-0; M-15; L-5; I-0 Rationale: • Some Committee members had concerns about the specifications, specifically the lack of exclusion related to patients who may need transfusions due to acute gastrointestinal bleeds, trauma, or other unplanned surgery. • Developers provided results of reliability testing of the performance measure score using Medicare claims data from 2011-2014 at the facility level of analysis. Inter-unit reliability (IUR) was estimated using a bootstrap approach, which uses a resampling scheme to estimate the within-facility variation that cannot be directly estimated by a one-way analysis of variance. IURs had a range of 0.60-0.66 across the years 2011, 2012, 2013 and 2014, indicating that around two-thirds of the variation in the one-year STrR can be attributed to the between-facility differences and one-third to within-facility variation. Committee members noted that when stratified by facility size, larger facilities have greater IUR. The Committee agreed that the testing results demonstrate moderate reliability. • To demonstrate validity of the performance measure score, developers used Poisson regression models to measure the association between STrR and other facility level outcomes, Standardized Mortality Ratio (SMR, NQF #0369) and Standardized Hospitalization Ratio (SHR, NQF 1463). The results from the Poisson model indicated that the StrR tertiles were significantly associated with both SMR and SHR. The developer also noted that a similar analysis was performed to compare StTR scores with facility-achieved hemoglobin levels; the analysis found that the percentage of patients with hemoglobin greater than 10 was positively associated with risk of transfusion. • In addition, face validity was demonstrated, including a statement from the developers that six out of the six voting members of CMS's 2012 Technical Expert Panel voted to recommend the development of a facility-level standardized transfusion average. Overall, the Committee agreed that the testing results demonstrate moderate validity.
  
  
• Review for Feasibility: 3. Feasibility: H-15; M-4; L-0; I-0 (3a. Data generated during care; 3b. Electronic sources; and 3c. Data collection can be implemented (eMeasure feasibility assessment of data elements and logic) Rationale: • The Committee agreed that it is feasible to collect the data. Members also agreed that the data elements are generated as part of the care delivery process.
  
  
• Review for Usability: 4. Usability and Use: H-5; M-13; L-1; I-0(4a. Accountability/transparency; and 4b. Improvement – progress demonstrated; and 4c. Benefits outweighevidence of unintended negative consequences)Rationale:• This measure is publically reported nationally in Dialysis Facility Compare (DFC) and will be in End StageRenal Disease Quality Incentive Program (ESRD QIP) starting 2018.• Committee members noted that a potential unintended consequence of the STrR would be to create anincentive for dialysis facilities to target higher hemoglobin levels, as targeting hemoglobin concentrationsabove 12 to 13 grams per deciliter is associated with elevated risk of cardiac events and related mortality.However, the Committee accepted the developer’s rationale that the potential for unintendedconsequences is low with appropriate provider anemia management practices.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • No related or competing measures noted
  
  
• Endorsement Public Comments: 6. Public and Member Comment • The Kidney Care Partners notes that during the last project, this Standing Committee reviewed the STrR as #2699 and did not recommend it. The commenter expresses concerns about the specifications, reliability, validity (risk model), and harmonization. In regards to validity, the commenter does not believe the new measure addressed the Committee’s concerns about hospital- and physician-related factors. Overall, they remain concerned about the reliability, as well as the specifications and validity. The commenter strongly encourage the Committee to reconsider the reliability testing data, which document reliability issues with the STrR for small facilities, and comment specifically on the STrR’s reliability for such facilities. • The Committee thoroughly reviewed the specifications, reliability, and validity of the measure during the in-person and maintained that the measure meets the NQF criteria.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-16; N-4
  
  

Measure Specifications

• NQF Number (if applicable): 1664
  
  
• Description: The measure is reported as an overall rate which includes all hospitalized patients 18 years of age and older to whom alcohol or drug use disorder treatment was provided, or offered and refused, at the time of hospital discharge, and a second rate, a subset of the first, which includes only those patients who received alcohol or drug use disorder treatment at discharge. The Provided or Offered rate (SUB-3) describes patients who are identified with alcohol or drug use disorder who receive or refuse at discharge a prescription for FDA-approved medications for alcohol or drug use disorder, OR who receive or refuse a referral for addictions treatment.
  
  
• Numerator: SUB-3: The number of patients who received or refused at discharge a prescription for medication for treatment of alcohol or drug use disorder OR received or refused a referral for addictions treatment. SUB-3a: The number of patients who received a prescription at discharge for medication for treatment of alcohol or drug use disorder OR a referral for addictions treatment.
  
  
• Denominator: The number of hospitalized inpatients 18 years of age and older identified with an alcohol or drug use disorder
  
  
• Exclusions: There are 11 exclusions to the denominator as follows: • Patients less than 18 years of age • Patient drinking at unhealthy levels who do not meet criteria for an alcohol use disorder • Patients who are cognitively impaired • Patients who expire • Patients discharged to another hospital • Patients who left against medical advice • Patients discharged to another healthcare facility • Patients discharged to home or another healthcare facility for hospice care • Patients who have a length of stay less than or equal to three days or greater than 120 days • Patients who do not reside in the United States • Patients receiving Comfort Measures Only documented
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record, Paper Medical Record
  
  
• Measure Type: Process
  
  
• Steward: The Joint Commission
  
  
• Endorsement Status: Endorsed
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is NQF-endorsed at the facility level in the hospital/acute care setting. This measure is currently in the IPFQR program. However, no scientific evidence provided to demonstrate that patients who received a prescription at discharge for the treatment of alcohol or drug use disorder or a referral for addictions treatment received treatment after discharge.
  • Impact on quality of care for patients:This measure encourages hospitals to provide patients with a prescription for the treatment of alcohol or drug use disorder or a referral for addictions treatment.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. No scientific evidence provided to demonstrate that patients who received a prescription at discharge for the treatment of alcohol or drug use disorder or a referral for addictions treatment received treatment after discharge.
  
  
• Does the measure address a quality challenge? Yes. In a study on the provision of evidence-based care and preventive services provided in hospitals for 30 different medical conditions, quality varied substantially according to diagnosis. Adherence to recommended practices for treatment of substance use ranked last, with only 10% of patients receiving proper care (Gentilello LM, Ebel BE, Wickizer TM, Salkever DS Rivera FP. Alcohol interventions for trauma patients treated in emergency departments and hospitals: A cost benefit analysis. Ann Surg. 2005 Apr;241(4):541-50). Currently, less than one in twenty patients with an addiction is referred for treatment (Gentilello LM, Villaveces A, Ries RR, Nason KS, Daranciang E, Donovan DM Copass M, Jurkovich GJ Rivara FP. Detection of acute alcohol intoxication and chronic alcohol dependence by trauma center staff. J Trauma. 1999 Dec;47(6):1131-5; discussion 1135-9).
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is NQF-endorsed at the facility level in the hospital/acute care setting.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. No implementation issues have been identified in the IPFQR program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In a study on the provision of evidence-based care and preventive services provided in hospitals for 30 different medical conditions, quality varied substantially according to diagnosis. Adherence to recommended practices for treatment of substance use ranked last, with only 10% of patients receiving proper care (McGlynn 2003, Gentilello 2005). Currently, less than one in twenty patients with an addiction are referred for treatment (Gentilello 1999). Unfortunately, many physicians mistakenly believe that substance use problems are largely confined to the young. They are significantly less likely to recognize an alcohol problem in an older patient than in a younger one. (Curtis 1989) As a result, these problems usually go undetected, resulting in harmful, expensive, and sometimes even catastrophic consequences. This is demonstrated by the fact that few older adults who need substance use treatment actually receive it. In 2005, persons 65 years and older made up only 11,344 out of 1.8 million substance use treatment episodes recorded.(SAMHSA 2007) • Gentilello LM, Ebel BE, Wickizer TM, Salkever DS Rivera FP. Alcohol interventions for trauma patients treated in emergency departments and hospitals: A cost benefit analysis. Ann Surg. 2005 Apr;241(4):541-50. • Gentilello LM, Villaveces A, Ries RR, Nason KS, Daranciang E, Donovan DM Copass M, Jurkovich GJ Rivara FP. Detection of acute alcohol intoxication and chronic alcohol dependence by trauma center staff. J Trauma. 1999 Dec;47(6):1131-5; discussion 1135-9. • McGlynn, EA, Asch SM, Adams J, Keesey J, et al. The New England Journal of Medicine. Boston: Jun 26, 2003. Vol. 348, Iss.26; pg. 2635, 11pgs. • Curtis, J.R.; Geller, G.; Stokes, E.J. ; et al. Characteristics, diagnosis, and treatment of alcoholism in elderly patients. J Am Geriatr Soc 37:310-316, 1989. • SAMHSA. Office of Applied Studies. Older adults in substance abuse treatment: 2005. The DASIS Report. Rockville MD, November 8, 2007.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2014
  
  
• Project for Most Recent Endorsement Review: Behavioral Health
  
  
• Review for Importance: 1a. Impact: H-16; M-2; L-0; I-0; 1b. Performance Gap: H-12; M-6; L-0; I-0; 1c. Evidence: Y-16; N-1; I-1 Rationale: • The Steering Committee initially reviewed and rated the Importance criteria for this measure on April 18, 2012, during the first phase of this project; accordingly, Importance to Measure and Report was not discussed during the phase two meeting. Instead, the votes from Phase 1 were carried over, and appear above.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-0; M-19; L-0; I-0; 2b. Validity: H-0; M-16; L-5; I-0 Rationale: • The Steering Committee agreed the measure meets the criteria. Reliability involved the re-abstraction of 96 medical records at five hospitals and resulted in an overall agreement rate to 96.2 percent for SUB-3 and 93.8 percent for SUB-3a. • The face validity of the measure was initially assessed through a public comment period and issues identified were addressed through measure revisions. An alpha test was then incorporated into the pilot test of the measure to reevaluate its validity. Finally, an eleven member Technical Advisory Panel was asked to review the measure specifications on a five point scale. The measure score varied from 3.85 to 5.0 based on clarity of specifications, usefulness, interpretability, data accessibility and ease of collection and national use. • A Steering Committee member expressed concern that the measure includes alcohol as well as other drug use disorders, which creates a broad measure and potentially an additional burden for providers. Members also noted that incorporating a prescription at discharge may be problematic since use of medications for substance abuse may not be as efficacious as medications to treat other addictions, such as tobacco. o The developer referenced a table, linked to the measure, which indicates medications approved by the FDA that could be prescribed to patients. They also clarified that the measure only focuses on the patient’s receipt of a prescription, and does not address patient compliance. o The Steering Committee expressed concern that medications for substance abuse may be expensive, which could deter patients from actually filling a prescription but ultimately agreed with the measure, noting the measure is constructed to allow patients to receive a prescription OR a referral for treatment. • The Steering Committee reviewed the measure testing results regarding the identification of meaningful differences in performance and noted that the measure had an overall rate of 3.5 percent, a significant decrease from the baseline of 9.2 percent. This indicates that there was a reduction of differences in performance for the measure among hospitals implementing the measure.
  
  
• Review for Feasibility: 4. Feasibility: H-0; M-11; L-10; I-0 (4a. Clinical data generated during care delivery; 4b. Electronic sources; 4c.Susceptibility to inaccuracies/ unintended consequences identified 4d. Data collection strategy can be implemented) Rationale: • The Steering Committee agreed the measure is feasible and some data elements are available in electronic sources. In the future the developer plans to further develop electronic specifications for the measure. • A Steering Committee member expressed concern that the measure includes alcohol as well as other drug use disorders, which could create an additional burden for providers, and that generating the data elements requires chart review. o The developer clarified that providers would also need to conduct chart reviews in measures 1661 SUB-1 Alcohol use screening and 1663 SUB-2 Alcohol use brief intervention provided or offered and Sub-2a Alcohol use brief intervention. The developer also noted that hospitals currently implementing the substance abuse suite of measures rely on electronic health records to reduce the burden.
  
  
• Review for Usability: 3. Usability: H-2; M-11; L-8; I-0 (Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting/Accountability and 3b. Quality Improvement) Rationale: • The Steering Committee agreed the measure is usable. CMS has indicated that this measure will be required for reporting for inpatient psychiatric hospitals and psych units in general hospitals starting in 2016.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • This measure is related to the other measures in the SUB suite of measures in addition to the AMA-PCPI measure #2152 – Preventive Care and Screening: Unhealthy Diagnosis.
  
  
• Endorsement Public Comments: See 1661
  
  
• Endorsement Committee Recommendation: Steering Committee Recommendation for Endorsement: Y-11; N-9 • The Steering Committee recommended that the developer expand the measure population to include adolescents (aged 13 and older) to make the measure more consistent with Meaningful Use and to incorporate an age group that also struggles with substance use disorders. The developer noted that they would review the evidence for extending the age range of the measure in the future.
  
  

Measure Specifications

• NQF Number (if applicable): 1663
  
  
• Description: The measure is reported as an overall rate which includes all hospitalized patients 18 years of age and older to whom a brief intervention was provided, or offered and refused, and a second rate, a subset of the first, which includes only those patients who received a brief intervention. The Provided or Offered rate (SUB-2), describes patients who screened positive for unhealthy alcohol use who received or refused a brief intervention during the hospital stay. The Alcohol Use Brief Intervention (SUB-2a) rate describes only those who received the brief intervention during the hospital stay. Those who refused are not included. These measures are intended to be used as part of a set of 4 linked measures addressing Substance Use (SUB-1 Alcohol Use Screening ; SUB-2 Alcohol Use Brief Intervention Provided or Offered; SUB-3 Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge; SUB-4 Alcohol and Drug Use: Assessing Status after Discharge [temporarily suspended]).
  
  
• Numerator: SUB-2 The number of patients who received or refused a brief intervention. SUB-2a The number of patients who received a brief intervention.
  
  
• Denominator: The number of hospitalized inpatients 18 years of age and older who screen positive for unhealthy alcohol use or an alcohol use disorder (alcohol abuse or alcohol dependence).
  
  
• Exclusions: The denominator has five exclusions as follows: • Patients less than 18 years of age • Patient who are cognitively impaired • Patients who refused or were not screened for alcohol use during the hospital stay • Patients who have a length of stay less than or equal to three days and greater than 120 days • Patients receiving Comfort Measures Only documented
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record, Paper Medical Record
  
  
• Measure Type: Process
  
  
• Steward: The Joint Commission
  
  
• Endorsement Status: Endorsed
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is NQF-endorsed at the facility level in the hospital/acute care setting. This measure is currently in the IPFQR program; no implementation issues have been identified.
  • Impact on quality of care for patients:This measure encourages hospitals to provide brief interventions to patients with unhealthy alcohol use.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Excessive alcohol use places drinkers, their families, and their communities at risk for many harmful health effects, including chronic conditions, sexual risk behaviors, motor vehicle crashes, violence and injuries and fetal alcohol spectrum discorders.
  
  
• Does the measure address a quality challenge? Yes. In a study on the provision of evidence-based care and preventive services provided in hospitals for 30 different medical conditions, quality varied substantially according to diagnosis. Adherence to recommended practices for treatment of substance use ranked last, with only 10% of patients receiving proper care (Gentilello LM, Ebel BE, Wickizer TM, Salkever DS Rivera FP. Alcohol interventions for trauma patients treated in emergency departments and hospitals: A cost benefit analysis. Ann Surg. 2005 Apr;241(4):541-50). Currently, less than one in twenty patients with an addiction is referred for treatment (Gentilello LM, Villaveces A, Ries RR, Nason KS, Daranciang E, Donovan DM Copass M, Jurkovich GJ Rivara FP. Detection of acute alcohol intoxication and chronic alcohol dependence by trauma center staff. J Trauma. 1999 Dec;47(6):1131-5; discussion 1135-9).
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is NQF-endorsed at the facility level in the hospital/acute care setting.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. No implementation issues have been identified in the IPFQR program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Excessive use of alcohol has a substantial harmful impact on health and society in the United States. It is a drain on the economy and a source of enormous personal tragedy. In 2010, excessive alcohol use cost the US economy $249 billion, or $2.05 a drink, and $2 of every $5 of these costs were paid by the public. More than 537,000 persons died as a consequence of alcohol, drug, and tobacco use, making them the cause of more than one out of four deaths in the United States.1 Excessive alcohol use places drinkers, their families, and their communities at risk for many harmful health effects, including: Chronic conditions. Over time, excessive drinking can lead to high blood pressure, various cancers, heart disease, stroke, and liver disease. Sexual risk behaviors. Excessive drinking increases sexual risk behaviors, which can result in unintended pregnancy, HIV infection, and other sexually transmitted diseases. Motor vehicle crashes. Excessive drinking can lead to motor vehicle crashes, resulting in injuries and deaths. Binge drinkers are responsible for most of the alcohol-impaired driving episodes involving US adults. Violence and injuries. Excessive alcohol use can lead to falls, drowning, homicide, suicide, intimate partner violence, and sexual assault. Fetal alcohol spectrum disorders. Any alcohol use by a pregnant woman can harm a developing fetus, resulting in physical, behavioral, and learning problems later in life. Hospitalization provides a prime opportunity to address substance use, and for many patients, controlling their other health problems requires addressing their substance use.2 Approximately 8% of general hospital inpatients and 40 to 60% of traumatically injured inpatients and psychiatric inpatients have substance use disorders. 3 1. Mokdad AH, Marks JS, Stroup DS, Geberding JL. Actual Causes of Death in the United States, 2000. JAMA 2004;291:128-1245. 2. Fleming MF, Mundt MP, French MT, Manwell LB, Stauffacher EA, Barry KL. Brief physician advice for problem drinkers: Long-term efficacy and cost-benefit analysis. Alcohol Clin Exp Res. 2002 Jan;26(1):36-43. 3. Gentilello LM, Villaveces A, Ries RR, Nason KS, Daranciang E, Donovan DM, Copass M, Jurkovick GJ, Rivara FP. Detection of acute intoxication and chronic alcohol dependence by trauma center staff. J Trauma. 1999 Dec;47(6):1131-5; discussion 1135-9.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2014
  
  
• Project for Most Recent Endorsement Review: Behavioral Health
  
  
• Review for Importance: 1a. Impact: H-18; M-1; L-0; I-0; 1b. Performance Gap: H-11; M-8; L-0; I-0; 1c. Evidence: Y-14; N-0; I-5 Rationale: • The Steering Committee initially reviewed and rated the Importance criteria for this measure on April 18, 2012, during the first phase of this project; accordingly, Importance to Measure and Report was not discussed during the phase two meeting. Instead, the votes from Phase 1 were carried over, and appear above.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-2; M-19; L-0; I-0; 2b. Validity: H-0; M-16; L-5; I-0 Rationale: • The Steering Committee agreed that the measure meets the criteria. Reliability involved the reabstraction of 96 medical records at five hospitals. Initial reliability testing indicated an agreement rate of 71.4 percent; however, improvements to the measure focusing on skip logic, refinement of data definitions and notes for abstraction increased the agreement rate to 80.2 percent. Following the reabstraction, focus groups were conducted at each hospital and differences in abstraction were further discussed and highlighted as an opportunity for improvement on the measure. • The face validity of the measure was initially assessed through a public comment period and issues identified were addressed through measure revisions. An alpha test was then incorporated into the pilot test of the measure to reevaluate its validity. Finally, an eleven member Technical Advisory Panel was asked to review the measure specifications on a five point scale. The measure score varied from 3.87 to 4.9 based on clarity of specifications, usefulness, interpretability, data accessibility and ease of collection and national use. • A Steering Committee member requested clarification regarding the type of individual and training required for those delivering brief interventions to patients. o The developer explained that they have created educational standards and core competencies, which are required for individuals who will be performing the interventions. They also stated that in general hospitals develop a cadre of trained people to provide the brief intervention. It was also noted that brief interventions are different from brief counseling. • Steering Committee members discussed that the measure could be improved by conducting a brief intervention for patients with unhealthy alcohol use and referring patients with an alcohol disorder rate to additional services rather than using a brief intervention for all patients with unhealthy alcohol use. This approach may also lessen the burden on providers to administer brief interventions to patients. However, the Steering Committee concluded that conducting a brief intervention could help guide the referral and create a greater willingness in the patient to follow through with cessation.
  
  
• Review for Feasibility: 4. Feasibility: H-0; M-14; L-7; I-0 (4a. Clinical data generated during care delivery; 4b. Electronic sources; 4c.Susceptibility to inaccuracies/ unintended consequences identified 4d. Data collection strategy can be implemented) Rationale: • The Steering Committee agreed the measure is feasible and some data elements are available in electronic sources. In the future the developer plans to further develop electronic specifications for the measure. • A Steering Committee member questioned whether the measure may be more feasible in sites dedicated to screening for alcohol misuse, and more difficult to implement in the general populous.
  
  
• Review for Usability: 3. Usability: H-2; M-14; L-5; I-0 (Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting/Accountability and 3b. Quality Improvement) Rationale: • The Steering Committee agreed the measure is usable. CMS has indicated that this measure will be required for reporting for inpatient psychiatric hospitals and psych units in general hospitals starting in 2016. • A Steering Committee member noted that the measure appropriate
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • This measure is related to the other measures in the SUB suite of measures in addition to the AMA-PCPI measure #2152 – Preventive Care and Screening: Unhealthy Diagnosis.
  
  
• Endorsement Public Comments: See 1661
  
  
• Endorsement Committee Recommendation: Steering Committee Recommendation for Endorsement: Y-16; N-5 • The Steering Committee recommended that the developer expand the measure population to include adolescents (aged 13 and older) to make the measure more consistent with Meaningful Use and to incorporate an age group that also struggles with substance use disorders. The developer noted that they would review the evidence for extending the age range of the measure in the future.
  
  

Measure Specifications

• NQF Number (if applicable): 1661
  
  
• Description: Hospitalized patients 18 years of age and older who are screened within the first three days of admission using a validated screening questionnaire for unhealthy alcohol use. This measure is intended to be used as part of a set of 4 linked measures addressing Substance Use (SUB-1 Alcohol Use Screening; SUB-2 Alcohol Use Brief Intervention Provided or Offered; SUB-3 Alcohol and Other Drug Use Disorder Treatment Provided or Offered at Discharge; SUB-4 Alcohol and Drug Use: Assessing Status after Discharge [temporarily suspended]).
  
  
• Numerator: The number of patients who were screened for alcohol use using a validated screening questionnaire for unhealthy drinking within the first three days of admission.
  
  
• Denominator: The number of hospitalized inpatients 18 years of age and older
  
  
• Exclusions: The denominator has four exclusions: • Patients less than 18 years of age • Patients who are cognitively impaired • Patients who a have a duration of stay less than or equal to three days or greater than 120 days • Patients with Comfort Measures Only documented
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record, Paper Medical Record
  
  
• Measure Type: Process
  
  
• Steward: The Joint Commission
  
  
• Endorsement Status: Endorsed
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is NQF-endorsed at the facility level in the hospital/acute care setting. This measure is currently in the IPFQR program and publicly reported on Hospital Compare. No implementation issues have been identified.
  • Impact on quality of care for patients:This measure encourages hospitals to screen patients for unhealthy alcohol use.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Brief interventions can be delivered to patients identifed with a validated tool as using alcohol at unhealthy levels.
  
  
• Does the measure address a quality challenge? Yes. In a study on the provision of evidence-based care and preventive services provided in hospitals for 30 different medical conditions, quality varied substantially according to diagnosis. Adherence to recommended practices for treatment of substance use ranked last, with only 10% of patients receiving proper care (Gentilello LM, Ebel BE, Wickizer TM, Salkever DS Rivera FP. Alcohol interventions for trauma patients treated in emergency departments and hospitals: A cost benefit analysis. Ann Surg. 2005 Apr;241(4):541-50). Currently, less than one in twenty patients with an addiction is referred for treatment (Gentilello LM, Villaveces A, Ries RR, Nason KS, Daranciang E, Donovan DM Copass M, Jurkovich GJ Rivara FP. Detection of acute alcohol intoxication and chronic alcohol dependence by trauma center staff. J Trauma. 1999 Dec;47(6):1131-5; discussion 1135-9).From January 1, 2014 to December, 31, 2014, 71.0% of patients admitted to inpatient psychiatric hospitals received alcohol screening (hospitalcompare.gov).
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes . The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program and publicly reported on Hospital Compare.
  
  
• Can the measure can be feasibly reported? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program and publicly reported on Hospital Compare.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is NQF-endorsed at the facility level in the hospital/acute care setting.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. No implementation issues have been identified in the IPFQR program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
It was the expert opinion of our advisory panel that implementation of this measure would lead to the provision of brief interventions for patients at risk for excessive alcohol use and alcohol-related harms. Evidence-based screening instruments exist that can detect harmful alcohol use. Brief interventions that can be delivered during a single primary care office visit have been tested in multiple randomized trials, including a multi-center one in the Medicare eligible age group. They demonstrate that screening and intervention significantly reduce health risks, and generate cost savings of approximately $4 dollars for every dollar invested in providing them. (Fleming 1999) Clinical trials have demonstrated that brief interventions, especially prior to the onset of addiction, significantly improve health and reduce costs, and that similar benefits occur in those with addictive disorders who are referred to treatment (SAMHSA 2007, NIAAA 2005, Fleming 2002). Yet, according to a recent study by CDC and SAMHSA, 9 in 10 excessive drinkers are not alcohol dependent (Esser MB, Hedden SL, Kanny D, Brewer RD, Gfroerer JC, Naimi TS. Prevalence of Alcohol Dependence Among US Adult Drinkers, 2009–2011. Prev Chronic Dis 2014;11:140329).

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2014
  
  
• Project for Most Recent Endorsement Review: Behavioral Health
  
  
• Review for Importance: 1a. Impact: H-18; M-1; L-0; I-0; 1b. Performance Gap: H-12; M-7; L-0; I-0; 1c. Evidence: Y-17; N-0; I-2 Rationale: • The Steering Committee initially reviewed and rated the Importance criteria for this measure on April 18, 2012, during the first phase of this project; accordingly, Importance to Measure and Report was not discussed during the phase two meeting. Instead, the votes from Phase 1 were carried over, and appear above.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-2; M-16; L-3; I-0; 2b. Validity: H-2; M-17; L-2; I-0 Rationale: • The Steering Committee agreed the measure met the criteria. Reliability testing of the measure involved the re-abstraction of 96 medical records at five hospitals and the overall agreement rate was 75 percent. Following the re-abstraction, focus groups were conducted at each hospital and differences in abstraction were further discussed and highlighted as an opportunity for improvement on the measure. • On a previous review of the measure the Steering Committee had indicated concern regarding the reliability of the data element focused on screening patients for alcohol use; however, the developer noted that alterations to the measure had substantially improved the measure’s reliability. • The face validity of the measure was initially assessed through a public comment period and issues identified were addressed through measure revisions. An alpha test was then incorporated into the pilot test of the measure to reevaluate its validity. Finally, an eleven member Technical Advisory Panel was asked to review the measure specifications on a five point scale. The measure score varied from 4.12 -5 based on clarity of specifications, usefulness, interpretability, data accessibility and ease of collection and national use.
  
  
• Review for Feasibility: 4. Feasibility: H-4; M-17; L-0; I-0 (4a. Clinical data generated during care delivery; 4b. Electronic sources; 4c.Susceptibility to inaccuracies/ unintended consequences identified 4d. Data collection strategy can be implemented) Rationale: • The Steering Committee agreed the measure is feasible. Some data elements are available in electronic sources, and in the future the developer plans to further develop electronic specifications for the measure.
  
  
• Review for Usability: 3. Usability: H-4; M-17; L-0; I-0 (Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting/Accountability and 3b. Quality Improvement) Rationale: • The Steering Committee agreed the measure is usable. CMS has indicated that this measure will be required for reporting for inpatient psychiatric hospitals and psychiatric units in general hospitals starting in 2016.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures • This measure is related to the other measures in the SUB suite of measures in addition to the AMA-PCPI measure #2152 – Preventive Care and Screening: Unhealthy Diagnosis.
  
  
• Endorsement Public Comments: 6. Public and Member Comment Theme 1: Evidence Supporting The Joint Commission’s Suites of Tobacco (TOB) and Alcohol/Substance (SUB) Use Measures Description Commenters did not support the recommended endorsement of the following substance use measures and questioned whether the measures meet the evidence criterion relative to hospitalization and discharge: 1661 SUB-1 Alcohol Use Screening; 1663 SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention; 1664 SUB-3 Alcohol & Other Drug Use Disorder Treatment Provided or Offered at Discharge; SUB-3a Alcohol & Other Drug Use Disorder Treatment at Discharge (The Joint Commission). Committee Response: In the first phase of this project the Steering Committee reviewed and rated the three importance sub-criteria - impact, performance gap and evidence -for the substance use measures (1661 SUB-1, 1663 SUB-2 and 1664 SUB-3) and agreed that sufficient evidence was presented to support the measures. The Committee noted that the majority of the evidence, generally, is related to the outpatient setting. However, following substantial discussion, committee members agreed that certain evidence could be generalizable from the primary care setting to the inpatient setting, and that sufficient evidence was presented related to the inpatient setting based on the USPSTF and Cochrane review evidence to support the measures. Theme 2: Appropriateness of Tobacco (TOB) and Alcohol/Substance (SUB) Use Measures in the Inpatient Psychiatric Setting Description: 14 commenters did not support the recommended endorsement of the tobacco and alcohol/substance use suites of measures for use in the inpatient psychiatric setting, citing concerns about the appropriateness of brief interventions given the intensive treatment provided to patients in this setting, and the burden of collecting data and providing referrals at discharge. Developer Response: The Joint Commission specified this measure for use in all hospitals; therefore, since testing was conducted in psychiatric settings as well as general acute care hospitals, it is equally appropriate for use in IPFs. Committee Response: Agree with Developer. Theme 3: Reliability of SUB-1 Measure Description: One commenter did not support the recommended endorsement of the substance use measure 1661 SUB-1 Alcohol Use Screening, concerned by the measure’s reliability. In particular, the overall agreement rate for re-abstraction (75 percent) and the agreement rate for the data element ‘alcohol use status’ (64.7 percent) were noted. Committee Response: The Steering Committee reviewed the reliability of the measure 1661 SUB-1 based on additional testing presented by the Joint Commission. The additional testing gauged the sensitivity and specificity of the measure and the Committee noted improvements from previous reliability testing presented. NQF’s measure evaluation criteria requires reliability testing to demonstrate that either the measure data elements are repeatable, producing the same results a high proportion of the time when assessed in the same population in the same time period, and/or that the overall measure score is precise. The Committee noted that the overall measure agreement rate of 75 percent between the originally abstracted data and the re-abstracted data is at the threshold of an acceptable agreement rate, and ultimately determined it was sufficient to meet the criterion. The Committee also noted that further improvement is expected over time as the measure is more widely adopted.
  
  
• Endorsement Committee Recommendation: Steering Committee Recommendation for Endorsement: Y-19; N-2 • The Steering Committee recommended that the developer expand the measure population to include adolescents (aged13 and older) to make the measure more consistent with Meaningful Use and to incorporate an age group that also struggles with substance use disorders. The developer noted that they would review the evidence for extending the age range of the measure in the future.
  
  

Measure Specifications

• NQF Number (if applicable): 3090
  
  
• Description: Appropriate documentation of a malnutrition diagnosis for patients age 65 and older admitted to inpatient care who are found to be malnourished based on a nutrition assessment.
  
  
• Numerator: Patients with a documented diagnosis of malnutrition.
  
  
• Denominator: Patients age 65 years and older admitted to inpatient care who have a completed nutrition assessment indicative of malnutrition documented in their medical record.
  
  
• Exclusions: Patients with length of stay < 24 hours; Patients who are discharged to palliative care; Patients who are discharged to hospice; Patients who left against medical advice
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record, Record review
  
  
• Measure Type: Process
  
  
• Steward: The Academy of Nutrition and Dietetics
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is currently under review in NQF’s Health and Well-Being 2015-2017 project. The Standing Committee agreed that the evidence provided to support the measure was not sufficient. The measure did not pass the Evidence criterion and was not recommended for NQF endorsement.
  • Impact on quality of care for patients:This measure encourages documentation of a malnutrition diagnosis for patients = 65 years who have a completed nutrition assessment in their medical record.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The NQF Health and Well-Being Standing Committee recently reviewed the measure and agreed the evidence does not support that documentation of a malnutrition diagnosis is linked to improved patient outcomes. The measure failed the Evidence Criterion and was not recommended for endorsement.
  
  
• Does the measure address a quality challenge? Yes. Based on a national survey of hospital-based professionals in the United States focused on nutrition screening and assessment practices, out of 1,777 unique respondents, only 36.7% reported completing nutrition screening at admission, and 50.8% reported doing so within 24 hours. Only 69% reported documenting the findings in the medical record.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? No. Due to the lack of evidence supporting this process and linking it to improved patient outcomes, the value to patients/consumers does not outweigh any burden of implementation.
  
  
• Can the measure can be feasibly reported? Yes. This measure is a hybrid measure consisting of both electronically-derived data elements consisting of discrete and structured data as well as unstructured data also available in the electronic health record (EHR). Some Standing Committee members noted that some of the data elements are not consistently captured in EHRs and the criteria are not regularly spelled out as a discrete value.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and tested at the facility level in the hospital/acute care setting. Per NQF criteria, Scientific Acceptability was “Low” because the specifications are not consistent with the evidence.
  
  
• Measure development status: Field Testing; Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No . This is a new measure and has not been implemented.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The diagnosis of malnutrition via the completion of a nutrition assessment in patients at-risk of malnutrition can assist clinicians in identifying the appropriate interventions addressing patients’ malnourished state (White, 2011; Mueller, 2011; Kruizenga, 2005). Current estimates of the prevalence of adult malnutrition range from 15%-60% depending on the patient population and criteria used to identify its occurrence (Mueller, 2011). While this reflects a large portion of the population, only around 3 percent of patients are diagnosed with malnutrition; in turn, it is estimated that 4-19 million cases are left undiagnosed and untreated (White, 2012). An analysis of nationally representative, cross-sectional data indicate that hospitalized patients diagnosed with malnutrition tend to be older and sicker and also incur increased healthcare costs compared to non-malnourished patients (Corkins, 2014). A diagnosis of malnutrition has been associated with increased length-of-stay, readmissions, and risk of mortality in the hospital (Lew, 2016). An analysis of the 2010 HealthCare Cost and Utilization Project (HCUP), which provides a broad and nationally-representative dataset describing U.S. hospital discharges, reported that mortality was more than 5 times as common among patients with a malnutrition diagnosis (Corkins, 2014). Furthermore, malnutrition in hospitalized patients is also associated with higher post-operative complications such as infections and pressure ulcers (Fry, 2010; Banks, 2010). Early identification and subsequent intervention in particular can have a positive impact on those same patient outcomes (Somanchi, 2011). Additionally, documentation of malnutrition diagnoses has been associated with significant healthcare cost savings per hospital day per patient (Amaral, 2007). Lew CC, Yandell R, Fraser RJ, Chua AP, Chong MF, Miller M. Association Between Malnutrition and Clinical Outcomes in the Intensive Care Unit: A Systematic Review. JPEN J Parenter Enteral Nutr. 2016. Corkins MR, Guenter P, Dimaria-ghalili RA, et al. Malnutrition diagnoses in hospitalized patients: United States, 2010. JPEN J Parenter Enteral Nutr. 2014;38(2):186-95. White JV, et al. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN. 2012;36(3):275–283. Mueller C, Compher C & Druyan ME and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical Guidelines: Nutrition Screening, Assessment, and Intervention in Adults. J Parenter Enteral Nutr. 2011;35: 16-24. Somanchi et al., The Facilitated Early Enteral and Dietary Management Effectiveness Trial in Hospitalized Patients with Malnutrition. JPEN J Parenteral Enteral Nutr 2011 35:209. Banks M, Bauer J, Graves N, Ash S. Malnutrition and pressure ulcer risk in adults in Australian health care facilities. Nutrition. 2010;26(9):896-901. Fry DE, Pine M, Jones BL, Meimban RJ. Patient characteristics and the occurrence of never events. Arch Surg. 2010;145(2):148-51. Amaral TF, Matos LC, Tavares MM, Subtil A, Martins R, Nazaré M, et al. The economic impact of disease-related malnutrition at hospital admission. Clin Nutr. 2007 Dec;26(6):778–84. Kruizenga HM et al., Effectiveness and cost-effectiveness of early screening and treatment of malnourished patients. AM J Clin Nutrition. 2005 Nov 82(5): 1082-9.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The following questions (or a subset of questions) would replace the current Pain Management measure in the HCAHPS Survey with a new measure(s). The following items were tested in early 2016. CMS is currently analyzing the results, as well as discussing these potential new pain management items with focus groups and hospital staff. Multi-item measure (composite): HP1: “During this hospital stay, did you have any pain?” HP2: “During this hospital stay, how often did hospital staff talk with you about how much pain you had?” HP3: “During this hospital stay, how often did hospital staff talk with you about how to treat your pain?” HP4: “During this hospital stay, did you get medicine for pain?” HP5: “Before giving you pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Numerator: HCAHPS Survey measures are calculated using top-box scoring. The top-box refers to the percentage of patients who choose the most positive response option. For questions HP2 and HP3 in this measure, the top-box numerator is number of respondents who answer “Always.” For question HP5, the top-box numerator is number of respondents who answer “Yes.” Questions HP1 and HP4 are screener items that serve to direct respondents to subsequent questions, if applicable. HP1: “During this hospital stay, did you have any pain?” HP2: “During this hospital stay, how often did hospital staff talk with you about how much pain you had?” HP3: “During this hospital stay, how often did hospital staff talk with you about how to treat your pain?” HP4: “During this hospital stay, did you get medicine for pain?” HP5: “Before giving you pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Denominator: The top box denominator is the number of respondents who answer at least one of the questions in this multi-item measure, that is, questions HP2, HP3 and HP5.
  
  
• Exclusions: Patients who respond “No” to question HP1 are excluded from questions HP2 and HP3. Patients who respond “No” to question HP4 are excluded from question HP5. In addition, the following types of patients are excluded from the HCAHPS Survey: Patients younger than 18 years old at time of admission; Patients who did not have at least one overnight station in the hospital; Patients who were not admitted in the medical, surgical or maternity service lines; Patients who were not alive at time of discharge; “No-Publicity” patients – Patients who request that they not be contacted; Court/Law enforcement patients (i.e., prisoners); Patients with a foreign home address; Patients discharged to hospice care; Patients who are excluded because of state regulations; Patients discharged to nursing homes and skilled nursing facilities. For details, see HCAHPS Quality Assurance Guidelines, V11.0 at http://www.hcahpsonline.org/qaguidelines.aspx
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Survey
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is undergoing field testing and is intended to replace the Pain Management composite measure in the HCAHPS Survey in response to concerns expressed by physicians, hospitals and others about the current Pain Management items in the survey. The testing results should demonstrate that the measure is reliable and valid in IQR. In addition, the survey should be submitted to NQF for review and endorsement of this new composite measure that focuses on communication about pain during the hospital stay.
  • Impact on quality of care for patients:This measure can improve how hospital staff communicate with patients about pain during their hospital stay.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure promotes effective communication and coordination of care and ensures that each person and family is engaged as partners in their care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The scientific evidence-base and rationale for how this outcome measure is influenced by healthcare processes or structures was not provided. CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff in response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey.
  
  
• Does the measure address a quality challenge? Yes. The average top-box score for hospitals on the current Pain Management measure is 71.0%, indicating there is room for improvement.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The proposed measure will replace the Pain Management composite measure currently in the HCAHPS Survey for IQR and VBP. The proposed measure focuses on communication about pain during the patient’s hospital stay, rather than how well pain was controlled.
  
  
• Can the measure can be feasibly reported? Yes. CMS is testing this measure on Q1’16 hospital discharges from 50 hospitals. Additionally, the previous measure has been reported since 2006.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is currently undergoing field testing on patients discharged from 50 hospitals Q1’16.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. CMS states they are not aware of any unintended consequences from the use of this measure. The measure is currently undergoing field testing and is not yet in use.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey, CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff. These items would replace the 3 Pain Management items on the HCAHPS Survey, which comprise the current Pain Management measure. CMS is currently evaluating data on the items as well as focus groups and interviews about the new pain items. A measure based on these items would be similar to the Pain Management composite measure currently used, which is based on the current HCAHPS Survey items The new measure, Communication about Pain During the Hospital Stay, focusses on communication about pain during the patient’s hospital stay, rather than on how well pain was controlled Different from the other measures in the HCAHPS Survey, this new measure uniquely focusses on communication about pain during the patient’s hospital stay The Communication about Pain During the Hospital Stay measure would replace the current Pain Management measure in the HCAHPS Survey, which is part of the IQR Program.  CMS is testing this new measure in a large-scale HCAHPS mode experiment.  CMS is currently collecting data for the Communication about Pain During the Hospital Stay measure from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment, January-March 2016.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The following questions (or a subset of questions) would replace the current Pain Management measure in the HCAHPS Survey with a new measure(s). The following items were tested in early 2016. CMS is currently analyzing the results, as well as discussing these potential new pain management items with focus groups and hospital staff. Multi-item measure (composite): DP1: “Before you left the hospital, did someone talk with you about how to treat pain after you got home?” DP2: “Before you left the hospital, did hospital staff give you a prescription for medicine to treat pain?” DP3: “Before giving you the prescription for pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Numerator: HCAHPS Survey measures are calculated using top-box scoring. The top-box refers to the percentage of patients who choose the most positive response option. For questions DP1 and DP3, the top-box numerator is number of respondents who answer “Yes.” Question DP2 is a screener item that serves to direct respondents to question DP3, if applicable. DP1: “Before you left the hospital, did someone talk with you about how to treat pain after you got home?” DP2: “Before you left the hospital, did hospital staff give you a prescription for medicine to treat pain?” DP3: “Before giving you the prescription for pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Denominator: The top box denominator is the number of respondents who answer at least one of the questions in this multi-item measure, that is, questions DP1 and DP3.
  
  
• Exclusions: Patients who respond “No” to question DP2 are excluded from question DP3. In addition, the following types of patients are excluded from the HCAHPS Survey: Patients younger than 18 years old at time of admission; Patients who did not have at least one overnight station in the hospital; Patients who were not admitted in the medical, surgical or maternity service lines; Patients who were not alive at time of discharge; “No-Publicity” patients – Patients who request that they not be contacted; Court/Law enforcement patients (i.e., prisoners); Patients with a foreign home address; Patients discharged to hospice care; Patients who are excluded because of state regulations; Patients discharged to nursing homes and skilled nursing facilities. For details, see HCAHPS Quality Assurance Guidelines, V11.0 at http://www.hcahpsonline.org/qaguidelines.aspx
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Survey
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is undergoing field testing and is intended to replace the Pain Management composite measure in the HCAHPS Survey in response to concerns expressed by physicians, hospitals and others about the current Pain Management items in the survey. The testing results should demonstrate that the measure is reliable and valid in IQR. In addition, the survey should be submitted to NQF for review and endorsement of this new composite measure addressing communication about treating pain post-discharge.
  • Impact on quality of care for patients:This measure can improve how hospital staff communicate with patients about pain they may experience after they are discharged from the hospital.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure promotes effective communication and coordination of care and ensures that each person and family is engaged as partners in their care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The scientific evidence-base and rationale for how this outcome measure is influenced by healthcare processes or structures was not provided. CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff in response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey.
  
  
• Does the measure address a quality challenge? Yes. The average top-box score for hospitals on the current Pain Management measure is 71.0%, indicating there is room for improvement.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The proposed measure will replace the Pain Management composite measure currently in the HCAHPS Survey for IQR and VBP. The proposed measure focuses on communication about pain the patient may experience after discharge from the hospital.
  
  
• Can the measure can be feasibly reported? Yes. CMS is testing this measure on Q1’16 hospital discharges from 50 hospitals. Additionally, the previous measure has been reported since 2006.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is currently undergoing field testing on patients discharged from 50 hospitals Q1’16.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is currently undergoing field testing and is not yet in use. There may be potential unintended consequences regarding question HP4, which could lead to increased prescription of pain medications “During this hospital stay, did you get medicine for pain?”.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey, CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff. These items would replace the 3 Pain Management items on the HCAHPS Survey, which comprise the current Pain Management measure. CMS is currently evaluating data on the items as well as focus groups and interviews about the news pain items. A measure based on these items would be similar to the Pain Management composite measure currently used, which is based on the current HCAHPS Survey items The new measure, Communication about Treating Pain Post-Discharge, focusses on communication about pain that the patient may experience after discharge from the hospital, rather than on how well pain was controlled Different from the other measures in the HCAHPS Survey, this new measure uniquely focusses on communication about pain that the patient may experience after discharge from the hospital The Communication about Treating Pain Post-Discharge measure would replace the current Pain Management measure in the HCAHPS Survey, which is part of the IQR Program.  CMS is testing this new measure in a large-scale HCAHPS mode experiment.  CMS is currently collecting data for the Communication about Treating Pain Post-Discharge measure from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment, January-March 2016.

Measure Specifications

• NQF Number (if applicable): 3087
  
  
• Description: Completion of a malnutrition screening using a validated screening tool to determine if a patient is at-risk for malnutrition, within 24 hours of admission to the hospital.
  
  
• Numerator: Patients in the denominator who have a completed malnutrition screening documented in the medical record within 24 hours of admission to the hospital. For the purposes of this measure, it is recommended that a malnutrition screening be performed using a validated screening tool which may include but is not limited to one of the following validated tools: Malnutrition Screening Tool (MST) (Ferguson, 1999), Nutrition Risk Classification (NRC) (Kovacevich, 1997), Nutritional Risk Index (NRI) (Bouillanne, 2005), Nutritional Risk Screening 2002 (NRS-2002) (Kondrup, 2003), Short Nutrition Assessment Questionnaire (SNAQ) (Kruizenga, 2005).
  
  
• Denominator: All patients age 18 years and older at time of admission who are admitted to an inpatient hospital.
  
  
• Exclusions: Patients with length of stay < 24 hours
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: The Academy of Nutrition and Dietetics
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is currently under review in NQF’s Health and Well-Being 2015-2017 project. The Standing Committee did not reach consensus on the Evidence Criterion during the in-person meeting in September. The measure must pass the evidence criterion and be recommended for endorsement.
  • Impact on quality of care for patients:This measure encourages documentation of a malnutrition screening within 24 hours for patients >18 years admitted into the acute inpatient care setting, which is the first step in nutrition care.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The NQF Health and Well-Being Standing Committee that recently reviewed the measure were concerned that the screening, assessment, diagnosis to treatment link was not substantiated by the evidence. In addition, the guideline cited to support this measure is graded E (Nonrandomized cohort with historical controls and case series, uncontrolled studies, and expert opinion). The Standing Committee did not reach concensus on the evidence criterion. The Standing Committee will revote on the evidence criterion on December 6, 2016 during the post-comment call.
  
  
• Does the measure address a quality challenge? Yes. Based on a national survey of hospital-based professionals in the United States focused on nutrition screening and assessment practices, out of 1,777 unique respondents, only 36.7% reported completing nutrition screening at admission, and 50.8% reported doing so within 24 hours. Only 69% reported documenting the findings in the medical record.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is not duplicative of an existing measure in IQR.
  
  
• Can the measure can be feasibly reported? Yes. The Standing Committee did not raise any concerns with the feasibility of this eCQM. Feasibility was assessed in 3 different EHR systems at 2 sites.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and tested at the facility level in the hospital/acute care setting. The measure meets the NQF Scientific Acceptability criterion.
  
  
• Measure development status: Field Testing; Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a new measure and has not been implemented. The NQF Standing Committee raised concerns with implementing this measure without evidence demonstrating that screening leads to quality improvement.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The peer reviewed evidence supporting this measure is centered on the concept that malnutrition screening is an important first step in identifying malnutrition risk. Identifying patients at-risk of malnutrition allows clinicians to then complete a nutrition assessment that can confirm malnutrition and initiate a care plan recommending appropriate interventions. The evidence supports rapid recognition and treatment (as well as prevention) of malnutrition which is associated with lower costs of care, lower readmission rates, length of stay and hospital-acquired conditions. Malnutrition risk identified in patients through a malnutrition screening was able to predict certain patient outcomes including length of stay, mortality, and post-operative complications. (Mueller C, Compher C & Druyan ME and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical Guidelines: Nutrition Screening, Assessment, and Intervention in Adults. J Parenter Enteral Nutr. 2011;35: 16-24.) Retrospective analysis of administrative data for years 2013 and 2014 from a university hospital, in which being nutritionally 'at-risk' was defined as a Nutritional risk screening-2002 score = 3, reinforces the association between risk of malnutrition and rates of mortality, as well as cost of care. After multivariate adjustment, 'at-risk' patients had a 3.7-fold (95% confidence interval: 1.91; 7.03) higher in-hospital mortality and higher costs (excess 5642.25 ± 1479.80 CHF in 2013 and 5529.52 ± 847.02 CHF in 2014, p < 0.001) than 'not at-risk' patients, while no difference was found for LOS. It also indicates that being nutritionally 'at-risk' affects three in every five patients. (Khalatbari-soltani S, Marques-vidal P. Impact of nutritional risk screening in hospitalized patients on management, outcome and costs: A retrospective study. Clin Nutr. 2016; pii: S0261-5614(16)00069-8.) 543 patients were recruited from consecutive admissions at 2 hyperacute stroke units in London and were screened for risk of malnutrition (low, medium, and high) according to MUST. Six-month outcomes were obtained for each patient through a national database. Results of the study among stroke patients showed a highly significant increase in mortality with increasing risk of malnutrition (P?

Measure Specifications

• NQF Number (if applicable): 3088
  
  
• Description: Patients age 65 years and older identified as at-risk for malnutrition based on a malnutrition screening who have a nutrition assessment documented in the medical record within 24 hours of the most recent malnutrition screening.
  
  
• Numerator: Patients in the denominator who have a nutrition assessment documented in the medical record within 24 hours of the most recent malnutrition screening.
  
  
• Denominator: Patients age 65 years and older admitted to the hospital who were identified as at-risk for malnutrition upon completing a malnutrition screening.
  
  
• Exclusions: Patients with a length of stay < 24 hours
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: The Academy of Nutrition and Dietetics
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is currently under review in NQF’s Health and Well-Being 2015-2017 project. The Standing Committee did not reach consensus on the Evidence Criterion during the in-person meeting in September. The measure must pass the evidence criterion and be recommended for endorsement.
  • Impact on quality of care for patients:This measure encourages documentation of a malnutrition assessment within 24 hours of the most recent malnutrition screening for patients = 65 years so that a dietitian can subsequently recommend a nutrition care plan that includes appropriate interventions to address the patient's malnutrition.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The NQF Health and Well-Being Standing Committee that recently reviewed the measure were concerned that the screening, assessment, diagnosis to treatment link was not substantiated by the evidence. The guideline cited to support this measure is graded E (Nonrandomized cohort with historical controls and case series, uncontrolled studies, and expert opinion). Committee members debated whether the number of studies in the observation and randomized trials mentioned in the guideline were sufficient, and able to discern the risk of bias. The Standing Committee did not reach concensus on the evidence criterion. The Standing Committee will revote on the evidence criterion on December 6, 2016 during the post-comment call.
  
  
• Does the measure address a quality challenge? Yes. Based on a national survey of hospital-based professionals in the United States focused on nutrition screening and assessment practices, out of 1,777 unique respondents, only 36.7% reported completing nutrition screening at admission, and 50.8% reported doing so within 24 hours. Only 69% reported documenting the findings in the medical record.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is not duplicative of an existing measure in IQR.
  
  
• Can the measure can be feasibly reported? Yes. Feasibility was assessed in 3 different EHR systems at 2 sites.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and tested at the facility level in the hospital/acute care setting. The measure meets the NQF Scientific Acceptability criterion.
  
  
• Measure development status: Field Testing; Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a new measure and has not been implemented.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The peer reviewed evidence supporting this measure supports the assessment of patients at-risk of malnutrition via the completion of a nutrition assessment that can confirm malnutrition and initiate a care plan recommending appropriate interventions. The evidence supports rapid recognition and treatment (as well as prevention) of malnutrition which is associated with lower costs of care, lower readmission rates, length of stay and hospital-acquired conditions. Nutrition assessments conducted for at-risk patients identified by malnutrition screening using a validated screening tool was associated with key patient outcomes including less weight loss, reduced length of stay, improved muscle function, better nutritional intake, and fewer readmissions. (Mueller C, Compher C & Druyan ME and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical Guidelines: Nutrition Screening, Assessment, and Intervention in Adults. J Parenter Enteral Nutr. 2011;35: 16-24.) A systematic review found that patient outcomes associated with malnutrition that was first identified by the use of a nutrition assessment was independently associated with poorer patient outcomes. Malnutrition was identified using two different assessment tools, the Subjective Global Assessment (SGA), this patient cohort was associated with higher hospital mortality, higher incidence of infection, and an increased risk of readmission. Using the Mini Nutritional Assessment (MNA), those identified as malnourished also experienced increased risk of postoperative complications. Additionally, fewer malnourished patients are discharged to their own homes compared to well-nourished patients. (Lew CC, Yandell R, Fraser RJ, Chua AP, Chong MF, Miller M. Association Between Malnutrition and Clinical Outcomes in the Intensive Care Unit: A Systematic Review. JPEN. Journal of parenteral and enteral nutrition. 2016.) A prospective, matched case control study supports statistically significant associations of malnutrition (assessed using the Subjective Global Assessment) with increased lengths of stay, mortality, and hospitalization costs. Malnourished patients were also more likely to be readmitted within 15 days. (Lim SL, Ong KC, Chan YH, Loke WC, Ferguson M, Daniels L. Malnutrition and its impact on cost of hospitalization, length of stay, readmission and 3-year mortality. Clin Nutr. 2012;31(3):345-50.)

Measure Specifications

• NQF Number (if applicable): 576
  
  
• Description: The percentage of discharges for patients 6 years of age and older who were hospitalized for treatment of selected mental illness diagnoses and who had an outpatient visit, an intensive outpatient encounter or partial hospitalization with a mental health practitioner. Two rates are reported: - The percentage of discharges for which the patient received follow-up within 30 days of discharge - The percentage of discharges for which the patient received follow-up within 7 days of discharge.
  
  
• Numerator: 30-Day Follow-Up: An outpatient visit, intensive outpatient visit or partial hospitalization with a mental health practitioner within 30 days after discharge. Include outpatient visits, intensive outpatient visits or partial hospitalizations that occur on the date of discharge. 7-Day Follow-Up: An outpatient visit, intensive outpatient visit or partial hospitalization with a mental health practitioner within 7 days after discharge. Include outpatient visits, intensive outpatient visits or partial hospitalizations that occur on the date of discharge.
  
  
• Denominator: Patients 6 years and older as of the date of discharge who were discharged from an acute inpatient setting (including acute care psychiatric facilities) with a principal diagnosis of mental illness during the first 11 months of the measurement year (e.g., January 1 to December 1).
  
  
• Exclusions: Exclude both the initial discharge and the readmission/direct transfer discharge if the readmission/direct transfer discharge occurs after the first 11 months of the measurement year (e.g., after December 1). Exclude discharges followed by readmission or direct transfer to a nonacute facility within the 30-day follow-up period, regardless of principal diagnosis for the readmission. Exclude discharges followed by readmission or direct transfer to an acute facility within the 30-day follow-up period if the principal diagnosis was for non-mental health (any principal diagnosis code other than those included in the Mental Health Diagnosis Value Set). These discharges are excluded from the measure because rehospitalization or transfer may prevent an outpatient follow-up visit from taking place.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare; enter relevant parts in the field below)
  
  
• Measure Type: Process
  
  
• Steward: National Committee for Quality Assurance
  
  
• Endorsement Status: Endorsed
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure, NQF #0576, is specified and tested at the health plan level; therefore, performance on the measure cannot be attributed to the facility as currently specified. Additionally, problems encountered with the initial measure results in the IPFQR program should be resolved prior to implementing the measure in additional programs.
  • Impact on quality of care for patients:This measure can help bridge the gap between the inpatient setting and outpatient treatment services for individuals with serious mental illness.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure promotes effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Individuals with serious mental Illnesses who have been discharged from inpatient settings and remain unconnected to outpatient treatment services are at a higher risk of recidivism. After discharge, psychiatric patients are at high risk of adverse outcomes, including psychiatric re-hospitalization, first-episode or recurrent homelessness, violence against others, and suicide. Emerging evidence suggests that brief, low-intensity case management interventions are effective in bridging the gap between inpatient and outpatient treatment.(Dixon L, Goldberg R, Iannone V, et al. Use of a critical time intervention to promote continuity of care after psychiatric inpatient hospitalization for severe mental illness. Psychiatr Serv. 2009;60:451–458).
  
  
• Does the measure address a quality challenge? Yes. From 2009 to 2011, approximately 40-60% of Medicare and Medicaid patients who were hospitalized for treatment of a mental illness received outpatient follow-up within 7 days and 30 days.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is currently in the Inpatient Psychiatric Facility Quality Reporting Program (IPFQR).
  
  
• Can the measure can be feasibly reported? No. For fiscal year 2016, problems encountered with the coding and calculation of the initial measure results in the Inpatient Psychiatric Facility Quality Reporting Program (IPFQR) have prevented them from being reported on Hospital Compare for this year. These problems are being corrected and other modifications to the calculation of the measure are being considered to improve its usefulness for the program. The measure results will be suppressed by CMS.Source: http://www.qualityreportingcenter.com/wp-content/uploads/2016/01/IPF_PublicReportingMeasureResultsReview_1.7.2016_FINAL50811.pdf
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is specified, reliable, valid and NQF-endorsed at the health plan level not at the facility level as proposed.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. CMS has encountered problems calculating the measure in the Inpatient Psychiatric Facility Quality Reporting Program (IPFQR) and the measure results are not available on Hospital Compare. However, no evidence found of unreasonable implementation issues in various Medicaid programs.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
This measure assesses whether health plan members who were hospitalized for a mental illness received timely follow-up visits. Studies suggest that patients who start treatment soon after diagnosis are less likely to have negative health and social outcomes. A plan’s ability to improve its seven- and 30-day follow-up rates may result in better overall health outcomes. As studies have shown, efforts to facilitate treatment following a hospital discharge also lead to less attrition in the initial period of treatment. Thus, this time period may be an important opportunity for health plans to implement strategies aimed at establishing strong relationships with mental health providers and facilitate long-term engagement in treatment. Low-intensity interventions that can be applied widely are typically implemented at periods of high risk for treatment dropout, such as following an emergency room or hospital discharge or the time of entry into outpatient treatment (Kreyenbuhl 2009). Emerging evidence suggests that brief, low-intensity case management interventions are effective in bridging the gap between inpatient and outpatient treatment (Dixon 2009). For example, Boyer et al evaluated strategies aimed at increasing attendance at outpatient appointments following hospital discharge. They found that the most common factor in a patient’s medical history that was linked to a patient having a follow-up visit was a discussion about the discharge plan between the inpatient staff and outpatient clinicians. Other strategies they found that increased attendance at appointments included having the patient meet with outpatient staff and visit the outpatient program prior to discharge (Boyer 2000). Although rates vary across studies, reviews of the literature suggest that up to one-third of individuals with serious mental illnesses who have had some contact with the mental health service system disengage from care. Younger age, male gender, ethnic minority background, and low social functioning have been consistently associated with disengagement from mental health treatment. Individuals with co-occurring psychiatric and substance use disorders, as well as those with early onset psychosis, are at particularly high risk of treatment dropout. Studies suggest that engagement strategies that specifically target these high-risk groups, as well as high-risk periods, including following an emergency room or hospital admission and the initial period of treatment, can improve outcomes (Kreyenbuhl 2009).

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Behavioral Health
  
  
• Review for Importance: 1a. Impact: H-6; M-7; L-1; I-0; 1b. Performance Gap: H-10; M-4; L-0; I-0; 1c. Evidence: Y-13, N-1, I-0 Rationale:• The Committee believes this measure addresses a high impact area, as individuals with schizophrenia have highcost healthcare expenditures and typically lack follow-up post hospitalization.• The measure has been reported in HEDIS for 10 years, the average performance rate at seven days is 45 to 50percent. Over time, the rate has improved but the Medicaid rates remain very low. At 30 days the rate is closer to 70 percent.• The Committee agreed the evidence presented demonstrates that outcomes are poorer when follow up does not occur.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-8; M-6; L-0; I-0; 2b. Validity: H-5; M-8; L-0; I-0Rationale: The Steering Committee agreed reliability and validity of the measure was demonstrated.The developer used a beta-binomial approach to estimate reliability using a 0.0 to 1.0 reliability score, where a minimum reliability score of 0.7 is used to indicate sufficient signal strength to discriminate performance between accountable entities. The results for the percentage of members who received follow-up within 30 days of discharge were 0.949 or better for Commercial, Medicaid and Medicare populations, and the results for members who received follow-up within 7 days of discharge were 0.95or better for the three populations. The measure was written, field-tested, and presented to the CPM and incorporated into HEDIS in 1994
  
  
• Review for Feasibility: 4. Feasibility: H-7; M-6; L-0; I-1 (4a. Clinical data generated during care process; 4b. Electronic data; 4c. Susceptibility to inaccuracies/ unintended consequences identified 4d. Data collection strategy can be implemented) Rationale: • There may be difficulty following up with individuals due to socioeconomic issues such as homelessness or living in group housing, which is difficult to capture in administrative data. • The Committee noted poverty, crime and living in unsafe neighborhoods all play a role in the difficulty to ensure adequate follow up with these patients.
  
  
• Review for Usability: 3. Usability: H-3; M-10; L-0; I-1 (Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting and 3b. Quality Improvement) Rationale: • The measure is easily understood and currently in use for public reporting, regulatory accreditation programs, quality improvement, benchmarking, external benchmarking over multiple organizations and then internal quality improvement within a specific organization. • The Committee noted that if the measure received continued endorsement, the developer should review its usefulness for additional populations.
  
  
• Review for Related and Competing Measures: N/A
  
  
• Endorsement Public Comments: No comments
  
  
• Endorsement Committee Recommendation: Steering Committee Recommendation for Endorsement: Y-13; N-1 Rationale: • There are few measures of quality related to follow up and transition of care over time. This measure has been in use over 10 years and addresses a population for which follow-up is critical. Recommendation: • The Steering Committee discussed the possibility of including #1937 Follow-Up After Hospitalization for Schizophrenia (7- and 30-day) (NCQA) as strata for the schizophrenic population within this measure. o NCQA agreed to incorporate the new measure #1937 as a subset or target population within the more broadly defined measure #0576 following the member voting period and CSAC/Board reviews. • Committee members suggested highly vulnerable groups who receive disparate care, including the fragile elderly, should be included in the measure, and extending the target age beyond 64 should be considered.
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This measure estimates hospital-level, risk-standardized mortality rate (RSMR) for Medicare fee-for-service (FFS) patients who are between the ages of 65 and 95. Death is defined as death from any cause within 30 days after the index admission date.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure outcome. The outcome for this measure is 30-day all-cause mortality. Mortality is defined as death for any reason within 30 days after the index admission date, including in-hospital deaths.
  
  
• Denominator: The cohort includes inpatient admissions for patients aged 65 years and older, with a complete claims history for the 12 months prior to admission. If a patient has more than one admission in a year, one hospitalization is randomly selected for inclusion in the measure.
  
  
• Exclusions: The measure excludes admissions for patients: - With inconsistent or unknown vital status or other unreliable data - Aged over 95 years old - Discharged against medical advice - Enrolled in the Medicare hospice program at any time in the 12 months prior to the index admission, including the first day of the index admission - With a principal diagnosis of cancer and enrolled in hospice during their index admission - With any diagnosis of metastatic cancer - Admissions for crush injury (CCS 234), burn (CCS 240), intracranial injury (CCS 233) or spinal cord injury (CCS 227) - Admissions for rehabilitation CCS 254 - Admissions for psychiatric diagnosis CCS 650, 651, 652, 654, 655, 656, 657, 658, 659, 662 & 670 - With a principal discharge diagnosis of anoxic brain damage (ICD-9 3481), persistent vegetative state (ICD-9 78003), prion diseases Creutzfeldt-Jakob disease (ICD-9 04619), Cheyne-Stokes respiration (ICD-9 78604), brain death (ICD-9 34882), respiratory arrest (ICD-9 7991), or cardiac arrest (ICD-9 4275) without a secondary diagnosis if acute myocardial infarction.
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims (non-Medicare)
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Fully Developed
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Hospital-wide mortality has been the focus of a number of previous quality reporting initiatives in the U.S. and other countries. Prior efforts have met with some success and a number of challenges. Through our environmental scan and literature review, we identified multiple hospital-wide mortality measures reported at the state-level, and several at the health-system level. There is no HWM measure reported at the national-level in the United States. The vast majority of patients admitted to the hospital have survival as a primary goal, and this outcome is already the focus of existing CMS condition- and procedure-specific mortality quality measures. We know from these existing measures of risk-standardized mortality rates that there is variation across hospitals in risk-adjusted mortality, supporting variation in the quality of care received at these hospitals1. Furthermore, we also know that these existing mortality measures provide specificity for targeted quality improvement work and may have contributed to national declines in hospital mortality rates for measured conditions2. However, these measures do not allow broader statements about a hospital’s performance for those admitted, nor do they meaningfully capture performance for small-volume hospitals. By creating a hospital-wide mortality measure, we will be able to capture cross-cutting hospital-wide characteristics that may contribute to quality of care such as a culture of safety, good communication across teams, multidisciplinary care teams, coordination with community services and efforts, and effective care transitions. While avoiding mortality is a primary outcome for most patients, we do recognize that this is not true for all patients, and that there are also some patients for which the quality of care at a hospital may not impact the outcome. In order to create a measure that is meaningful and accurately reflects patient’s goals of care, we have worked with a broad range of stakeholders, including patients, family caregivers, and clinicians to best identify those admissions which should not be included in the measure, such as patients that have been enrolled in hospice before or on admission. While limitation of treatment orders (such as DNR, or comfort care only) are important for understanding patient wishes, for this measure we only have data from claims. The code for DNR is unreliable and not appropriately captured in claims3. In addition, there are no claims for other limitation of treatment orders. Because of this, our stakeholders have agreed that it should not be used in this measure. 1. Render ML, Kim HM, Deddens J, et al. Variation in outcomes in Veterans Affairs intensive care units with a computerized severity measure. Critical care medicine. May 2005;33(5):930-939. 2. Suter LG, Li SX, Grady JN, et al. National patterns of risk-standardized mortality and readmission after hospitalization for acute myocardial infarction, heart failure, and pneumonia: update on publicly reported outcomes measures based on the 2013 release. Journal of general internal medicine. Oct 2014;29(10):1333-1340. 3. Goldman LE, Chu PW, Osmond D, Bindman A. Accuracy of do not re-suscitate (DNR) in administrative data. Med Care Res Rev. 2013;70:98–112. doi: 10.1177/1077558712458455

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure estimates the hospital-level quality of informed consent documents for elective procedures for fee-for-service (FFS) Medicare patients. The outcome is defined as the quality of the informed consent document, as evaluated using an instrument developed for this purpose, the Abstraction Tool. A sample of hospitals’ informed consent documents are evaluated and hospital-level performance will be derived by aggregating these individual informed consent document quality scores. The measure is broadly applicable to a range of procedures, including elective cardiac, orthopedic, and urological procedures, that are performed in the hospital.
  
  
• Numerator: The outcome of this measure is the quality of informed consent documents. The measure evaluates the scores of informed consent documents on a scale from 0 to 20 using an instrument developed for this purpose, the Abstraction Tool. A score of 20 indicates that the document met all criteria on the Abstraction Tool.The measure aggregates the quality of a sample of informed consent documents for procedures at each hospital. The informed consent documents of patients undergoing electively performed hospital procedures are evaluated using an instrument (“Abstraction Tool”) developed for this purpose. Trained abstractors use the Abstraction Tool to score informed consent documents using standardized criteria for the following items:1) Is language describing "What is the procedure" (beyond the medical name) provided for the patient? (2 points) 1t) If provided, is it typed? (1 point)2) Is a description of how the procedure will be performed provided for the patient? (2 points) 2t) If provided, is it typed? (1 point) 3) Is the clinical rationale (condition-specific justification) for WHY the procedure will be performed provided? (2 points)4) Is any patient-oriented benefit provided (intended impact on patient's health, longevity, and/or quality of life)? (2 points)5) Is a quantitative probability provided for any procedure-specific risk? (2 points)6) Is a qualitative probability provided for any procedure-specific risk? (2 points)7) Is any alternative provided for the patient? (2 points)8) Is the date of patient signature at least one day before date of procedure if the patient did not opt out of signing at least one day in advance? (5 points)
  
  
• Denominator: The measure cohort includes procedures for patients aged 18 years or older. The cohort is a subset of elective, hospital-based procedures for Medicare fee-for-service (FFS) beneficiaries, for which informed consent is considered standard practice (see codes below and attached data dictionary code table) during the measurement period. Patients may be included in the cohort multiple times if they underwent multiple qualifying elective procedures during the measurement period. Each qualifying elective procedure performed in a Medicare FFS beneficiary in the hospital setting is considered a “case” in sampling. To be included in the measure cohort, patients must meet the following inclusion criteria: 1. Underwent an elective procedure (described below), as an inpatient during the measurement period. 2. Enrolled in Medicare FFS Part A at the time of the procedure The measure is specified for patients undergoing elective procedures for several reasons. Informed consent is standard practice for the procedures captured in this population. Additionally, this population will benefit from a measure aimed at optimizing communications about the procedure because elective procedures are generally considered ‘preference-sensitive’ (meaning there are reasonable alternatives to the procedure) and different patients may choose different options depending on their preferences, values, and goals.Though currently specified for inpatient procedures, the measure could be expanded to include outpatient hospital-based procedures. Additionally, this measure could be expanded to other care settings and payer groups. We have explicitly tested the measure for patients 18 years and older who underwent procedures in an inpatient or outpatient hospital setting. Qualifying elective procedures for the measure come from the 82 AHRQ Clinical Classification Software (CCS) procedure categories in 10 surgical sub-divisions. These sub-divisions were created during development of the Hospital-Wide Readmission Measure which identified and then classified each major surgical CCS procedure into one of 10 surgical sub-divisions based on surgical service-line; these groupings were reviewed by 3 physicians on our team as well as our TEP. Cardiothoracic (8 CC codes)Ear/Nose/Throat (6 CC codes)General Surgery (26 CC codes)Neurosurgery (2 CC codes)Obstetrics/Gynecology (7 CC codes)Ophthalmology (3 CC codes)Orthopedic (11 CC codes)Plastic Surgery (3 CC codes)Urology (8 CC codes)Vascular Surgery (8 CC codes)A procedure division to CC category crosswalk is attached in field S.2b. (Data Dictionary or Code Table). The 82 included CC codes meet all of the following criteria:1. Codes for procedures that are included in the Planned Readmission Algorithm as typically planned, or elective, procedures[1].2. Codes that are not for minor procedures for which informed consent may or may not require a signed document (such as minor procedures commonly performed at the bedside or by allied health professionals);3. Codes that are not for non-invasive radiographic diagnostic tests (for example, CT Scan with contrast) since informed consent standards may be different than standards for invasive procedures and surgeries; or4. Codes that are not for procedures that are conducted over several encounters (for example, dialysis, chemotherapy, radiation therapy since informed consent is likely only conducted prior to the first procedure.Note 1. The Planned Readmission Algorithm is a set of criteria for classifying readmissions as planned among the general Medicare population using Medicare administrative claims data. For this measure, the Planned Readmission Algorithm is used to identify admissions for procedures as planned or unplanned. It was also used in specifying procedures that are typically considered planned, by CC code, for the measure cohort inclusions criteria. The Planned Readmission Algorithm and associated code tables are attached in data field S.2b (Data Dictionary or Code Table). For more details on the Planned Readmission Algorithm, please see the report titled “Centers for Medicare and Medicaid Services. 2014 Measure Updates and Specifications Report Hospital-Wide All-Cause Unplanned Readmission – Version 3.0.” http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.Centers for Medicare and Medicaid Services. 2014 Measure Updates and Specifications Report Hospital-Wide All-Cause Unplanned Readmission – Version 3.0. http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html./Measure-Methodology.html.Centers for Medicare and Medicaid Services. 2014 Measure Updates and Specifications Report Hospital-Wide All-Cause Unplanned Readmission – Version 3.0. http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
  
  
• Exclusions: This measure excludes: 1. Unplanned admissions based on the medical diagnosis code or procedure code associated with the hospital visit, identified using the Planned Readmission Algorithm[1]. Rationale: Several procedures may be appropriate for inclusion if we can determine that they were performed on an elective basis. Procedures performed during admissions defined as “unplanned” are likely to be performed on a non-elective, potentially urgent or acute basis, and thus are excluded. 2. Cases with a health insurance claim (HIC) number ending in a letter other than “A” Rationale: HIC numbers ending in letters other than “A” indicate that the patient is not the primary beneficiary for the FFS Medicare plan. As such, it is difficult to match the claim information to an informed consent document in the medical record.3. Non-English informed consent documentsRationale: At the present time, we are not equipped to rate the quality of Informed consent documents in languages other than English. While some forms are in English on one side and Spanish on the other, we are not certain that the same information is communicated, especially since many forms contain hand-written information that has not been reviewed for quality of translation.4. Procedures performed during the same encounter as another already selected procedure. We will select the first procedure in the encounter, chronologically; if more than one procedure is performed on the same date, we will randomly select one. Rationale: Two procedures performed during the same encounter are commonly performed together, and thus may not have distinct informed consent documents. Additionally, subsequent procedures performed after the initial procedure but in the same encounter may not be elective.Note 1. The Planned Readmission Algorithm is a set of criteria for classifying readmissions as planned among the general Medicare population using Medicare administrative claims data. For this measure, the Planned Readmission Algorithm is used to identify admissions for procedures as planned or unplanned. It was also used in specifying procedures that are typically considered planned, by CC code, for the measure cohort inclusions criteria. The Planned Readmission Algorithm and associated code tables are attached in data field S.2b (Data Dictionary or Code Table). For more details on the Planned Readmission Algorithm, please see the report titled “Centers for Medicare and Medicaid Services. 2014 Measure Updates and Specifications Report Hospital-Wide All-Cause Unplanned Readmission – Version 3.0.” http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.Centers for Medicare and Medicaid Services. 2014 Measure Updates and Specifications Report Hospital-Wide All-Cause Unplanned Readmission – Version 3.0. http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HospitalQualityInits/Measure-Methodology.html.
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination, Best Practice of Healthy Living
  
  
• HHS Data Source: Administrative claims (non-Medicare), Record review
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure is the first step towards improving the practice of informed consent through quality measurement, and may compliment or serve as a platform for other measures of high-quality, patient-centered decision making. The reliability testing results should demonstrate hospital-level reliability. In addition, the measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:Consistent and patient-centered standards based on existing guidelines for informed consent can lead to improved patient autonomy, patient safety, and high-quality decision making.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on ensuring that each person and family is engaged as partners in their care; promoting effective communication and coordination of care; and working with communities to promote wide use of best practices to enable healthy living.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. A consistent and patient-centered standard based on existing guidelines for informed consent can lead to improved patient autonomy, patient safety, and high-quality decision making.
  
  
• Does the measure address a quality challenge? Yes. Among eight hospitals in the pilot study, the mean hospital score (based on a scale of 0 to 20, with 20 representing high quality informed consent documents) ranged from 3.2 to 7.8. In the top-performing hospital, only 86% of documents met a quality threshold of 5 or more points (out of 20), and 29% met a quality threshold of 10 or more points. Only 6% met a quality threshold of 15 or more points.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This informed consent document measure is a first step towards improving the practice of informed consent through quality measurement, and may compliment or serve as a platform for other measures of high-quality, patient-centered decision making.
  
  
• Can the measure can be feasibly reported? Yes. A pilot study of eight hospitals conducted during measure development confirmed the feasibility of requesting and receiving informed consent documents from hospitals.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and specified. Interrater reliability of the Abstraction Tool demonstrated during pilot testing. Hospital-level reliability testing in process. Face validity of the measure concept, specifications, and Abstraction Tool assessed.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. No negative unintended consequences identified during pilot testing of measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The goal of this measure of informed consent document quality is to support national strategies to promote patient-centered decision making. In evaluating hospitals' informed consent document quality, CMS seeks to increase the attention and effort that hospitals dedicate to providing high-quality informed consent, thereby supporting patient autonomy. This measure evaluates the quality of informed consent documents using items, developed through a consensus process, that are firmly based in the ethical and legal principles of informed consent, and are supported by patients as being meaningful improvements to the informed consent process. The measure aims to transform the informed consent document from a transactional form used to attain a patients’ signature to a meaningful document and resource that supports patients in the decision-making process. This informed consent document measure is a first step towards improving the practice of informed consent through quality measurement, and may compliment or serve as a platform for other measures of high-quality, patient-centered decision making. There are significant gaps in informed consent document quality and highly variable compliance with informed consent guidelines.[1-3] Hospitals often follow legal precedent, which results in perfunctory consent documents that convey the minimum amount of information necessary for compliance without providing patient-centered information that fosters patient autonomy or choice.[4-8] Prior studies, lawsuits and patient testimonies reflect a process that is broken, void of meaningful information for patients to develop informed preferences, and sometimes jeopardizing patient safety.[4,9-10] The implementation of a new quality measure that establishes a consistent and patient-centered standard based on existing guidelines for informed consent can lead to improved patient autonomy, patient safety, and high-quality decision making. The goal of this measure focuses on supporting the national efforts of CMS and NQF to improve patient-centered care and to fill several quality gaps in both the informed consent document and the measurement of these documents. References: 1. Bottrell MM, Alpert H, Fischbach RL, Emanuel LL. Hospital informed consent for procedure forms: facilitating quality patient-physician interaction. Archives of surgery (Chicago, Ill. : 1960). 2000;135(1):26-33. 2. Falagas ME, Korbila IP, Giannopoulou KP, Kondilis BK, Peppas G. Informed consent: how much and what do patients understand? American journal of surgery. 2009;198(3):420-435. 3. O'Neill O. Some limits of informed consent. Journal of medical ethics. 2003;29(1):4-7. 4. Oster, RR. Questioning Protocol, a Family's Perspective. Available at: http://www.engagingpatients.org/redesigning-the-care-experience/questioning-protocol-familys-perspective/. Accessed: July 5, 2015. 5. Habiba M, Jackson C, Akkad A, Kenyon S, Dixon-Woods M. Women's accounts of consenting to surgery: is consent a quality problem? Quality & safety in health care. 2004;13(6):422-427. 6. Childers R, Lipsett PA, Pawlik TM. Informed consent and the surgeon. Journal of the American College of Surgeons. 2009;208(4):627-634. 7. Mulley A, Trimble C, Elwyn G. Patients' preferences matter: stop the silent misdiagnosis. Bmj. 2012. 8. Krumholz HM, Schwartz J, Eddy E, et al. Surveillance Report: New Measure Probe. Not published: Prepared for: Centers for Medicare & Medicaid Services; Prepared by: Yale New Haven Health Services Corporation/Center for Outcomes Research and Evaluation (YNHHSC/CORE); 2014. 9. Montgomery v Lanarkshire Health Board. In: Court TS, ed. UKSC 11. United Kingdom. 2015. Available at: https://www.supremecourt.uk/decided-cases/docs/UKSC_2013_0136_Judgment.pdf. Accessed: July 5, 2016. 10. Statements on Principles. Relation of the Surgeon to the Patient: Informed Consent: American College of Surgeons; 2008:1-12.

Measure Specifications

• NQF Number (if applicable): 3089
  
  
• Description: Documentation of a nutrition care plan for those patients age 65 and older admitted to inpatient care who are found to be malnourished based on a completed nutrition assessment
  
  
• Numerator: Patients with a nutrition care plan documented in the patient´s medical record. Care plan components include, but are not limited to: Completed assessment results; data and time stamp; treatment goals; prioritization based on treatment severity; prescribed treatment / nutrition intervention; identification of members of the Care Team, timeline for patient follow-up.
  
  
• Denominator: Patients age 65 years and older admitted to inpatient care who are found to be malnourished based on a completed nutrition assessment.
  
  
• Exclusions: Patients with length of stay < 24 hours
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record, Record review
  
  
• Measure Type: Process
  
  
• Steward: The Academy of Nutrition and Dietetics
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is currently under review in NQF’s Health and Well-Being 2015-2017 project. The Standing Committee did not reach consensus on the Validity Criterion during the in-person meeting in September. The measure must pass the validity criterion and be recommended for endorsement.
  • Impact on quality of care for patients:This measure encourages documentation of a nutrition care plan for patients = 65 years with a finding of malnutrition. The Nutrition care plan may include completed assessment results, treatment goals, prioritization based on treatment severity, prescribed treatment/intervention, identification of members of the care team and a timeline for patient follow-up.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes . This measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The NQF Health and Well-Being Standing Committee that recently reviewed the measure agreed that the evidence provided demonstrated a that nutrition plans are related to patient outcomes.
  
  
• Does the measure address a quality challenge? Yes. Based on a national survey of hospital-based professionals in the United States focused on nutrition screening and assessment practices, out of 1,777 unique respondents, only 36.7% reported completing nutrition screening at admission, and 50.8% reported doing so within 24 hours. Only 69% reported documenting the findings in the medical record.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is not duplicative of an existing measure in IQR.
  
  
• Can the measure can be feasibly reported? Yes. Feasibility was assessed in 3 different EHR systems at 2 sites.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. The measure is fully developed and tested at the facility level in the hospital/acute care setting. The Standing Committee did not reach consensus on the Validity criterion because the percent agreement and Kappa statistic for the data element “nutrition care plan documented” at one test site was 83.0% and 0.58. The Standing Committee will revote on the Validity criterion on December 6, 2016 during the post-comment call.
  
  
• Measure development status: Field Testing; Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a new measure and has not been implemented.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted. Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Patients who are malnourished while in the hospital have an increased risk of complications, readmissions, and length of stay, which is associated with a significant increase in costs. Malnutrition is also associated with many adverse outcomes including depression of the immune system, impaired wound healing, muscle wasting, and increased mortality. Referral rates for dietetic assessment and treatment of malnourished patients have proven to be suboptimal, thereby increasing the likelihood of developing such aforementioned complications (Corkins, 2014), (Barker et al., 2011), (Amaral, et al., 2007), (Kruizenga et al. 2005). Presence of malnutrition/weight loss in hospitalized older adult patients is associated with higher odds of post-operative complications (including infections such as MRSA, C. diff, surgical site infections, and pneumonia) and decubitus ulcers (Fry, 2011). Nutritional status and progress are often not adequately documented in the medical record. It can be difficult to tell when (or if) patients are consuming food and supplements. In addition, nutritional procedures and EHR-triggered care are often lacking in the hospital. Similarly, nutritional care plans and patient issues are poorly communicated to post-acute facilities and PCPs (Corkins, 2014). Nutrition support intervention in patients identified by screening and assessment as at risk for malnutrition or malnourished may improve clinical outcomes (Mueller, 2011). Two research studies associated early nutritional care after risk identification with improved outcomes such as reduced length of stay, reduction in risk of readmissions, and cost of care (Lew, 2016), (Meehan, 2016). A systematic review of 62 studies with 10,187 randomized participants reported evidence for the effectiveness of nutritional supplements containing protein and energy. Overall, the review demonstrated that nutrition supplementation provided a significant reduction in mortality (RR 0.79, 95% CI 0.64 – 0.97) when patients were originally identified as “undernourished” (another term for malnourished). The risk of complications was reduced in 24 trials (RR 0.86, 95% CI 0.75-0.99) (Milne, 2009). A randomized controlled trial of 652 hospitalized, malnourished older adults over the age of 65 evaluated the use of a high-protein oral nutrition supplement for its impact on patient outcomes of non-elective readmission and mortality. The study found no effects towards improving 90-day readmission rate compared to placebo, but saw a significant reduction of 90-day mortality (p = 0.018) (Deutz, 2016). Finally, documentation of malnutrition diagnoses has been associated with significant healthcare cost savings per hospital day per patient (Amaral, 2007). Amaral TF, Matos LC, Tavares MM, Subtil A, Martins R, Nazaré M, et al. The economic impact of disease-related malnutrition at hospital admission. Clin Nutr. 2007 Dec;26(6):778–84. Barker LA, Gout BS, Crowe TC. Hospital malnutrition: prevalence, identification and impact on patients and the healthcare system. Int J Environ Res Public Health. 2011;8(2):514-27. Corkins MR, Guenter P, Dimaria-ghalili RA, et al. Malnutrition diagnoses in hospitalized patients: United States, 2010. JPEN J Parenter Enteral Nutr. 2014;38(2):186-95. Fry DE, Pine M, Jones BL, Meimban RJ. Patient characteristics and the occurrence of never events. Arch Surg. 2010;145(2):148-51. Kruizenga HM et al., Effectiveness and cost-effectiveness of early screening and treatment of malnourished patients. AM J Clin Nutrition. 2005 Nov 82(5): 1082-9. Lew CC, Yandell R, Fraser RJ, Chua AP, Chong MF, Miller M. Association Between Malnutrition and Clinical Outcomes in the Intensive Care Unit: A Systematic Review. JPEN J Parenter Enteral Nutr. 2016. Meehan A, Loose C, Bell J, Partridge J, Nelson J, Goates S. Health System Quality Improvement: Impact of Prompt Nutrition Care on Patient Outcomes and Health Care Costs. J Nurs Care Qual. 2016. Milne AC, Potter J, Vivanti A, Avenell A. Protein and energy supplementation in elderly people at risk from malnutrition. Cochrane Database Syst Rev. 2009;(2):CD003288. Mueller C, Compher C & Druyan ME and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical Guidelines: Nutrition Screening, Assessment, and Intervention in Adults. JPEN J Parenter Enteral Nutr. 2011;35: 16-24. White JV, et al. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN J Parenter Enteral Nutr. 2012;36(3):275–283. Somanchi et al., The Facilitated Early Enteral and Dietary Management Effectiveness Trial in Hospitalized Patients with Malnutrition. JPEN J Parenteral Enteral Nutr 2011 35:209.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Percentage of hospital patient panel who currently smoke according to the EHR structured data
  
  
• Numerator: Number of patients in the denominator whose recorded status indicates they are current smokers
  
  
• Denominator: Number of patients seen in the hospital during the reporting period
  
  
• Exclusions: An EP who sees no patients 13 years or older would be excluded from this requirement.
  
  
• HHS NQS Priority: Effective Prevention and Treatment, Best Practice of Healthy Living
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is not fully developed and tested in the acute inpatient setting. A more comprehensive measure, MUC16-50 Tobacco Use Screening (TOB-1), that likely captures smoking status has been proposed for IQR.
  • Impact on quality of care for patients:A more comprehensive measure that focuses on tobacco screening improves the quality of tobacco-cessation interventions patients receive while hospitalized.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on working with communities to promote wide use of best practices to enable healthy living and promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. NQF defines an outcome of care as the health status of a patient (or change in health status) resulting from healthcare—desirable or adverse. The evidence provided does not demonstrate that implementing this measure leads to a decrease in smoking prevalence.
  
  
• Does the measure address a quality challenge? Yes. Current smoking rates range from 10-30%, depending on geography. Between 2005-2009, 87% of lung cancer deaths, 61% of all pulmonary disease deaths, and 32% of all coronary heart disease deaths were attributable to smoking and secondhand smoke exposure (HHS, 2014), making it an essential risk factor to address in reducing both disease burden and health care costs.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? No. MUC16-50: Tobacco Use Screening (TOB-1) is a more comprehensive measure and likely includes smoking status. The denominator in MUC16-50 is: Patients who were comprehensively screened or refused screening within 3 days prior through 1 day after admission for tobacco use within the 30 days prior to the screening. A comprehensive tobacco use screen should identify the type of tobacco product used (cigarettes, smokeless tobacco, pipe tobacco, cigars), as well as the amount of cigarette use and frequency of pipe tobacco and cigar use.
  
  
• Can the measure can be feasibly reported? Yes. Smoking status is included in the Meaningful Use Core Objectives for hospitals (Stage 1). This enables a hospital to electronically record, change, and access the smoking status of a patient in accordance with the standards specified at § 170.207(h). https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/downloads/9_Record_Smoking_Status.pdf. A significant number of hospitals have met MU and will have the smoking attestation in their records.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is not fully developed, tested, and validated in the acute inpatient setting. The information provided states the measure was tested at the clinician level in the ambulatory/office-based care setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is not currently in use and no information provided about implementation issues from field testing.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Cigarette smoking is still the leading preventable cause of death and disease in the U.S. and costs the U.S. health care system nearly $170 billion in direct medical care for adults each year (CDC 2014a; HHS 2014; Xu et al. 2014). Currently more than 16 million US residents are living with a smoking-related illness (HHS 2014). Smoking harms nearly every organ in the body and has been causally linked to numerous cancers, heart disease and stroke, chronic obstructive pulmonary disease, pneumonia, other respiratory diseases, aortic aneurysm, peripheral vascular disease, cataracts and blindness, age-related macular degeneration, periodontitis, diabetes, pregnancy and reproductive complications, bone fractures, arthritis, and reduced immune function (HHS, 2014). Mortality among current smokers is two to three times that of persons who never smoked (Jha et al. 2013). Since the first Surgeon General’s Report on Smoking and Health in 1964, cigarette smoking has killed more than 20 million people in the U.S. (HHS 2014). Between 2005-2009, 87% of lung cancer deaths, 61% of all pulmonary disease deaths, and 32% of all coronary heart disease deaths were attributable to smoking and secondhand smoke exposure (HHS, 2014), making it an essential risk factor to address to reduce both disease burden and health care costs. The toll smoking takes on health extends beyond the smokers. Since 1964, almost 2.5 million nonsmoking adults have died from heart disease and lung cancer caused by exposure to secondhand smoke, and 100,000 babies have died of sudden infant death syndrome or complications from prematurity, low birth weight, or other conditions caused by parental smoking, particularly smoking by the mother (HHS, 2014). Reducing cigarette smoking in the community can impact the health and health care costs of nonsmokers as well. CDC (Centers for Disease Control and Prevention). (2014a). CDC’s Tips from Former Smokers campaign provided outstanding return on investment. Atlanta, GA. Available at: http://www.cdc.gov/media/releases/2014/p1210-tips-roi.html. (Accessed 27 October, 2015). HHS (US Department of Health and Human Services). (2014). The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health. Available at: http://www.surgeongeneral.gov/library/reports/50-years-of-progress/full-report.pdf. (Accessed 23 September, 2015). Xu X, Bishop EE, Kennedy SM, Simpson SA, Pechacek TF. (2014) Annual Healthcare Spending Attributable to Cigarette Smoking: An Update. American Journal of Preventive Medicine, 48(3), p.326-333. Available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4603661/ (Accessed 24 September, 2015). Jha, P. and Peto, R. (2014). Global effects of smoking, of quitting, and of taxing tobacco. New England Journal of Medicine, 2014(370), p.60-68. Available at: http://www.nejm.org/doi/full/10.1056/nejmra1308383. (Accessed 22 October, 2015). doi: 10.1056/NEJMra1308383

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Patients age 18 years and older with active, concurrent prescriptions for opioids at discharge, or patients with active, concurrent prescriptions for an opioid and benzodiazepine at discharge from a hospital-based encounter (inpatient, ED, outpatient)
  
  
• Numerator: Patients with active, concurrent prescriptions for opioids at discharge, or patients with active, concurrent prescriptions for an opioid and benzodiazepine at discharge
  
  
• Denominator: Patient age 18 years and older with an active opioid or benzodiazepine prescription, discharged from a hospital-based encounter (inpatient stay less than or equal to 120 days, ED, or outpatient) during the measurement period.
  
  
• Exclusions: Denominator exclusions: Patients with cancer or patients receiving palliative care
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This newly developed eMeasure was tested at the facility level in the emergency department setting and currently undergoing field testing. The testing results should demonstrate reliability and validity in the hospital setting for IQR. The measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages hospitals to identify patients discharged with concurrent prescriptions of opioids or opioids and benzodiazepines and discourage prescriptions for two or more different opioids or opioids and benzodiazepines concurrently.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The 2016 CDC Guideline for Prescribing Opioids for Chronic Pain states that clinicians should avoid prescribing opioids and benzodiazepines concurrently whenever possible.
  
  
• Does the measure address a quality challenge? Yes. According to data from the literature, 5-15% of patients receive concurrent opioid prescriptions and 5-20% of patients receive concurrent opioid-benzodiazepine prescriptions (Liu, Y., Logan, J. E., Paulozzi, L. J., Zhang, K., & Jones, C. M. (2013). Potential misuse and inappropriate prescription practices involving opioid analgesics. American Journal of Managed Care, 19(8), 648"“665. Retrieved [March 20, 2016] from http://www.ncbi.nlm.nih.gov/pubmed/24304213).
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is also proposed for consideration in the Hospital Outpatient Quality Reporting (HOQR) program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is based on medication and prescribing data found in the hospital inpatient, outpatient, or emergency department electronic health record system (EHR).
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and specified at the facility level in the emergency department setting. The measure is undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the inpatient hospital setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No . The measure is a newly developed eMeasure. The developer has noted that one unintended consequence of measure implementation could be under treatment of pain and anxiety as a result of abrupt cessation of medications or medication refusal when appropriate.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Unintentional opioid overdose fatalities have become an epidemic in the last 20 years and a major public health concern in the United States (Rudd 2016). Reducing the number of unintentional overdoses has become a priority for numerous federal organizations including the Centers for Disease Control and Prevention (CDC), the Federal Interagency Workgroup for Opioid Adverse Drug Events, and the Substance Abuse and Mental Health Services Administration. The U.S. Food and Drug Administration recently announced new requirements calling for class-wide changes to drug labeling, to help inform health care providers and patients of the serious risks associated with the combined use of certain opioid medications and benzodiazepines. Concurrent prescriptions of opioids or opioids and benzodiazepines puts patients at a greater risk of unintentional overdose due to the increased risk of respiratory depression (Dowell 2016). An analysis of national prescribing patterns shows that more than half of patients who received an opioid prescription in 2009 had filled another opioid prescription within the previous 30 days (NIDA 2011). Another analysis of more than 1 million hospital admissions in the United States found that over 43% of all patients with nonsurgical admissions were exposed to multiple opioids during their hospitalization (Herzig 2013). Studies of multiple claims and prescription databases have shown that between 5%-15% percent of patients receive concurrent opioid prescriptions and 5%-20% of patients receive concurrent opioid and benzodiazepine prescriptions across various settings (Liu 2013, Mack 2015, Park 2015). Patients who have multiple opioid prescriptions have an increased risk for overdose (Jena 2014). Rates of fatal overdose are ten times higher in patients who are co-dispensed opioid analgesics and benzodiazepines than opioids alone (Dasgupta 2015). Furthermore, concurrent use of benzodiazepines with opioids was prevalent in 31%-51% of fatal overdoses (Dowell 2016). Emergency Department (ED) visit rates involving both opioid analgesics and benzodiazepines increased from 11.0 in 2004 to 34.2 per 100,000 population in 2011 (Jones 2015). Adopting a measure that calculates the proportion of patients prescribed two or more different opioids or opioids and benzodiazepines concurrently, has the potential to reduce preventable mortality and reduce the costs associated with adverse events related to opioid use by 1) encouraging providers to identify patients with concurrent prescriptions of opioids or opioids and benzodiazepines and 2) discouraging providers from prescribing two or more different opioids or opioids and benzodiazepines concurrently. References: Dasgupta, N., et al. "Cohort Study of the Impact of High-dose Opioid Analgesics on Overdose Mortality", Pain Medicine, Wiley Periodicals, Inc., Sep 2015. http://onlinelibrary.wiley.com/doi/10.1111/pme.12907/abstract Dowell, D., Haegerich, T., Chou, R. "CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016". MMWR Recomm Rep 2016;65. http://www.cdc.gov/media/dpk/2016/dpk-opioid-prescription-guidelines.html Herzig, S., Rothberg, M., Cheung, M., et al. "Opioid utilization and opioid-related adverse events in nonsurgical patients in US hospitals". Nov 2013. DOI: 10.1002/jhm.2102. http://onlinelibrary.wiley.com/doi/10.1002/jhm.2102/abstract Jena, A., et al. "Opioid prescribing by multiple providers in Medicare: retrospective observational study of insurance claims", BMJ 2014; 348:g1393 doi: 10.1136/bmj.g1393. http://www.bmj.com/content/348/bmj.g1393 Jones, CM., McAninch, JK. "Emergency Department Visits and Overdose Deaths From Combined Use of Opioids and Benzodiazepines". Am J Prev Med. 2015 Oct;49(4):493-501. doi: 10.1016/j.amepre.2015.03.040. Epub 2015 Jul 3. http://www.ncbi.nlm.nih.gov/pubmed/26143953 Liu, Y., Logan, J., Paulozzi, L., et al. "Potential Misuse and Inappropriate Prescription Practices Involving Opioid Analgesics". Am J Manag Care. 2013 Aug;19(8):648-65. http://www.ajmc.com/journals/issue/2013/2013-1-vol19-n8/Potential-Misuse-and-Inappropriate-Prescription-Practices-Involving-Opioid-Analgesics/ Mack, K., Zhang, K., et al. "Prescription Practices involving Opioid Analgesics among Americans with Medicaid, 2010", J Health Care Poor Underserved. 2015 Feb; 26(1): 182-198. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4365785/ National Institute on Drug Abuse. "Analysis of opioid prescription practices finds areas of concern". April 2011. Retrieved from https://www.drugabuse.gov/news-events/news-releases/2011/04/analysis-opioid-prescription-practices-finds-areas-concern Park, T., et al. "Benzodiazepine Prescribing Patterns and Deaths from Drug Overdose among US Veterans Receiving Opioid Analgesics: Case-cohort Study", BMJ 2015; 350:h2698. http://www.bmj.com/content/350/bmj.h2698 Rudd, R., Aleshire, N., Zibbell, J., et al. "Increases in Drug and Opioid Overdose Deaths - United States, 2000-2014". MMWR, Jan 2016. 64(50);1378-82 http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6450a3.htm U.S. Food and Drug Administration. “FDA requires strong warnings for opioid analgesics, prescription opioid cough products, and benzodiazepine labeling related to serious risks and death from combined use”. Aug 31, 2016. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm518697.htm

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Inpatients age 6 months and older discharged during October, November, December, January, February or March who are screened for influenza vaccine status and vaccinated prior to discharge if indicated.
  
  
• Numerator: Inpatient discharges who were screened for influenza vaccine status and were vaccinated prior to discharge if indicated. Included Populations: - Patients who received the influenza vaccine during this inpatient hospitalization - Patients who received the influenza vaccine during the current year's flu season but prior to the current hospitalization - Patients who were offered and declined the influenza vaccine - Patients who have an allergy/sensitivity to the influenza vaccine, anaphylactic latex allergy or anaphylactic allergy to eggs, or for whom the vaccine is not likely to be effective because of bone marrow transplant within the past 6 months, or history of Guillain-Barre Syndrome within 6 weeks after a previous influenza vaccination.
  
  
• Denominator: Inpatients age 6 months and older discharged during the months of October, November, December, January, February or March.
  
  
• Exclusions: Denominator Exclusions: - Patients who expire prior to hospital discharge - Patients with an organ or bone marrow transplant during the current hospitalization - Patients who are discharged to another acute care hospital - Patients who leave Against Medical Advice (AMA) - Patients for whom vaccination was indicated, but supply had not been received by the hospital due to problems with vaccine production or distribution.
  
  
• HHS NQS Priority: Best Practice of Healthy Living
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The Health and Well-Being Standing Committee acknowledged the importance of this hospital-based measure, but did not believe the narrowing performance gaps were clinically significant in the chart-abstracted version of the measure (#1659). No data/evidence provided demonstrating that this eMeasure addresses a performance gap in IQR.
  • Impact on quality of care for patients:Approximately 94.0% of acute-care hospitalized patients are screened and vaccinated for influenza prior to discharge based on data from the chart-abstracted version of this measure (#1659). No evidence was provided that this eMeasure will increase the percentage of patients receiving influenza vaccine.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on working with communities to promote wide use of best practices to enable healthy living.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. CDC's Advisory Committee on Immunization Practices (ACIP) Recommends Universal Annual Influenza Vaccination to include all people aged 6 months and older.
  
  
• Does the measure address a quality challenge? No. In the 2014-2015 (4th qtr 2014 and 1st qtr 2015) influenza season 1,572,215 cases were submitted for the chart-version of IMM-2. Of those 94.16% were appropriately screened and vaccinated if indicated. The Health and Well-Being Standing Committee recently reviewed the chart-abstracted version of this measure (NQF #1659) and acknowledged the importance of this hospital-based measure, but did not believe the narrowing performance gaps were clinically significant. The Standing Committee recommended this measure for Inactive Endorsement with Reserve Status. Performance data was not provided from the eMeasure.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? No. The Health and Well-Being Standing Committee acknowledged the importance of this hospital-based measure, but did not believe the narrowing performance gaps were clinically significant in the chart-abstracted version of the measure (#1659).
  
  
• Can the measure can be feasibly reported? Yes. A feasibility scorecard, scorecard follow-up interviews, and the public comment process were used to assess the extent to which EHRs currently contain data elements required for implementation. Alpha testing confirmed that the measure data elements are readily available or could be captured without undue burden and that the measure specifications are feasible to implement.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This eMeasure is fully developed and specified. Reliability and validity preliminary testing results from field testing were not provided. Due to the Standing Committee’s recommendation for Inactive Endorsement with Reserve Status for the chart-abstracted version (#1659), the eMeasure does not meet NQF criteria for endorsement.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a newly developed eMeasure and is currently undergoing field testing. For this measure, the developer noted no potential unintended consequences were identified during development or through public comment.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Up to 1 in 5 people in the United States get influenza every season (CDC Key Facts 2015). Each year an average of approximately 226,000 people in the US are hospitalized with complications from influenza and between 3,000 and 49,000 die from the disease and its complications (Thompson 2003). Combined with pneumonia, influenza is the nation's 8th leading cause of death (Heron 2012). Up to two-thirds of all deaths attributable to pneumonia and influenza occur in the population of patients that have been hospitalized during flu season regardless of age (Fedson 2000). The Advisory Committee on Immunization Practices (ACIP) recommends seasonal influenza vaccination for all persons 6 months of age and older to highlight the importance of preventing influenza. Vaccination is associated with reductions in influenza among all age groups (Kostova 2013). The influenza vaccination is the most effective method for preventing influenza virus infection and its potentially severe complications. Screening and vaccination of inpatients is recommended, but hospitalization is an underutilized opportunity to provide vaccination to persons 6 months of age or older. References: Centers for Disease Control and Prevention. Key facts about influenza and the influenza vaccine, October 2015. Available at: http://www.cdc.gov/flu/keyfacts.htm. Accessed October 14, 2015. Fedson DS, Houck PM, Bratzler DW. Hospital-based influenza and pneumococcal vaccination: Sutton's Law applied to prevention. Infect Control Hosp Epi. 2000;21:692-699. Heron M. Deaths: Leading Causes for 2012. National Vital Statistics Reports; vol 64 no 10. Hyattsville, MD: National Center for Health Statistics. 2015. Kostova D, Reed C, Finelli L, Cheng P, Gargiullo PM, Shay DK, Singleton JA, Meltzer MI, Lu P,2 and Joseph S. Bresee1 Influenza Illness and Hospitalizations Averted by Influenza Vaccination in the United States, 2005-2011. PLoS One. 2013; 8(6): e66312 Thompson WW, Shay DK, Weintraub E, Brammer L, Cox N, Anderson LJ, Fukuda. Mortality associated with influenza and respiratory syncytial virus in the United States. JAMA. 2003 January 8; 289 (2): 179-186.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This measure assesses the proportion of hospitalized adult patients who were comprehensively screened (or refused screening) within 3 days prior through 1 day after admission for tobacco use within the 30 days prior to the screening.
  
  
• Numerator: Patients who were comprehensively screened or refused screening within 3 days prior through 1 day after admission for tobacco use within the 30 days prior to the screening. A comprehensive tobacco use screen should identify the type of tobacco product used (cigarettes, smokeless tobacco, pipe tobacco, cigars), as well as the amount of cigarette use and frequency of pipe tobacco and cigar use.
  
  
• Denominator: Patients age 18 years and older discharged from inpatient care during the measurement period, with a length of stay greater than 1 day and less than or equal to 120 days
  
  
• Exclusions: Denominator Exclusions: Patients with comfort measures documented within 3 days prior to or anytime during admission. A diagnosis indicative of impaired cognition that overlaps with the encounter. Patients with documentation of impaired cognition within 3 days prior through 1 day after admission, as evidenced by: * An assessment of the patient's cognitive status * Explicit documentation of impaired cognition as a reason not to perform a tobacco screening assessment
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This eMeasure is fully developed and specified at the facility level in the hospital setting. The measure is undergoing field testing. The testing results should demonstrate reliability and validity in the acute care setting. The eMeasure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages hospitals to ask all patients if they use tobacco and document their tobacco use status on a regular basis.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The 2008 clinical practice guideline on Treating Tobacco Use and Dependence from the U.S. Department of Health and Human Services, states that all patients should be asked if they use tobacco and should have their tobacco use status documented on a regular basis.
  
  
• Does the measure address a quality challenge? Yes. Using the data for the chart-abstracted version of this measure, as reported to the Joint Commission, Quarter 1 rates for 2014 and 2015 were 95.4% and 97.3% for the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program. Per the developer, the goal is that 100% of patients are screening for tobacco use. No data was provided demonstrating a performance gap in the acute-care hospital inpatient population.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The chart-abstraction version of this measure (NQF #1651) is in the Inpatient Psychiatric Facility Quality Reporting (IPFQR) program. NQF #0028 Preventive Care and Screening: Tobacco Use: Screening and Cessation Intervention is a clinician level measure that assesses screening with the use of any type of tobacco used with no specificity to product.
  
  
• Can the measure can be feasibly reported? Yes. The developer assessed the feasibility of collecting the data using hospital EHR systems and whether the reengineered measure may be calculated from an EHR without unduly burdening hospitals and vendors. Testing showed that the measure may be captured in the future without significant burden. Alpha testing showed that some elements (30-day look back for screening, patient refusal, and referral) are not currently available and required technical and workflow updates to collect. However, discussions with sites and vendors indicated updates can be made with minimal burden.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and specified at the facility level in the hospital setting. The eMeasure is currently undergoing field testing. No preliminary reliability and validity testing results provided.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a newly developed eMeasure and is currently undergoing field testing. For this measure, the developer noted no potential unintended consequences were identified during development or through public comment.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Tobacco use is the single greatest cause of disease in the United States today and accounts for more than 480,000 deaths each year (CDC MMWR 2014). Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases (DHHS 2014). Tobacco use creates a heavy cost to society as well as to individuals. Smoking-attributable health care expenditures are estimated to be at least $130 billion per year in direct medical expenses for adults, and over $150 billion in lost productivity (DHHS 2014). There is strong and consistent evidence that tobacco dependence interventions, if delivered in a timely and effective manner, significantly reduce the user's risk of suffering from tobacco-related disease and improve outcomes for those already suffering from a tobacco-related disease (DHHS 2000; Baumeister 2007; Lightwood 2003 and 1997; Rigotti 2012). Effective, evidence-based tobacco dependence interventions have been clearly identified and include brief clinician advice, individual, group, or telephone counseling, and use of FDA-approved medications. These treatments are clinically effective and extremely cost-effective relative to other commonly used disease prevention interventions and medical treatments. Hospitalization (both because hospitals are a tobacco-free environment and because patients may be more motivated to quit as a result of their illness) offers an ideal opportunity to provide cessation assistance that may promote the patient's medical recovery. Patients who receive even brief advice and intervention from their care providers are more likely to quit than those who receive no intervention (DHHS, 2008). References: Baumeister SE, Schumann A, Meyer C, et al. Effects of smoking cessation on health care use: is elevated risk of hospitalization among former smokers attributable to smoking-related morbidity? Drug Alcohol Depend. 2007 May 11;88(2-3):197-203. Epub 2006 Nov 21. Centers for Disease Control and Prevention. Current Cigarette Smoking Among Adults — United States, 2005–2013. Morbidity and Mortality Weekly Report (MMWR) 2014. 63(47); 1108-1112. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6347a4.htm?s_cid=mm6347a4_w Lightwood JM. The economics of smoking and cardiovascular disease. Prog Cardiovasc Dis. 2003 Jul-Aug;46(1):39-78. Lightwood JM, Glantz SA. Short-term economic and health benefits of smoking cessation: myocardial infarction and stroke. Circulation. 1997 Aug 19;96 (4):1089-96. Rigotti, et al. Interventions for smoking cessation in hospitalized patients. Cochrane Database of Systematic Reviews. 2012. Available from: http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD001837.pub3/abstract U.S. Department of Health and Human Services. Reducing tobacco use: a report of the Surgeon General. Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2000. US Department of Health and Human Services. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, CDC; 2014. Available at http://www.surgeongeneral.gov/library/reports/50-years-of-progress/full-report.pdf U.S. Department of Health and Human Services. Tobacco Use and Dependence Guideline Panel. Treating Tobacco Use and Dependence: 2008 Update. Rockville, MD, U.S. Department of Health and Human Services; 2008 May. Available from: http://www.ncbi.nlm.nih.gov/books/NBK63952/

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: TOB-2: This measure assesses the proportion of hospitalized adult patients who:*Are light tobacco users and received or refused practical counseling to quit within 3 days prior to or anytime during inpatient admission.*Are heavy tobacco users and received or refused practical counseling to quit AND received, had a medical reason not to receive or refused FDA-approved cessation medications within 3 days prior to or anytime during inpatient admission.TOB-2a: This measure assesses the proportion of hospitalized adult patients who:*Are light tobacco users and received practical counseling to quit within 3 days prior to or anytime during inpatient admission. * Are heavy tobacco users and received practical counseling to quit AND received, or had a medical reason not to receive, FDA-approved cessation medications within 3 days prior to or anytime during inpatient admission.
  
  
• Numerator: TOB-2: Patients who: *Are light tobacco users and received or refused practical counseling to quit within 3 days prior to or anytime during inpatient admission *Are heavy tobacco users and received or refused practical counseling to quit AND received, had a medical reason not to receive, or refused FDA-approved cessation medications within 3 days prior to or anytime during inpatient admission TOB-2a: Patients who: *Are light tobacco users and received practical counseling to quit within 3 days prior to or anytime during inpatient admission *Are heavy tobacco users and received practical counseling to quit AND received, or had a medical reason not to receive, FDA-approved cessation medications within 3 days prior to or anytime during inpatient admission
  
  
• Denominator: Patients identified as current tobacco users who are age 18 years and older discharged from inpatient care during the measurement period, with a length of stay greater than 1 day and less than or equal to 120 days.
  
  
• Exclusions: Denominator Exclusion: Patients with comfort measures documented within 3 days prior to or anytime during admission.
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Tobacco use is the single greatest cause of disease in the United States today and accounts for more than 480,000 deaths each year (CDC MMWR 2014). Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases (DHHS 2014). Tobacco use creates a heavy cost to society as well as to individuals. Smoking-attributable health care expenditures are estimated to be at least $130 billion per year in direct medical expenses for adults, and over $150 billion in lost productivity (DHHS 2014). There is strong and consistent evidence that tobacco dependence interventions, if delivered in a timely and effective manner, significantly reduce the user's risk of suffering from tobacco-related disease and improve outcomes for those already suffering from a tobacco-related disease (DHHS 2000; Baumeister 2007; Lightwood 2003 and 1997; Rigotti 2012). Effective, evidence-based tobacco dependence interventions have been clearly identified and include brief clinician advice, individual, group, or telephone counseling, and use of FDA-approved medications. These treatments are clinically effective and extremely cost-effective relative to other commonly used disease prevention interventions and medical treatments. Hospitalization (both because hospitals are a tobacco-free environment and because patients may be more motivated to quit as a result of their illness) offers an ideal opportunity to provide cessation assistance that may promote the patient's medical recovery. Patients who receive even brief advice and intervention from their care providers are more likely to quit than those who receive no intervention (DHHS, 2008). References: Baumeister SE, Schumann A, Meyer C, et al. Effects of smoking cessation on health care use: is elevated risk of hospitalization among former smokers attributable to smoking-related morbidity? Drug Alcohol Depend. 2007 May 11;88(2-3):197-203. Epub 2006 Nov 21. Centers for Disease Control and Prevention. Current Cigarette Smoking Among Adults — United States, 2005–2013. Morbidity and Mortality Weekly Report (MMWR) 2014. 63(47); 1108-1112. Available at: http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6347a4.htm?s_cid=mm6347a4_w Lightwood JM. The economics of smoking and cardiovascular disease. Prog Cardiovasc Dis. 2003 Jul-Aug;46(1):39-78. Lightwood JM, Glantz SA. Short-term economic and health benefits of smoking cessation: myocardial infarction and stroke. Circulation. 1997 Aug 19;96 (4):1089-96. Rigotti, et al. Interventions for smoking cessation in hospitalized patients. Cochrane Database of Systematic Reviews. 2012. Available from: http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD001837.pub3/abstract U.S. Department of Health and Human Services. Reducing tobacco use: a report of the Surgeon General. Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2000. US Department of Health and Human Services. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, CDC; 2014. Available at http://www.surgeongeneral.gov/library/reports/50-years-of-progress/full-report.pdf U.S. Department of Health and Human Services. Tobacco Use and Dependence Guideline Panel. Treating Tobacco Use and Dependence: 2008 Update. Rockville, MD, U.S. Department of Health and Human Services; 2008 May. Available from: http://www.ncbi.nlm.nih.gov/books/NBK63952/

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: TOB-3: This measure assesses the proportion of hospitalized adult patients who:*Are light tobacco users and were referred to or refused evidence-based outpatient counseling within 3 days prior to admission through 1 day after discharge.*Are heavy tobacco users and were referred to or refused evidence-based outpatient counseling AND received, had a medical reason not to receive, or refused a prescription for FDA-approved cessation medication upon discharge.TOB-3a: This measure assesses the proportion of hospitalized adult patients who:*Are light tobacco users and were referred to evidence-based outpatient counseling within 3 days prior to admission through 1 day after discharge.*Are heavy tobacco users and were referred to evidence-based outpatient counseling AND received or had a medical reason not to receive a prescription for FDA-approved cessation medication upon discharge.
  
  
• Numerator: TOB-3: Patients who: *Are light tobacco users and were referred to or refused evidence-based outpatient counseling within 3 days prior to admission through 1 day after discharge *Are heavy tobacco users and were referred to or refused evidence-based outpatient counseling AND received, had a medical reason not to receive, or refused a prescription for FDA-approved cessation medication upon discharge TOB-3a: Patients who: *Are light tobacco users and were referred to evidence-based outpatient counseling within 3 days prior to admission through 1 day after discharge *Are heavy tobacco users and were referred to evidence-based outpatient counseling AND received or had a medical reason not to receive a prescription for FDA-approved cessation medication upon discharge
  
  
• Denominator: Patients identified as current tobacco users age 18 years and older discharged from inpatient care to home or police custody during the measurement period, with a length of stay greater than 1 day and less than or equal to 120 days.
  
  
• Exclusions: Denominator Exclusions: Patients with comfort measures documented within 3 days prior to or anytime during admission.
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Tobacco use is the single greatest cause of disease in the United States today and accounts for more than 480,000 deaths each year (CDC MMWR 2014). Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases (DHHS 2014). Tobacco use creates a heavy cost to society as well as to individuals. Smoking-attributable health care expenditures are estimated to be at least $130 billion per year in direct medical expenses for adults, and over $150 billion in lost productivity (DHHS 2014). There is strong and consistent evidence that tobacco dependence interventions, if delivered in a timely and effective manner, significantly reduce the user's risk of suffering from tobacco-related disease and improve outcomes for those already suffering from a tobacco-related disease (DHHS 2000; Baumeister 2007; Lightwood 2003 and 1997; Rigotti 2012). Effective, evidence-based tobacco dependence interventions have been clearly identified and include brief clinician advice, individual, group, or telephone counseling, and use of FDA-approved medications. These treatments are clinically effective and extremely cost-effective relative to other commonly used disease prevention interventions and medical treatments. Hospitalization (both because hospitals are a tobacco-free environment and because patients may be more motivated to quit as a result of their illness) offers an ideal opportunity to provide cessation assistance that may promote the patient's medical recovery. Patients who receive even brief advice and intervention from their care providers are more likely to quit than those who receive no intervention (DHHS, 2008). References: Baumeister, S. E., Schumann, A., Meyer, C., John, U., Volzke, H., & Alte, D. (2007). Effects of smoking cessation on health care use: Is elevated risk of hospitalization among former smokers attributable to smoking-related morbidity? Drug and Alcohol Dependence, 88(2–3), 197–203. Centers for Disease Control and Prevention. (2014). Current cigarette smoking among adults—United States, 2005–2013. Morbidity and Mortality Weekly Report (MMWR), 63(47), 1108–1112. Retrieved from http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6347a4.htm?s_cid=mm6347a4_w. Lightwood, J. M. (2003). The economics of smoking and cardiovascular disease. Progress in Cardiovascular Diseases, 46(1), 39–78. Lightwood, J. M., & Glantz, S. A. (1997). Short-term economic and health benefits of smoking cessation: Myocardial infarction and stroke. Circulation, 96(4), 1089–1096. Rigotti, N. A., Clair, C., Munafo, M. R., & Stead, L. F. (2012). Interventions for smoking cessation in hospitalized patients. Cochrane Database of Systematic Reviews. Retrieved from http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD001837.pub3/abstract. U.S. Department of Health and Human Services. (2014). The health consequences of smoking—50 years of progress: A report of the Surgeon General. Atlanta, GA: U.S. Department of Health and Human Services. Reducing tobacco use: a report of the Surgeon General. Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2000. US Department of Health and Human Services. The health consequences of smoking—50 years of progress: a report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, CDC; 2014. Available at http://www.surgeongeneral.gov/library/reports/50-years-of-progress/full-report.pdf U.S. Department of Health and Human Services. Tobacco Use and Dependence Guideline Panel. Treating Tobacco Use and Dependence: 2008 Update. Rockville, MD, U.S. Department of Health and Human Services; 2008 May. Available from: http://www.ncbi.nlm.nih.gov/books/NBK63952/

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Proportion of inpatient hospitalizations for patients 65 years of age and older who do not demonstrate a threat to themselves or others but who receive antipsychotic medication therapy.
  
  
• Numerator: Inpatient hospitalizations for patients who received an order for an antipsychotic medication during the inpatient encounter
  
  
• Denominator: Inpatient hospitalizations for patients who are 65 and older
  
  
• Exclusions: Denominator exclusions: Inpatient hospitalizations for patients with a diagnosis of schizophrenia, Tourette's syndrome, bipolar disorder, Huntington's disease at the time of admission Numerator exclusions: Inpatient hospitalizations for patients with documented indication that they are threatening harm to self or others
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This newly developed eMeasure is fully developed and specified. The measure is currently undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting. In addition, the measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages hospitals against using antipsychotics as a standard first line of treatment for patients experiencing aggressive behavior unless they present a threat to themselves or their caregivers.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes . This measure focuses on making care safer by reducing harm caused in the delivery of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Clinical guidelines recommend against using antipsychotics as a standard first line of treatment for patients experiencing aggressive behavior unless they present a threat to themselves or their caregivers.
  
  
• Does the measure address a quality challenge? Yes. A summary of an ongoing study by the National Institutes of Health (NIH) suggests a strong link between antipsychotic use in hospitals and in nursing homes. Preliminary findings from this study indicate that nearly half of residents on antipsychotics in nursing homes began this therapy before admission. Given that over one-third of nursing home admissions come from the hospital, and nursing home residents have a high hospitalization rate, the NIH authors concluded that antipsychotics initiated in the hospital likely contribute to their use in nursing homes.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. Similar measures exist for use in in long-term care facilities. Another similar measure focuses on patients with dementia and is intended for use at the health plan level. This new Antipsychotics eMeasure is not limited to patients with dementia.
  
  
• Can the measure can be feasibly reported? Yes. This measure is based on medication and diagnosis data found in the hospital inpatient electronic health record system (EHR).
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and specified at the facility level in the hospital setting. The eMeasure is currently undergoing field testing. No preliminary reliability and validity testing results provided.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a newly developed eMeasure and is currently undergoing field testing. For this measure, the developer noted that one potential unintended consequence is the increased inappropriate use of physical or other chemical restraints in situations where providers previously inappropriately used antipsychotics.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Hospitalized patients are at risk for delirium, or "acute confusional state," which is a common clinical syndrome that is associated with increased mortality in ICU patients as well as the advancement of cognitive impairment. Antipsychotics are often used off-label as a method of treating patients in an acute confusional state despite conflicting evidence regarding the effectiveness of antipsychotics in treating these disorders. Clinical guidelines recommend against using antipsychotics as a standard first line of treatment for patients experiencing aggressive behavior unless they present a threat to themselves or their caregivers. References: American Geriatrics Society updated Beers Criteria for potentially inappropriate medication use in older adults. Journal of the American Geriatrics Society. Oct 2015 ;63:2227-2246; 2015. Practice guideline for the treatment of patients with delirium. American Psychiatric Association. The American journal of psychiatry. May 1999;156(5 Suppl):1-20. Barr J, Fraser GL, Puntillo K, et al. Clinical practice guidelines for the management of pain, agitation, and delirium in adult patients in the intensive care unit. Crit Care Med. Jan 2013;41(1):263-306. Barr J, Pandharipande PP. The pain, agitation, and delirium care bundle: synergistic benefits of implementing the 2013 Pain, Agitation, and Delirium Guidelines in an integrated and interdisciplinary fashion. Crit Care Med. Sep 2013;41(9 Suppl 1):S99-115. Campbell N, Boustani MA, Ayub A, et al. Pharmacological management of delirium in hospitalized adults--a systematic evidence review. Journal of general internal medicine. Jul 2009;24(7):848-853. Flaherty JH, Gonzales JP, Dong B. Antipsychotics in the treatment of delirium in older hospitalized adults: a systematic review. Journal of the American Geriatrics Society. Nov 2011;59 Suppl 2:S269-276. NICE (National Institute for Health and Clinical Excellence) Dementia: Supporting people with dementia and their careers in health and social care. 2015 (Issued November 2006, Modified March 2015). Rooney S, Qadir M, Adamis D, McCarthy G. Diagnostic and treatment practices of delirium in a general hospital. Aging Clin Exp Res. Dec 2014;26(6):625-633. Sampson EL, White N, Leurent B, et al. Behavioural and psychiatric symptoms in people with dementia admitted to the acute hospital: prospective cohort study. The British journal of psychiatry: the journal of mental science. Sep 2014;205(3):189-196. Sampson EL, White N, Lord K, et al. Pain, agitation, and behavioural problems in people with dementia admitted to general hospital wards: a longitudinal cohort study. Pain. Apr 2015;156(4):675-683. Tjia J, Briesacher BA, Peterson D, Liu Q, Andrade SE, Mitchell SL. Use of medications of questionable benefit in advanced dementia. JAMA internal medicine. Nov 2014;174(11):1763-1771.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Median elapsed time from emergency department arrival to emergency room departure for patients discharged from the emergency department
  
  
• Numerator: Time (in minutes) from emergency department (ED) arrival to ED departure for patients discharged from the ED
  
  
• Denominator: Any emergency department (ED) patient from the facility's ED
  
  
• Exclusions: Emergency department encounters where the patient expired during the encounter or where the ED visit is followed within an hour by an inpatient encounter at the same physical facility
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This eMeasure is fully developed, tested and currently implemented in IQR. This eMeasure uses EHR data rather than chart abstracted data to determine patient arrival and discharge times in the emergency department. Testing data should be provided demonstrating that this eMeasure more accurately determines patient arrival and discharge times compared to the chart abstracted version of the measure (NQF #0496) currently in the HOQR and HIQR programs. This eMeasure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:Reducing the median time from ED arrival to the time of departure from the emergency room potentially improves access to care specific to the patient condition and increases the capability to provide additional treatment.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Reducing the time patients remain in the emergency department (ED) can improve access to treatment and increase quality of care. Reducing this time potentially improves access to care specific to the patient condition and increases the capability to provide additional treatment. In 2014, the NQF Care Coordination Steering Committee reviewed the chart abstracted version of this measure (NQF #0496) and agreed the evidence presented was sufficient to support the measure.
  
  
• Does the measure address a quality challenge? Yes. There is no evidence provided to indicate there is a gap in performance based on this eMeasure. The Care Coordination Steering Committee noted the trend data provided in 2014 did not show improvement in performance on the chart abstracted version of this measure (NQF #0496). No updated performance data was provided from the chart abstracted version or this eMeasure.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The chart abstracted version of this measure (NQF #0495) is publicly reported on Hospital Compare. This eMeasure version is currently in the Hospital Inpatient Quality Reporting (IQR) program. This eMeasure uses EHR data, rather than chart abstracted data to more accurately determine patient arrival and discharge times in the emergency department.
  
  
• Can the measure can be feasibly reported? Yes. This measure is based on facility discharge data captured upon patient arrival and discharge from the facility EHR or point of service software.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This eMeasure is fully developed and currently in the IQR program. No testing information provided to demonstrate that this eMeasure is reliable and valid in the outpatient setting and that it determines patient arrival and discharge times more accurately than the chart abstracted version.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. For this measure, the developer states that no potential unintended consequences were identified during development or implementation.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In recent times, EDs have experienced significant overcrowding. Although once only a problem in large, urban, teaching hospitals, the phenomenon has spread to other suburban and rural healthcare organizations. According to a 2002 national U.S. survey, more than 90 percent of large hospitals report EDs operating "at" or "over" capacity. Overcrowding and heavy emergency resource demand have led to a number of problems, including ambulance refusals, prolonged patient waiting times, increased suffering for those who wait, rushed and unpleasant treatment environments, and potentially poor patient outcomes. Approximately one third of hospitals in the U.S. report increases in ambulance diversion in a given year, whereas up to half report crowded conditions in the ED. In a recent national survey, 40 percent of hospital leaders viewed ED crowding as a symptom of workforce shortages. ED crowding may result in delays in the administration of medication such as antibiotics for pneumonia and has been associated with perceptions of compromised emergency care. For patients with non-ST-segment-elevation myocardial infarction, long ED stays were associated with decreased use of guideline-recommended therapies and a higher risk of recurrent myocardial infarction. When EDs are overwhelmed, their ability to respond to community emergencies and disasters may be compromised. References: Derlet RW, Richards JR. Emergency department overcrowding in Florida, New York, and Texas. South Med J. 2002;95:846-9. Derlet RW, Richards JR. Overcrowding in the nation's emergency departments: complex causes and disturbing effects. Ann Emerg Med. 2000; 35:63-8. Fatovich DM, Hirsch RL. Entry overload, emergency department overcrowding, and ambulance bypass. Emerg Med J. 2003; 20:406-9. Hwang U, Richardson LD, Sonuyi TO, Morrison RS. The effect of emergency department crowding on the management of pain in older adults with hip fracture. J Am Geriatr Soc. 2006; 54:270-5. Pines JM, et al. ED crowding is associated with variable perceptions of care compromise. Acad Emerg Med. 2007;14:1176-81. Pines JM, et al. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51:6-7. Schull MJ, et al. Emergency department crowding and thrombolysis delays in acute myocardial infarction. Ann Emerg Med. 2004;44:577-85. Trzeciak S, Rivers EP. Emergency department overcrowding in the United States: an emerging threat to patient safety and public health. Emerg Med J. 2003;20:402-5. Wilper AP, Woolhandler S, Lasser KE, McCormick D, Cutrona SL, Bor DH, Himmelstein DU. Waits to see an emergency department physician: U.S. trends and predictors, 1997-2004. Health Aff (Millwood). 2008;27:w84-95.

Measure Specifications

• NQF Number (if applicable): 662
  
  
• Description: Median time from emergency department arrival to time of initial oral, nasal or parenteral pain medication administration for emergency department patients with a principal diagnosis of long bone fracture (LBF)
  
  
• Numerator: Time (in minutes) from emergency department (ED) arrival to time of initial oral, intranasal or parenteral pain medication administration for ED patients with a diagnosis of a long bone fracture (LBF). Previous measure specifications only allowed for oral pain medication to be administered for patients aged 2 through 18 years; the abstraction guidance has been removed for this measure allowing patients aged 18 and over to be included, increasing the number of cases for the measure.
  
  
• Denominator: Patients with a patient age on Outpatient Encounter Date (Outpatient Encounter Date ? Birthdate) greater than or equal to 2 years, and - An International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) Principal Diagnosis Code for a (long bone) fracture (as defined in Appendix A, OP Table 9.0 of the original measure documentation), and - Patients with Pain Medication (as defined in the Data Dictionary), and - An Evaluation and Management (E/M) Code for emergency department (ED) encounter (as defined in Appendix A, OP Table 1.0 of the original measure documentation)
  
  
• Exclusions: Patients less than 2 years of age - Patients who expired - Patients who left the emergency department against medical advice or discontinued care
  
  
• HHS NQS Priority: Making Care Safer, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative clinical data, Paper medical record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: De-endorsed
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure is currently in the Hospital Outpatient Quality Reporting (HOQR) program. The NQF Musculoskeletal Steering Committee agreed that the evidence supporting this measure is insufficient. The measure was de-endorsed in 2014.
  • Impact on quality of care for patients:This measure captures the median time to pain medication administration for long bone fractures for patients in the ED. Median time for pain medication administration does not indicate adequate pain management in the ED related to long bone fractures.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on making care safer by reducing harm caused in the delivery of care and promoting the most effective prevention and treatment practices for the leading causes of mortality, starting with cardiovascular disease.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The NQF Musculoskeletal Steering Committee reviewed the measure in 2014. The Committee noted that the evidence presented did not sufficiently link the process of measuring and reporting the time gap between arrival and administration of pain medication for long bone fractures to improved clinical outcomes. The Committee agreed that less time to administration is likely better, but the evidence was also lacking to support a particular timeframe for treating pain in long bone fractures. The Committee agreed that the measure did not meet the Evidence criterion and was not recommended for NQF endorsement.
  
  
• Does the measure address a quality challenge? No . In 2014, a review of 3,166 of 4,803 reporting facilities reported performance scores ranging from 14–167 minutes and an interquartile range of 43–66 minutes. This data demonstrates a variation in performance but there is no evidence supporting an acceptable timeframe for treating pain in long bone fractures indicating this is a quality issue.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? No. The measure is currently in the Hospital Outpatient Quality Reporting (HOQR) program; however, according to the NQF Musculoskeletal Steering Committee there is not sufficient evidence to support this measure. In addition, it appears the measure has been specified for patients 2 years and older for all 3 routes of pain medication administration.
  
  
• Can the measure can be feasibly reported? Yes. The measure is publicly reported on Hospital Compare.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure was de-endorsed in 2014.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The Steering Committee agreed the measure addresses efficiency, and recognized thatcare in the ED should be timely and efficient and noted that the evidence presented indicates thatdisparities in adequate pain management exist based on age and race. However, Committee members were concerned that measuring median time to pain administration is an indirect way to measure the adequacy of pain management in the ED, and were concerned about unintended consequences for complex patients. Committee members also observed that there is a spectrum of patients with fractures included in the measure, and that the metric may be more or less meaningful depending on the type of fracture presented.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? De-endorsed. De-endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? No.
  
  

Rationale for measure provided by HHS
Pain management in patients with long bone fractures is undertreated in emergency departments (Ritsema et al., 2007). Emergency department pain management has room for improvement (Ritsema et al., 2007). Patients with bone fractures continue to lack administration of pain medication as part of treatment regimens (Brown et al., 2003). When performance measures are implemented for pain management of these patients administration and treatment rates for pain improve (Herr & Titler, 2009). Disparities continue to exist in the administration of pain medication for minorities (Epps, Ware, & Packard, 2008; Todd, Samaroo, & Hoffman, 1993) and children as well (Brown et al., 2003; Friedland & Kulick, 1994). References: Brown JC, Klein EJ, Lewis CW, Johnston BD, Cummings P. Emergency department analgesia for fracture pain. Ann Emerg Med. 2003 Aug;42(2):197-205. Centers for Medicare and Medicaid Services (CMS). Hospital outpatient quality reporting specifications manual, version 9.0a. Baltimore (MD): Centers for Medicare and Medicaid Services (CMS); Effective 2016 Jan 1. various p. Epps CD, Ware LJ, Packard A. Ethnic wait time differences in analgesic administration in the emergency department. Pain Manag Nurs. 2008 Mar;9(1):26-32. Friedland LR, Kulick RM. Emergency department analgesic use in pediatric trauma victims with fractures. Ann Emerg Med. 1994 Feb;23(2):203-7. Herr K, Titler M. Acute pain assessment and pharmacological management practices for the older adult with a hip fracture: review of ED trends. J Emerg Nurs. 2009 Jul;35(4):312-20. Ritsema TS, Kelen GD, Pronovost PJ, Pham JC. The national trend in quality of emergency department pain management for long bone fractures. Acad Emerg Med. 2007 Feb;14(2):163-9. Todd KH, Samaroo N, Hoffman JR. Ethnicity as a risk factor for inadequate emergency department analgesia. JAMA. 1993 Mar 24-31;269(12):1537-9.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Muscoloskeletal
  
  
• Review for Importance: 1a. Evidence: H-0; M-3; L-7; I-9; IE-2; 1b. Performance Gap: H-NA; M-NA; L-NA; I-NA; 1c. Impact: H-NA; M-NA; L-NA; I-NA Rationale: • Evidence provided by the developer included studies that evaluated pain management practices for long bone fractures in the hospital emergency room. The Committee questioned if the evidence provided by the developer directly supported the measure focus, which is to improve the median time of pain medication administration from emergency department arrival for emergency department patients with a principal diagnosis of long bone fracture. Committee members noted that the studies presented didn’t sufficiently link the process of measuring and reporting the time gap between arrival and administration of pain medication for long bone fractures to improved clinical outcomes. Committee members agreed that less time to administration is likely better, but the evidence was also lacking to support a particular timeframe for treating pain in long bone fractures. Members acknowledged that there are no clinical guidelines that support or give a particular timeframe for treatment. Subsequently, the Committee agreed that the evidence presented was insufficient for meeting the evidence criterion.
  
  
• Review for Scientific Acceptability: N/A
  
  
• Review for Feasibility: N/A
  
  
• Review for Usability: N/A
  
  
• Review for Related and Competing Measures: N/A
  
  
• Endorsement Public Comments: Comment: • One commenter, the American College of Emergency Physicians (ACEP) submitted a letter requesting reconsideration of this measure for endorsement. The letter included comments that: o the evidence and performance gap for the measure were previously established, including by an NQF Committee in 2011 o there is inadequate pain management among patients with long bone fracture (LBF) presenting to the ED, and that certain populations may not be receiving appropriate pain management in the ED, and o the measure is in use in the Hospital Outpatient Quality Reporting (HOQR) program and has been approved by the NQF Measures Application Partnership for use in the PQRS program and was approved in 2014 for use in the American Board of Emergency Medicine Maintenance of Certification Part IV activities. The letter is available at this link. Developer response: The developer submitted a letter requesting reconsideration of this measure for endorsement. The developer expressed concern that this measure, which is focused on timely pain management for ED patients with long bone fractures, was considered in the Musculoskeletal portfolio. The developer notes that the measure “focuses on the coordination and timely delivery of care to ED patients” and should have been evaluated within the Care Coordination portfolio with other ED timeliness measures. The developer also noted that: • the Committee cited a lack of evidence linking the process of care to defined patient outcomes, and responds that numerous studies demonstrated that pain is often inadequately managed in the ED 42 • the Committee highlighted a lack of exclusion tin the measure for patients for whom pain medication is contraindicated, and responds that these patients would not be included in the measure, and • the measure was developed as part of a group of measures targeting efficiency of care in the ED and time to long bone fracture pain management was identified as measurement area for which a denominator population could be clearly defined with few unintended consequences, and the denominator population would consist of patients for whom pain management is almost always warranted. The letter is available at this link. Committee response: The Committee agreed the measure addresses efficiency, and recognized that care in the ED should be timely and efficient and noted that the evidence presented indicates that disparities in adequate pain management exist based on age and race. However, members were concerned that the measuring median time to pain administration is an indirect way to measure the adequacy of pain management in the ED, and were concerned about unintended consequences for complex patients. Members also observed that there is a spectrum of patients with fractures included in the measure, and that the metric may be more or less meaningful depending on the type of fracture presented. The Committee again raised concerns that there is little evidence linking the measurement of the median time to pain management for long bone fractures to improved clinical outcomes, questioned whether there could be a more direct way of measuring adequacy of pain management, and questioned how success on the measure would be defined. As a result, the Committee declined to reconsider the measure. NQF response: Throughout the various iterations of the NQF measure evaluation criteria, it is true that the basic criteria and concepts have remained largely unchanged. However, the measure evaluation guidance—which focuses on the specificity and rigor with which the criteria are applied—has become more comprehensive and more specific over time. Assignment of measures is based on the focus of the measure and the relevant Committee expertise required in reviewing measures. While there were concerns expressed regarding assignment of this measure to this portfolio, the measure evaluation guidance is also intended to promote consistency in evaluation across measures against the NQF criteria, regardless of the project.
  
  
• Endorsement Committee Recommendation: N/A
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Patients age 18 years and older with active, concurrent prescriptions for opioids at discharge, or patients with active, concurrent prescriptions for an opioid and benzodiazepine at discharge from a hospital-based encounter (inpatient, ED, outpatient)
  
  
• Numerator: Patients with active, concurrent prescriptions for opioids at discharge, or patients with active, concurrent prescriptions for an opioid and benzodiazepine at discharge
  
  
• Denominator: Patient age 18 years and older with an active opioid or benzodiazepine prescription, discharged from a hospital-based encounter (inpatient stay less than or equal to 120 days, ED, or outpatient) during the measurement period.
  
  
• Exclusions: Denominator exclusions: Patients with cancer or patients receiving palliative care
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Electronic Health Record
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This newly developed eMeasure was tested at the facility level in the emergency department setting and currently undergoing field testing. The testing results should demonstrate reliability and validity in the outpatient setting for HOQR. The measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages outpatient facilities to identify patients discharged with concurrent prescriptions of opioids or opioids and benzodiazepines and discourage prescriptions for two or more different opioids or opioids and benzodiazepines concurrently.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. The 2016 CDC Guideline for Prescribing Opioids for Chronic Pain states that clinicians should avoid prescribing opioids and benzodiazepines concurrently whenever possible.
  
  
• Does the measure address a quality challenge? Yes. According to data from the literature, 5-15% of patients receive concurrent opioid prescriptions and 5-20% of patients receive concurrent opioid-benzodiazepine prescriptions (Liu, Y., Logan, J. E., Paulozzi, L. J., Zhang, K., & Jones, C. M. (2013). Potential misuse and inappropriate prescription practices involving opioid analgesics. American Journal of Managed Care, 19(8), 648"“665. Retrieved [March 20, 2016] from http://www.ncbi.nlm.nih.gov/pubmed/24304213).
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The measure is also proposed for consideration in the Hospital Inpatient Quality Reporting (HIQR) program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is based on medication and prescribing data found in the hospital inpatient, outpatient, or emergency department electronic health record system (EHR).
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is fully developed and specified at the facility level in the emergency department setting. The measure is undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the outpatient hospital setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is a newly developed eMeasure. The developer has noted that one unintended consequence of measure implementation could be under treatment of pain and anxiety as a result of abrupt cessation of medications or medication refusal when appropriate.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Unintentional opioid overdose fatalities have become an epidemic in the last 20 years and a major public health concern in the United States (Rudd 2016). Reducing the number of unintentional overdoses has become a priority for numerous federal organizations including the Centers for Disease Control and Prevention (CDC), the Federal Interagency Workgroup for Opioid Adverse Drug Events, and the Substance Abuse and Mental Health Services Administration. The U.S. Food and Drug Administration recently announced new requirements calling for class-wide changes to drug labeling, to help inform health care providers and patients of the serious risks associated with the combined use of certain opioid medications and benzodiazepines. Concurrent prescriptions of opioids or opioids and benzodiazepines puts patients at a greater risk of unintentional overdose due to the increased risk of respiratory depression (Dowell 2016). An analysis of national prescribing patterns shows that more than half of patients who received an opioid prescription in 2009 had filled another opioid prescription within the previous 30 days (NIDA 2011). Another analysis of more than 1 million hospital admissions in the United States found that over 43% of all patients with nonsurgical admissions were exposed to multiple opioids during their hospitalization (Herzig 2013). Studies of multiple claims and prescription databases have shown that between 5%-15% percent of patients receive concurrent opioid prescriptions and 5%-20% of patients receive concurrent opioid and benzodiazepine prescriptions across various settings (Liu 2013, Mack 2015, Park 2015). Patients who have multiple opioid prescriptions have an increased risk for overdose (Jena 2014). Rates of fatal overdose are ten times higher in patients who are co-dispensed opioid analgesics and benzodiazepines than opioids alone (Dasgupta 2015). Furthermore, concurrent use of benzodiazepines with opioids was prevalent in 31%-51% of fatal overdoses (Dowell 2016). Emergency Department (ED) visit rates involving both opioid analgesics and benzodiazepines increased from 11.0 in 2004 to 34.2 per 100,000 population in 2011 (Jones 2015). Adopting a measure that calculates the proportion of patients prescribed two or more different opioids or opioids and benzodiazepines concurrently, has the potential to reduce preventable mortality and reduce the costs associated with adverse events related to opioid use by 1) encouraging providers to identify patients with concurrent prescriptions of opioids or opioids and benzodiazepines and 2) discouraging providers from prescribing two or more different opioids or opioids and benzodiazepines concurrently. References: Dasgupta, N., et al. "Cohort Study of the Impact of High-dose Opioid Analgesics on Overdose Mortality", Pain Medicine, Wiley Periodicals, Inc., Sep 2015. http://onlinelibrary.wiley.com/doi/10.1111/pme.12907/abstract Dowell, D., Haegerich, T., Chou, R. "CDC Guideline for Prescribing Opioids for Chronic Pain - United States, 2016". MMWR Recomm Rep 2016;65. http://www.cdc.gov/media/dpk/2016/dpk-opioid-prescription-guidelines.html Herzig, S., Rothberg, M., Cheung, M., et al. "Opioid utilization and opioid-related adverse events in nonsurgical patients in US hospitals". Nov 2013. DOI: 10.1002/jhm.2102. http://onlinelibrary.wiley.com/doi/10.1002/jhm.2102/abstract Jena, A., et al. "Opioid prescribing by multiple providers in Medicare: retrospective observational study of insurance claims", BMJ 2014; 348:g1393 doi: 10.1136/bmj.g1393. http://www.bmj.com/content/348/bmj.g1393 Jones, CM., McAninch, JK. "Emergency Department Visits and Overdose Deaths From Combined Use of Opioids and Benzodiazepines". Am J Prev Med. 2015 Oct;49(4):493-501. doi: 10.1016/j.amepre.2015.03.040. Epub 2015 Jul 3. http://www.ncbi.nlm.nih.gov/pubmed/26143953 Liu, Y., Logan, J., Paulozzi, L., et al. "Potential Misuse and Inappropriate Prescription Practices Involving Opioid Analgesics". Am J Manag Care. 2013 Aug;19(8):648-65. http://www.ajmc.com/journals/issue/2013/2013-1-vol19-n8/Potential-Misuse-and-Inappropriate-Prescription-Practices-Involving-Opioid-Analgesics/ Mack, K., Zhang, K., et al. "Prescription Practices involving Opioid Analgesics among Americans with Medicaid, 2010", J Health Care Poor Underserved. 2015 Feb; 26(1): 182-198. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4365785/ National Institute on Drug Abuse. "Analysis of opioid prescription practices finds areas of concern". April 2011. Retrieved from https://www.drugabuse.gov/news-events/news-releases/2011/04/analysis-opioid-prescription-practices-finds-areas-concern Park, T., et al. "Benzodiazepine Prescribing Patterns and Deaths from Drug Overdose among US Veterans Receiving Opioid Analgesics: Case-cohort Study", BMJ 2015; 350:h2698. http://www.bmj.com/content/350/bmj.h2698 Rudd, R., Aleshire, N., Zibbell, J., et al. "Increases in Drug and Opioid Overdose Deaths - United States, 2000-2014". MMWR, Jan 2016. 64(50);1378-82 http://www.cdc.gov/mmwr/preview/mmwrhtml/mm6450a3.htm U.S. Food and Drug Administration. “FDA requires strong warnings for opioid analgesics, prescription opioid cough products, and benzodiazepine labeling related to serious risks and death from combined use”. Aug 31, 2016. http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm518697.htm

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The following questions (or a subset of questions) would replace the current Pain Management measure in the HCAHPS Survey with a new measure(s). The following items were tested in early 2016. CMS is currently analyzing the results, as well as discussing these potential new pain management items with focus groups and hospital staff. Multi-item measure (composite): HP1: “During this hospital stay, did you have any pain?” HP2: “During this hospital stay, how often did hospital staff talk with you about how much pain you had?” HP3: “During this hospital stay, how often did hospital staff talk with you about how to treat your pain?” HP4: “During this hospital stay, did you get medicine for pain?” HP5: “Before giving you pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Numerator: HCAHPS Survey measures are calculated using top-box scoring. The top-box refers to the percentage of patients who choose the most positive response option. For questions HP2 and HP3 in this measure, the top-box numerator is number of respondents who answer “Always.” For question HP5, the top-box numerator is number of respondents who answer “Yes.” Questions HP1 and HP4 are screener items that serve to direct respondents to subsequent questions, if applicable. HP1: “During this hospital stay, did you have any pain?” HP2: “During this hospital stay, how often did hospital staff talk with you about how much pain you had?” HP3: “During this hospital stay, how often did hospital staff talk with you about how to treat your pain?” HP4: “During this hospital stay, did you get medicine for pain?” HP5: “Before giving you pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Denominator: The top box denominator is the number of respondents who answer at least one of the questions in this multi-item measure, that is, questions HP2, HP3 and HP5.
  
  
• Exclusions: Patients who respond “No” to question HP1 are excluded from questions HP2 and HP3. Patients who respond “No” to question HP4 are excluded from question HP5. In addition, the following types of patients are excluded from the HCAHPS Survey: Patients younger than 18 years old at time of admission; Patients who did not have at least one overnight station in the hospital; Patients who were not admitted in the medical, surgical or maternity service lines; Patients who were not alive at time of discharge; “No-Publicity” patients – Patients who request that they not be contacted; Court/Law enforcement patients (i.e., prisoners); Patients with a foreign home address; Patients discharged to hospice care; Patients who are excluded because of state regulations; Patients discharged to nursing homes and skilled nursing facilities. For details, see HCAHPS Quality Assurance Guidelines, V11.0 at http://www.hcahpsonline.org/qaguidelines.aspx
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Survey
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is undergoing field testing and is intended to replace the Pain Management composite measure in the HCAHPS Survey in response to concerns expressed by physicians, hospitals and others about the current Pain Management items in the survey. The testing results should demonstrate that the measure is reliable and valid in IQR. In addition, the survey should be submitted to NQF for review and endorsement of this new composite measure that focuses on communication about pain during the hospital stay.
  • Impact on quality of care for patients:This measure can improve how hospital staff communicate with patients about pain during their hospital stay.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure promotes effective communication and coordination of care and ensures that each person and family is engaged as partners in their care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The scientific evidence-base and rationale for how this outcome measure is influenced by healthcare processes or structures was not provided. CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff in response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey.
  
  
• Does the measure address a quality challenge? Yes. The average top-box score for hospitals on the current Pain Management measure is 71.0%, indicating there is room for improvement.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The proposed measure will replace the Pain Management composite measure currently in the HCAHPS Survey for IQR and VBP. The proposed measure focuses on communication about pain during the patient’s hospital stay, rather than how well pain was controlled.
  
  
• Can the measure can be feasibly reported? Yes. CMS is testing this measure on Q1’16 hospital discharges from 50 hospitals. Additionally, the previous measure has been reported since 2006.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is currently undergoing field testing on patients discharged from 50 hospitals Q1’16.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. CMS states they are not aware of any unintended consequences from the use of this measure. The measure is currently undergoing field testing and is not yet in use.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey, CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff. These items would replace the 3 Pain Management items on the HCAHPS Survey, which comprise the current Pain Management measure. CMS is currently evaluating data on the items as well as focus groups and interviews about the new pain items. A measure based on these items would be similar to the Pain Management composite measure currently used, which is based on the current HCAHPS Survey items The new measure, Communication about Pain During the Hospital Stay, focusses on communication about pain during the patient’s hospital stay, rather than on how well pain was controlled Different from the other measures in the HCAHPS Survey, this new measure uniquely focusses on communication about pain during the patient’s hospital stay The Communication about Pain During the Hospital Stay measure would replace the current Pain Management measure in the HCAHPS Survey, which is part of the IQR Program.  CMS is testing this new measure in a large-scale HCAHPS mode experiment.  CMS is currently collecting data for the Communication about Pain During the Hospital Stay measure from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment, January-March 2016.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The following questions (or a subset of questions) would replace the current Pain Management measure in the HCAHPS Survey with a new measure(s). The following items were tested in early 2016. CMS is currently analyzing the results, as well as discussing these potential new pain management items with focus groups and hospital staff. Multi-item measure (composite): DP1: “Before you left the hospital, did someone talk with you about how to treat pain after you got home?” DP2: “Before you left the hospital, did hospital staff give you a prescription for medicine to treat pain?” DP3: “Before giving you the prescription for pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Numerator: HCAHPS Survey measures are calculated using top-box scoring. The top-box refers to the percentage of patients who choose the most positive response option. For questions DP1 and DP3, the top-box numerator is number of respondents who answer “Yes.” Question DP2 is a screener item that serves to direct respondents to question DP3, if applicable. DP1: “Before you left the hospital, did someone talk with you about how to treat pain after you got home?” DP2: “Before you left the hospital, did hospital staff give you a prescription for medicine to treat pain?” DP3: “Before giving you the prescription for pain medicine, did hospital staff describe possible side effects in a way you could understand?”
  
  
• Denominator: The top box denominator is the number of respondents who answer at least one of the questions in this multi-item measure, that is, questions DP1 and DP3.
  
  
• Exclusions: Patients who respond “No” to question DP2 are excluded from question DP3. In addition, the following types of patients are excluded from the HCAHPS Survey: Patients younger than 18 years old at time of admission; Patients who did not have at least one overnight station in the hospital; Patients who were not admitted in the medical, surgical or maternity service lines; Patients who were not alive at time of discharge; “No-Publicity” patients – Patients who request that they not be contacted; Court/Law enforcement patients (i.e., prisoners); Patients with a foreign home address; Patients discharged to hospice care; Patients who are excluded because of state regulations; Patients discharged to nursing homes and skilled nursing facilities. For details, see HCAHPS Quality Assurance Guidelines, V11.0 at http://www.hcahpsonline.org/qaguidelines.aspx
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Survey
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is undergoing field testing and is intended to replace the Pain Management composite measure in the HCAHPS Survey in response to concerns expressed by physicians, hospitals and others about the current Pain Management items in the survey. The testing results should demonstrate that the measure is reliable and valid in IQR. In addition, the survey should be submitted to NQF for review and endorsement of this new composite measure addressing communication about treating pain post-discharge.
  • Impact on quality of care for patients:This measure can improve how hospital staff communicate with patients about pain they may experience after they are discharged from the hospital.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. The measure promotes effective communication and coordination of care and ensures that each person and family is engaged as partners in their care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. The scientific evidence-base and rationale for how this outcome measure is influenced by healthcare processes or structures was not provided. CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff in response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey.
  
  
• Does the measure address a quality challenge? Yes. The average top-box score for hospitals on the current Pain Management measure is 71.0%, indicating there is room for improvement.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. The proposed measure will replace the Pain Management composite measure currently in the HCAHPS Survey for IQR and VBP. The proposed measure focuses on communication about pain the patient may experience after discharge from the hospital.
  
  
• Can the measure can be feasibly reported? Yes. CMS is testing this measure on Q1’16 hospital discharges from 50 hospitals. Additionally, the previous measure has been reported since 2006.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is currently undergoing field testing on patients discharged from 50 hospitals Q1’16.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The measure is currently undergoing field testing and is not yet in use. There may be potential unintended consequences regarding question HP4, which could lead to increased prescription of pain medications “During this hospital stay, did you get medicine for pain?”.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
In response to concerns expressed by physicians, hospitals and others about the current Pain Management items on the HCAHPS Survey, CMS is considering new survey items for the HCAHPS Survey that focus on patients’ communication about pain with hospital staff. These items would replace the 3 Pain Management items on the HCAHPS Survey, which comprise the current Pain Management measure. CMS is currently evaluating data on the items as well as focus groups and interviews about the news pain items. A measure based on these items would be similar to the Pain Management composite measure currently used, which is based on the current HCAHPS Survey items The new measure, Communication about Treating Pain Post-Discharge, focusses on communication about pain that the patient may experience after discharge from the hospital, rather than on how well pain was controlled Different from the other measures in the HCAHPS Survey, this new measure uniquely focusses on communication about pain that the patient may experience after discharge from the hospital The Communication about Treating Pain Post-Discharge measure would replace the current Pain Management measure in the HCAHPS Survey, which is part of the IQR Program.  CMS is testing this new measure in a large-scale HCAHPS mode experiment.  CMS is currently collecting data for the Communication about Treating Pain Post-Discharge measure from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment, January-March 2016.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure assesses the percentage of patients admitted to an inpatient psychiatric facility who were screened and evaluated for opioid use disorder.
  
  
• Numerator: The number of patients who were evaluated for opioid use with a urine drug screen test, a clinical review of the Prescription Drug Monitoring Program (PDMP) database, and a clinical assessment for the presence or absence of opioid use disorder. 1) Urine drug screen: Collection of a urine specimen for a urine drug screen within 24 hours of admission to the IPF or 24 hours prior to admission if data are available (e.g., emergency department visit). This component is not required for patients transferred from an inpatient facility because opioids may have been administered during an inpatient stay. 2) Prescription Drug Monitoring Database (PDMP): For states in which a PDMP database is available, documentation of a clinical review of the PDMP database. This component is not required for patients less than 18 years of age which are not included in the PDMPs. 3) Clinical Assessment: Documentation of the presence or absence of opioid use disorder. When opioid use disorder is identified, documentation of the severity of the condition as mild, moderate, or severe.
  
  
• Denominator: All discharges from an IPF with a continuous stay in the IPF of at least 24 hours.
  
  
• Exclusions: There are no denominator exclusions for this measure.
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Record review
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is fully developed, specified and undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting. This measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages inpatient psychiatric facilities to screen patients for an opioid use disorder.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. This measure is based on the CDC Guideline for Prescribing Opioids for Chronic Pain that provides recommendations for primary care clinicians on prescribing opioids for chronic pain outside of active cancer treatment, palliative care, and end-of-life care.
  
  
• Does the measure address a quality challenge? Yes. A preliminary analysis of 365 patients prescribed an opioid during the IPF admission from one test site found that only 64.7% of these patients had received a urine drug screen, which indicates that there is room for improvement. Further measure testing will be conducted in additional facilities to verify these findings.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure excludes patients that have been clinically deemed to be at no risk for having an opioid use disorder by a clinician. This exclusion reduces the burden of abstracting this information for all patients admitted to an inpatient psychiatric facility.
  
  
• Can the measure can be feasibly reported? Yes. The measure can be chart abstracted from a sample of hospital records.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is fully developed and specified. The measure is currently undergoing testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This a new measure that is currently not in use.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Opioid use disorder and opioid overdose are latent risks with the use of opioid medications. These adverse drug events (ADE) are potentially preventable and current policy and literature has made a call to make a continuous effort to reduce morbidity and mortality secondary to opioids, which has achieved epidemic levels.[1-4] Opioid related ADEs including opioid use disorder (OUD) have led to an increase of deaths. Between 1999 to 2014, more than 165,000 persons died from overdose related to opioid use in the United States.[5, 6] Monitoring for any indicators of substance use allows clinicians to prevent or treat OUD and prevent related ADEs. The Diagnostic and Statistical Manual of Mental Disorders noted that “routine urine toxicology test results are often positive for opioid drugs in individuals with opioid use disorder.”[7] Urine drug testing has been consistently recommended by clinical guidelines for monitoring patients on opioid therapy and regarded as a useful marker for evaluating compliance to the therapy and detecting the misuse of prescribed medications or use of illicit agents.[1, 8, 9] Studies have suggested that results from the urine drug testing are informative in making clinical assessment on aberrant drug-taking behaviors and determining the need for clinical referral to specialists.[10, 11] Monitoring adherence to the plan of care is also recommended by guidelines to ensure the effectiveness and safety of the prescribed treatment.[1, 7] The prescription drug monitoring program (PDMP) is a central data repository that collects statewide data on the controlled substance prescriptions and can be a useful tool to monitor prescription drug utilization.[12] Citations: 1. Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain. MMWR Recomm Rep 2016;65(1):1-49. Available at: https://www.cdc.gov/mmwr/volumes/65/rr/rr6501e1.htm. 2. Liu Y, Logan JE, Paulozzi LJ, Zhang K, Jones CM. Potential misuse and inappropriate prescription practices involving opioid analgesics. Am J Manag Care. 2013;19(8):648-65. 3. Mack KA, Zhang K, Paulozzi L, Jones C. Prescription practices involving opioid analgesics among Americans with Medicaid, 2010. J Health Care Poor Underserved. 2015;26(1):182-98. 4. Bohnert AS, Valenstein M, Bair MJ, et al. Association between opioid prescribing patterns and opioid overdose-related deaths. JAMA. 2011;305(13):1315-21. 5. Centers for Disease Control and Prevention (CDC). Wide-ranging online data for epidemiologic research (WONDER). Atlanta, GA: CDC, National Center for Health Statistics; 2016. Available at: http://wonder.cdc.gov/mcd.html. 6. Frenk SM, Porter KS, Paulozzi LJ. Prescription opioid analgesic use among adults: United States, 1999–2012. NCHS data brief, no 189. Hyattsville, MD: National Center for Health Statistics. 2015. 7. American Psychiatric Association. Substance use disorders. In: Diagnostic and Statistical Manual of Mental Disorders, 5th ed. Arlington, VA: American Psychiatric Association; 2013. 8. Chou R, Fanciullo GJ, Fine PG, et al. Clinical guidelines for the use of chronic opioid therapy in chronic noncancer pain. J Pain. Feb 2009;10(2):113-130. 9. Christo PJ, Manchikanti L, Ruan X, et al. Urine drug testing in chronic pain. Pain Physician. 2011;14:123-143. 10. Katz NP, Sherburne S, Beach M, et al. Behavioral monitoring and urine toxicology testing in patients receiving long-term opioid therapy. Anesth Analg. 2003;97:1096-1102. 11. Gilbert JW, Wheeler GR, Mick GE, et al. Urine drug testing in the treatment of chronic noncancer pain in a Kentucky private neuroscience practice: the potential effect of Medicare benefit changes in Kentucky. Pain Physician. 2010;13:187-194. 12. Sehgal N, Manchikanti L, Smith HS. Prescription opioid abuse in chronic pain: a review of opioid abuse predictors and strategies to curb opioid abuse. Pain Physician. 2012;15:eS67-ES92.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: **As of 12/2 testing for this measure has been completed**** This measure assesses whether psychiatric patients admitted to an inpatient psychiatric facility (IPF) for major depressive disorder (MDD), schizophrenia, or bipolar disorder (BD) were dispensed a prescription for evidence-based medication within 30 days of discharge. The performance period for the measure is two years.
  
  
• Numerator: The numerator for this measure includes: 1. Discharges with a principal diagnosis of major depressive disorder (MDD) in the denominator population for which patients were dispensed evidence-based medication within 30 days of discharge 2. Discharges with a principal diagnosis schizophrenia in the denominator population for which patients were dispensed evidence-based medication within 30 days of discharge 3. Discharges with a principal diagnosis of bipolar disorder in the denominator population for which patients were dispensed evidence-based medication within 30 days of discharge
  
  
• Denominator: The denominator for this measure includes admissions for patients: 1. Discharged from an IPF with a principal diagnosis of MDD, schizophrenia, or bipolar disorder 2. 18 years of age or older 3. Enrolled in Medicare fee-for-service Part A during the index admission and Parts B and D at least 30-days post-discharge 4. Discharged alive and alive during the follow-up period 5. Discharged to home
  
  
• Exclusions: This measure excludes index admissions for patients: 1. Who received electroconvulsive therapy (ECT)during the inpatient stay 2. Who received transcranial magnetic stimulation (TMS) during the inpatient stay 3. Who were pregnant during the inpatient stay 4. Who had a secondary diagnosis of delirium 5. Who had schizophrenia with a secondary diagnosis of dementia
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Claims, Prescription Drug Event Data Elements
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is fully developed, specified and undergoing testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting. The measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages inpatient psychiatric facilities to ensure that patients with major depressive disorder (MDD), schizophrenia, or bipolar disorder (BD) are dispensed a prescription for evidence-based medication within 30 days of discharge.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on ensuring that each person and family is engaged as partners in their care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. IPFs can implement a variety of processes to improve medication continuation during the transition from inpatient to outpatient care. Examples that have been shown to increase medication compliance and prevent negative outcomes associated with nonadherence include patient education, enhanced therapeutic relationships, shared decision-making, and text-message reminders, with emphasis on multidimensional approaches.
  
  
• Does the measure address a quality challenge? Yes . An empirical analysis using 2013–2014 Medicare claims data, indicated that across 1,694 IPFs, evidence-based medication continuation rates within 30 days of IPF discharge vary across facilities. The median rate of medication continuation was 79% with a range of 66% in the 10th percentile to 88% in the 90th percentile. These data show variations in performance and indicate ample opportunity for improvement.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure uses claims and prescription drug event data elements and is not duplicative of an existing measure.
  
  
• Can the measure can be feasibly reported? Yes. The measure is based on Medicare claims data which includes all information necessary to identify the cohort and calculate the numerator
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is fully developed and specified. The measure is currently undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This is a new measure that is not currently in use.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
The medications that constitute the numerator are evidence-based with demonstrated efficacy and safety for MDD, schizophrenia, and bipolar disorder. The continued use of effective medication is implicit and underscored by a 2010 meta-analysis of 54 double-blind placebo-controlled relapse prevention studies which found that, among patients with depression who initially responded to drug therapy, continuation of antidepressants significantly reduced relapse (odds ratios 0.35; 95% CI 0.32–0.39), and this reduction was not affected by patient age, drug class, depression subtype, or treatment duration (Glue, Donovan, Kolluri, Emir, 2010). Furthermore, among patients with bipolar disorder, medication adherence was significantly associated with the course of illness (Sylvia, 2014). Among patients with schizophrenia, those who were “good compliers” according to the Medication Adherence Rating Scale had better outcomes in terms of rehospitalization rates and medication maintenance (Jaeger, Pfiffner, Weiser, et al., 2012). A review of the medication adherence literature found that as patient medication adherence increases, the average annual healthcare spending levels decrease (Braithwaite, Shirkhorshidian, Jones, Johnsrud, 2013; Roebuck, Liberman, Gemmill-Toyama, Brennan, 2011). This measure focuses on medication continuation rather than adherence because IPFs can implement a variety of processes to improve medication continuation during the transition from inpatient to outpatient care. Examples that have been shown to increase medication compliance and prevent negative outcomes associated with nonadherence include patient education, enhanced therapeutic relationships, shared decision-making, and text-message reminders, with emphasis on multidimensional approaches (Douaihy, Kelly, Sullivan, 2013; Haddad, Brain, Scott, 2014; Hung, 2014; Kasckow and Zisook, 2008; Lanouette, Folsom, Sciolla, Jeste, 2009; Mitchell, 2007; Sylvia, Hay, Ostacher, et al., 2013). Citations: * Braithwaite, S., Shirkhorshidian, I., Jones, K., & Johnsrud, M. (2013). The role of medication adherence in the US healthcare system. Retrieved from http://avalere.com/research/docs/20130612_NACDS_Medication_Adherence.pdf * Douaihy, A. B., Kelly, T. M., & Sullivan, C. (2013). Medications for substance use disorders. Soc Work Public Health, 28(3-4), 264-278. doi: 10.1080/19371918.2013.759031 * Glue, P., Donovan, M. R., Kolluri, S., & Emir, B. (2010). Meta-analysis of relapse prevention antidepressant trials in depressive disorders. Australian and New Zealand Journal of Psychiatry, 44(8), 697-705. doi: 10.3109/00048671003705441 * Haddad, P. M., Brain, C., & Scott, J. (2014). Nonadherence with antipsychotic medication in schizophrenia: challenges and management strategies. Patient Relat Outcome Meas, 5, 43-62. doi: 10.2147/PROM.S42735 * Jaeger, S., Pfiffner, C., Weiser, P., Kilian, R., Becker, T., Langle, G., . . . Steinert, T. (2012). Adherence styles of schizophrenia patients identified by a latent class analysis of the Medication Adherence Rating Scale (MARS): a six-month follow-up study. Psychiatry Research, 200(2-3), 83-88. doi: 10.1016/j.psychres.2012.03.033 * Kasckow, J. W., & Zisook, S. (2008). Co-occurring depressive symptoms in the older patient with schizophrenia. Drugs and Aging, 25(8), 631-647. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18665657 * Lanouette, N. M., Folsom, D. P., Sciolla, A., & Jeste, D. V. (2009). Psychotropic medication nonadherence among United States Latinos: a comprehensive literature review. Psychiatric Services, 60(2), 157-174. doi: 10.1176/appi.ps.60.2.157 * Roebuck, M. C., Liberman, J. N., Gemmill-Toyama, M., & Brennan, T. A. (2011). Medication adherence leads to lower health care use and costs despite increased drug spending. Health Affairs, 30(1), 91-99. doi: 10.1377/hlthaff.2009.1087 * Sylvia, L. G., Hay, A., Ostacher, M. J., Miklowitz, D. J., Nierenberg, A. A., Thase, M. E., . . . Perlis, R. H. (2013). Association between therapeutic alliance, care satisfaction, and pharmacological adherence in bipolar disorder. Journal of Clinical Psychopharmacology, 33(3), 343-350. doi: 10.1097/JCP.0b013e3182900c6f * Sylvia, L. G., Reilly-Harrington, N. A., Leon, A. C., Kansky, C. I., Calabrese, J. R., Bowden, C. L., . . . Nierenberg, A. A. (2014). Medication adherence in a comparative effectiveness trial for bipolar disorder. Acta Psychiatrica Scandinavica, 129(5), 359-365. doi: 10.1111/acps.12202

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: **As of 12/2 testing for this measure has been completed**** ****Changed from requiring reconciliation within 24 hours to requiring reconciliation within 48 hours as of 12/1/16**** This measure assesses the average completeness of medication reconciliations conducted within 24 hours of admission to an inpatient facility.
  
  
• Numerator: This measure does not have a traditional numerator. The numerator is the average completeness of three components of the medication reconciliation process. 1) Comprehensive prior to admission (PTA) medication information gathering and documentation• The medical record contains a designated Medication Reconciliation Form/Area that contains a prior to admission (PTA) medication listAt least one patient source was referenced to generate the PTA medication list or the patient was unable to provide information on their medications • At least one health system source was referenced to generate the PTA medication list • All medications in the History & Physical (H&P) or equivalent document are listed in the PTA medication list • When there are no medications on the PTA medication list, the Medication Reconciliation Form/Area should be reviewed by a licensed practitioner within 24 hours of admission. When there are no medications on the PTA medication list, Components 2 and 3 do not apply. 2) Completeness of critical PTA medication information: • Name • Dose • Route • Frequency • Indication • Last time taken 3) Reconciliation action for each PTA medication • Documentation of reconciliation action to continue, discontinue, or modify the medication • Reconciliation action documented within 24 hours of admission
  
  
• Denominator: Admissions to an inpatient facility with a duration of at least 24 hours.
  
  
• Exclusions: Admissions for patients transferred from another IPF or from an acute care hospital.
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Paper medical record, Record review
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit Prior to Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is fully developed, specified and undergoing field testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting. This measure should be submitted to NQF for review and endorsement.
  • Impact on quality of care for patients:This measure encourages inpatient psychiatric facilities to complete adequate medication reconciliation within 24 hours of admission.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on making care safer by reducing harm caused in the delivery of care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. This measure is based on the Joint Commission National Patient Safety Guidelines (2015) for hospitals with regard to medication reconciliation and the American Psychiatric Association’s recommendation that (APA) the initial psychiatric evaluation of a patient include a review of past treatment, including type, duration, and where applicable, doses, side effects, and adherence to past and current pharmacological and non-pharmacological psychiatric treatment [Grade 1C*] (American Psychiatric Association, 2016). The evaluation should also assess all other medications that the patient is currently taking and assess any substance use (e.g., tobacco, alcohol, and other substances and any misuse of prescribed or over-the-counter (OTC) products or supplement) [Grade 1C*].
  
  
• Does the measure address a quality challenge? Yes. Hospital medication records for admitted patients are often incomplete and contain clinically important errors. A systematic review of 22 studies identified that errors in prescription medication histories occurred at hospital admission in up to 67% of cases and that clinically significant errors ranged from 11%"“59% of all errors (Cornish, Knowles, Marchesano, et al., 2005). Of the studies identified, one was specific to the inpatient psychiatric setting and identified 48% of patients with ≥ 1 error in the medication history. A more recent study in a 172-bed inpatient psychiatric facility in New England identified a rate of ADEs that is one-third higher than in acute care hospitals (10 per 1,000 patient-days) and a serious error rate of 6.3 per 1,000 patient-days (Rothschild, Mann, Keohane, et al., 2007). Data on performance variation are not available.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This process measure requires medical record review. There are 6 NQF endorsed measure that address Medication Reconciliation, but are not competing measures, as this measure focuses on the medication reconciliation being conducted within 24 hours of admission and captures the broadest audience specific to IPFs. No medication reconcilation measures that capture the specific aspects of this measure exist within this program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is based on data abstracted from the medical record. The measure specifications will include a validated data abstraction tool.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is fully developed and specified. The measure is currently undergoing testing. The testing results should demonstrate reliability and validity at the facility level in the hospital setting.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. This a new measure that is currently not in use.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
A systematic review published in 2012 examined 26 controlled studies related to hospital-based medication reconciliation practices (Mueller, Sponsler, Kripalani, Schnipper, 2012). The studies “consistently demonstrated a reduction in medication discrepancies (17/17 studies), potential adverse drug events (5/6 studies), and adverse drug events (2/3 studies).” Of the 26 studies identified, six were rated as good quality; five as fair; and 15 as poor, using the United States Preventive Services Task Force (USPSTF) criteria. Although the heterogeneity of the study designs makes it difficult to identify the key elements of successful interventions, accurate pre-admission medication lists are critical to the medication reconciliation process as identified in the studies. Pre-admission medication reconciliation is further supported by two recent studies (MATCH and MARQUIS), which noted that most of the medication discrepancies or potential adverse drug events identified were the result of errors in obtaining the medication history (Gleason, McDaniel, Feinglass, et al., 2010; Salanitro, Kripalani, Resnic, et al., 2013). Five of the elements proposed by this measure concept are aligned with interventions from MATCH, MARQUIS, and the Joint Commission (2015). Specific to the IPF, a study indicated that 48% of patients had = 1 errors in their medication history and that the rate of ADEs is one-third higher in IPFs than in acute care hospitals (Cornish, Knowles, Marchesano, et al., 2005). Citations: * Cornish, P. L., Knowles, S. R., Marchesano, R., Tam, V., Shadowitz, S., Juurlink, D. N., & Etchells, E. E. (2005). Unintended medication discrepancies at the time of hospital admission. Archives of Internal Medicine, 165(4), 424-429. doi:10.1001/archinte.165.4.424 * Gleason, K. M., McDaniel, M. R., Feinglass, J., Baker, D. W., Lindquist, L., Liss, D., & Noskin, G. A. (2010). Results of the Medications at Transitions and Clinical Handoffs (MATCH) study: an analysis of medication reconciliation errors and risk factors at hospital admission. Journal of General Internal Medicine, 25(5), 441-447. doi:10.1007/s11606-010-1256-6 * Mueller, S. K., Sponsler, K. C., Kripalani, S., & Schnipper, J. L. (2012). Hospital-based medication reconciliation practices: a systematic review. Archives of Internal Medicine, 172(14), 1057-1069. doi: 10.1001/archinternmed.2012.2246 * Salanitro, A. H., Kripalani, S., Resnic, J., Mueller, S. K., Wetterneck, T. B., Haynes, K. T., . . . Schnipper, J. L. (2013). Rationale and design of the Multi-center Medication Reconciliation Quality Improvement Study (MARQUIS). BMC Health Services Research, 13, 230. doi:10.1186/1472-6963-13-230 * The Joint Commission. (2015). National Patient Safety Goals Effective January 1, 2015: Hospital Accreditation Program. Retrieved from http://www.jointcommission.org/assets/1/6/2015_NPSG_HAP.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The percentage of non-metastatic prostate cancer patients with a clinically-significant change in bowel function from baseline to follow-up, as measured by the validated Expanded Prostate Inventory Composite (EPIC) patient-reported outcome(EPIC-26 or EPIC-50).
  
  
• Numerator: Patients with a clinically-significant change in bowel function from baseline to follow-up. Numerator definitions: Bowel function is measured as the Bowel function domain score via the EPIC-26 or EPIC-50 at baseline (0-6 months prior to the start of surgery or radiation at the reporting facility) AND follow up (1 year (± 3 months) after the date of surgery or the start of a radiation regimen at the reporting facility). Clinically significant change is defined in Skolarus et al., 2015.
  
  
• Denominator: All non-metastatic prostate cancer patients undergoing radiation or surgical treatment for prostate cancer at the reporting facility. Denominator definitions: ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N.
  
  
• Exclusions: Any patients that are unable to complete a baseline and follow-up survey due to death, language barrier, or physical or mental incapacity Patients with progression to metastatic disease during the follow up period Patients who stop treatment at or leave the reporting facility during the follow up period
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Skolarus TA, Dunn RL, Sanda MG, Chang P, Greenfield TK, Litwin MS, Wei JT; PROSTQA Consortium. Minimally important difference for the Expanded Prostate Cancer Index Composite Short Form. Urology. 2015 Jan;85(1):101-5. doi: 10.1016/j.urology.2014.08.044. PubMed PMID: 25530370; PubMed Central PMCID: PMC4274392. Martin NE, Massey L, Stowell C, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. European Urology. 2015 Mar; 67(3): 460-467. Available at http://europeanurology.com/article/S0302-2838(14)00845-8/fulltext/defining-a-standard-set-of-patient-centered-outcomes-for-men-with-localized-prostate-cancer.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The percentage of non-metastatic prostate cancer patients with a clinically-significant change in sexual function from baseline to follow-up, as measured by the validated Expanded Prostate Inventory Composite (EPIC) patient-reported outcome).
  
  
• Numerator: Patients with a clinically-significant change in sexual function from baseline to follow-up. Numerator definitions: Sexual function is measured as the Sexual function domain score via the EPIC-26 or EPIC-50 at baseline (0-6 months prior to the start of surgery or radiation at the reporting facility) AND follow up (1 year (± 3 months) after the date of surgery or the start of a radiation regimen at the reporting facility). Clinically significant change is defined in Skolarus et al., 2015.
  
  
• Denominator: All non-metastatic prostate cancer patients undergoing radiation or surgical treatment for prostate cancer at the reporting facility. Denominator definitions: ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N.
  
  
• Exclusions: Any patients that are unable to complete a baseline and follow-up survey due to death, language barrier, or physical or mental incapacity Patients with progression to metastatic disease during the follow up period Patients who stop treatment at or leave the reporting facility during the follow up period
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Skolarus TA, Dunn RL, Sanda MG, Chang P, Greenfield TK, Litwin MS, Wei JT; PROSTQA Consortium. Minimally important difference for the Expanded Prostate Cancer Index Composite Short Form. Urology. 2015 Jan;85(1):101-5. doi: 10.1016/j.urology.2014.08.044. PubMed PMID: 25530370; PubMed Central PMCID: PMC4274392. Martin NE, Massey L, Stowell C, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. European Urology. 2015 Mar; 67(3): 460-467. Available at http://europeanurology.com/article/S0302-2838(14)00845-8/fulltext/defining-a-standard-set-of-patient-centered-outcomes-for-men-with-localized-prostate-cancer.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The percentage of non-metastatic prostate cancer patients with a clinically-significant change in urinary frequency, obstruction, and/or irritation from baseline to follow-up, as measured by the validated Expanded Prostate Inventory Composite (EPIC) patient-reported outcome).
  
  
• Numerator: Patients with a clinically-significant change in urinary frequency, obstruction, and/or irritation from baseline to follow-up Numerator definitions: Urinary frequency, obstruction, and/or irritation is measured as the Urinary frequency domain score via the EPIC-26 or EPIC-50 at baseline (0-6 months prior to the start of surgery or radiation at the reporting facility) AND follow up (1 year (± 3 months) after the date of surgery or the start of a radiation regimen at the reporting facility) Clinically significant change is defined in Skolarus et al., 2015.
  
  
• Denominator: All non-metastatic prostate cancer patients undergoing radiation or surgical treatment for prostate cancer at the reporting facility. Denominator definitions: ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N.
  
  
• Exclusions: Any patients that are unable to complete a baseline and follow-up survey due to death, language barrier, or physical or mental incapacity Patients with progression to metastatic disease during the follow up period Patients who stop treatment at or leave the reporting facility during the follow up period
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Skolarus TA, Dunn RL, Sanda MG, Chang P, Greenfield TK, Litwin MS, Wei JT; PROSTQA Consortium. Minimally important difference for the Expanded Prostate Cancer Index Composite Short Form. Urology. 2015 Jan;85(1):101-5. doi: 10.1016/j.urology.2014.08.044. PubMed PMID: 25530370; PubMed Central PMCID: PMC4274392. Martin NE, Massey L, Stowell C, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. European Urology. 2015 Mar; 67(3): 460-467. Available at http://europeanurology.com/article/S0302-2838(14)00845-8/fulltext/defining-a-standard-set-of-patient-centered-outcomes-for-men-with-localized-prostate-cancer.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The percentage of non-metastatic prostate cancer patients with a clinically-significant change in urinary incontinence from baseline to follow-up, as measured by the validated Expanded Prostate Inventory Composite (EPIC) patient-reported outcome).
  
  
• Numerator: Patients with a clinically-significant change in urinary incontinence from baseline to follow-up. Numerator definitions: Urinary incontinence is measured as the Urinary function domain score via the EPIC-26 or EPIC-50 at baseline (0-6 months prior to the start of surgery or radiation at the reporting facility) AND follow up (1 year (± 3 months) after the date of surgery or the start of a radiation regimen at the reporting facility) Clinically significant change is defined in Skolarus et al., 2015.
  
  
• Denominator: All non-metastatic prostate cancer patients undergoing radiation or surgical treatment for prostate cancer at the reporting facility. Denominator definitions: ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N.
  
  
• Exclusions: Any patients that are unable to complete a baseline and follow-up survey due to death, language barrier, or physical or mental incapacity Patients with progression to metastatic disease during the follow up period Patients who stop treatment at or leave the reporting facility during the follow up period
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Skolarus TA, Dunn RL, Sanda MG, Chang P, Greenfield TK, Litwin MS, Wei JT; PROSTQA Consortium. Minimally important difference for the Expanded Prostate Cancer Index Composite Short Form. Urology. 2015 Jan;85(1):101-5. doi: 10.1016/j.urology.2014.08.044. PubMed PMID: 25530370; PubMed Central PMCID: PMC4274392. Martin NE, Massey L, Stowell C, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. European Urology. 2015 Mar; 67(3): 460-467. Available at http://europeanurology.com/article/S0302-2838(14)00845-8/fulltext/defining-a-standard-set-of-patient-centered-outcomes-for-men-with-localized-prostate-cancer.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The percentage of non-metastatic prostate cancer patients with a clinically-significant change in vitality from baseline to follow-up, as measured by the validated Expanded Prostate Inventory Composite (EPIC) patient-reported outcome (EPIC-26 or EPIC-50).
  
  
• Numerator: Patients with a clinically-significant change in vitality from baseline to follow-up. Numerator definitions: Vitality is measured as the Vitality/Hormonal domain score via the EPIC-26 or EPIC-50 at baseline (0-6 months prior to the start of surgery or radiation at the reporting facility) AND follow up (1 year (± 3 months) after the date of surgery or the start of a radiation regimen at the reporting facility) Clinically significant change is defined in Skolarus et al., 2015.
  
  
• Denominator: All non-metastatic prostate cancer patients undergoing radiation or surgical treatment for prostate cancer at the reporting facility. Denominator definitions: ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N.
  
  
• Exclusions: Any patients that are unable to complete a baseline and follow-up survey due to death, language barrier, or physical or mental incapacity Patients with progression to metastatic disease during the follow up period Patients who stop treatment at or leave the reporting facility during the follow up period
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Electronic Health Record
  
  
• Measure Type: Outcome
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: This measure is no longer under consideration
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been removed from consideration]
  • Impact on quality of care for patients:This measure has been removed from consideration]
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? . This measure has been removed from consideration]
  
  
• Measure development status: Field Testing
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  

Rationale for measure provided by HHS
Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Skolarus TA, Dunn RL, Sanda MG, Chang P, Greenfield TK, Litwin MS, Wei JT; PROSTQA Consortium. Minimally important difference for the Expanded Prostate Cancer Index Composite Short Form. Urology. 2015 Jan;85(1):101-5. doi: 10.1016/j.urology.2014.08.044. PubMed PMID: 25530370; PubMed Central PMCID: PMC4274392. Martin NE, Massey L, Stowell C, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. European Urology. 2015 Mar; 67(3): 460-467. Available at http://europeanurology.com/article/S0302-2838(14)00845-8/fulltext/defining-a-standard-set-of-patient-centered-outcomes-for-men-with-localized-prostate-cancer.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Use of a validated patient-reported outcome (PRO) instrument to measure functional status in adult, non-metastatic prostate cancer patients during the 12-month measurement period.
  
  
• Numerator: Facilities will respond to the following questions on an annual basis: (A) Does your facility measure functional status outcomes in adult patients with non-metastatic prostate cancer using a validated survey instrument and a standardized implementation? (B) What is the name of the survey instrument administered? (C) Which of the following functional status domains are measured by the survey instrument? (select all that apply): Urinary function; Urinary Frequency, Obstruction, and/or Irritation; Sexual function; Bowel irritation; and, Vitality. (D) According to your implementation plan, how frequently is the survey administered to eligible patients? (E) Does your facility report survey results to a centralized location? (select one of the following options) National repository; State-based repository; Health system repository; Other repository; or, Do not report the data outside the facility.) Numerator definitions: Adult = > 18 years at time of diagnosis ‘Non-metastatic’ is defined as AJCC 7th edition M0 (non-M1) cancer stage, regardless of T and N. Validated PRO instrument is defined as an instrument that has undergone psychometric testing that demonstrates the instrument reflects what it is supposed to measure Any PRO instrument validated for use to measure functional status in non-metastatic prostate cancer patients meets the numerator of this measure.
  
  
• Denominator: Number of institutions responding ‘yes’ to (A) Does your facility measure functional status outcomes in adult patients with non-metastatic prostate cancer using a validated survey instrument and a standardized implementation.
  
  
• Exclusions: Facilities that do not see at least 11 patients with a diagnosis of non-metastatic prostate cancer during the 12-month reporting period.
  
  
• HHS NQS Priority: Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Survey
  
  
• Measure Type: Structure
  
  
• Steward: The University of Texas MD Anderson Cancer Center
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:It is unclear if the value of this measure to patients/consumers outweighs the burden of implementation. There is limited information regarding how the measure can be operationalized and the measure is not fully specified and tested.
  • Impact on quality of care for patients:This measure would encourage facilities measure functional status in adult patients with non-metastatic prostate cancer using a validated survey instrument.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This focuses on ensuring that each person and family is engaged as partners in their care and promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? No. This is a structural measure related to measurement of PRO utilization. Structural measures require a strong scientific evidence-base to demonstrate that when implemented can lead to the desired outcomes. No evidence was provided to demonstrate that implementation of this measure would lead to improved outcomes for patient with prostate cancer.
  
  
• Does the measure address a quality challenge? No. No information was provided indicating that there is a quality issue in PRO utilization in in non-metastatic prostate cancer patients. However, the developer states that through the proposed survey on use of a validated PRO instrument to measure functional status and quality of life in non-metastatic prostate cancer patients, we will begin to understand how facilities are using PROs to measure and improve functional status and quality of life for these patients.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? No. It is unclear if the value of this measure to patients/consumers outweighs the burden of implementation.
  
  
• Can the measure can be feasibly reported? No. There is limited information regarding how the measure can be operationalized, though information is provided stating that participating facilities could submit data via a web portal (e.g., via QualityNet). The measure is not fully specified and specifications do not use data in structured data fields.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. The measure is undergoing field testing. This measure has not been submitted for NQF endorsemement.
  
  
• Measure development status: Field Testing
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? No. The developers do not anticipate any unintended consequences as a result of implementing this measure. However, it is unclear if the value of this measure to patients/consumers outweighs the burden of implementation.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Neil E. Martin, Laura Massey, Caleb Stowell, et al. Defining a Standard Set of Patient-centered Outcomes for Men with Localized Prostate Cancer. Eur Urol 2015;67:460–7 Stover A, Irwin DE, Chen RC, Chera BS, Mayer DK, Muss HB, Rosenstein DL, Shea TC, Wood WA, Lyons JC, Reeve BB; Integrating Patient-Reported Outcome Measures into Routine Cancer Care: Cancer Patients’ and Clinicians’ Perceptions of Acceptability and Value. eGEMS. 2015 Oct. 3(1): 1169. Available at: http://repository.edm-forum.org/egems/vol3/iss1/17 Wei JT, Dunn RL, Litwin MS, Sandler HM, Sanda MG. "Development and Validation of the Expanded Prostate Cancer Index Composite (EPIC) for Comprehensive Assessment of Health-Related Quality of Life in Men with Prostate Cancer", Urology. 56: 899-905, 2000. Wei JT, Dunn RL, Sandler HM, McLaughlin PW, Montie JE, Litwin MS, Nyquist L, Sanda MG. Comprehensive comparison of health-related quality of life after contemporary therapies for localized prostate cancer ", Journal of Clinical Oncology. 20(2): 557-66, 2002. Hollenbeck BK, Dunn RL, Wei JT, McLaughlin PW, Han M, Sanda MG. Neoadjuvant hormonal therapy and older age are associated with adverse sexual health-related quality-of-life outcome after prostate brachytherapy ", Urology. 59: 480-4, 2002. Hollenbeck BK, Dunn RL, Wei JT, Montie JE, Sanda MG. Determinants of Long-Term Sexual HRQOL After Radical Prostatectomy Measured by a Validated Instrument", Journal of Urology. 169: 1453-7, 2003. Van Andel G, Bottomley A, Fossa SD, Efficace F, Coens C, Guerif S, Kynaston H, Gontero P, Thalmann G, Akdas A, D’Haese S, Aronson NK An international field study of the EORTC QLQ-PR25: a questionnaire for assessing the health-related quality of life of patients with prostate cancer. Eur J Cancer. 2008 Nov;44(16):2418-24. doi: 10.1016/j.ejca.2008.07.030. Epub 2008 Sep 5. Sonn GA, Sadetsky N, Presti JC, Litwin M. Differing perceptions of quality of life in patients with prostate cancer and their doctors. J Urol 2009; 182: 2296–2302. Justice AC, Rabeneck L, Hays RD, Wu AW, Bozzette SA. Sensitivity, specificity, reliability, and clinical validity of provider-reported symptoms: a comparison with self-reported symptoms. J Acquir Immune Defic Syndr 1999; 21: 126–133.

Measure Specifications

• NQF Number (if applicable): 216
  
  
• Description: Proportion of patients who died from cancer admitted to hospice for less than 3 days
  
  
• Numerator: Patients who died from cancer and spent fewer than three days in hospice.
  
  
• Denominator: Patients who died from cancer who were admitted to hospice
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Registry
  
  
• Measure Type: Intermediate Outcome
  
  
• Steward: American Society of Clinical Oncology
  
  
• Endorsement Status: Endorsed
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure is not specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The measure should be specified, tested and NQF endorsed at the facility level in the hospital setting for the PPS-Exempt Cancer Hospital Quality Reporting Program.
  • Impact on quality of care for patients:This measure provides the proportion of patients who died from cancer and were admitted to hospice for less than 3 days.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Patients enrolled in hospice experience increased survival times along with a reduction in resource use such as aggressive end of life care and hospital admissions; benefits that increased the longer patients are enrolled in hospice (Lee, 2015; Langton, 2014).
  
  
• Does the measure address a quality challenge? Yes. This measure was submitted to the NQF Palliative Care and End-of-Life project. The developer provided group/practice level performance data from the ASCO Quality Oncology PracticeInitiative registry (QOPI) for 2013-2015. The median performance score was 12.97 in 2013, 14.64 in 2014 and 15.38 in 2015.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure is not duplicative of existing measures in the portfolio.
  
  
• Can the measure can be feasibly reported? Yes. This measure is currently used in the Merit-Based Incentive Payment Program, and has been since 2015. In addition, the measure is currently in use for quality improvement with benchmarking in the QOPI® registry. Finally, this measure has been reported to CMS by the registry as a PQRS Qualified Clinical Data Registry.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is specified at the group/clinician level and tested in the ambulatory care setting. The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The appeals period is scheduled to close November 25, 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The developers do not anticipate any unintended consequences as a result of implementing this measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Langton, J. M., B. Blanch, et al. (2014). "Retrospective studies of end-of-life resource utilization and costs in cancer care using health administrative data: a systematic review." Palliat Med 28(10): 1167-1196. Lee, Y. J., J. H. Yang, et al. (2015). "Association between the duration of palliative care service and survival in terminal cancer patients." Support Care Cancer 23(4): 1057-1062. O´Connor, T. L., N. Ngamphaiboon, et al. (2015). "Hospice utilization and end-of-life care in metastatic breast cancer patients at a comprehensive cancer center." J Palliat Med 18(1): 50-55.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Palliative and End-of-Life Care Project 2015-2016
  
  
• Review for Importance: 1a. Evidence: Previous Evidence Evaluation Accepted 1b. Performance Gap: H-14; M-7; L-0; I-0; Rationale:• For the 2012 endorsement evaluation, the developers cited two studies indicating hospice admission did not have detrimental effect on survival among elderly patients with lung cancer and was associated with bereaved family members reporting a) higher quality of end-of-life care, b) no unmet need for help with anxiety or depression, and c) death in the decedent’s died in preferred location. The developer also cited a 2003 expert consensus paper identifying short hospice enrollment as an indicator of quality of end-of-life cancer care. • For the current evaluation, developers updated the evidence by referencing: a 2013 Cochrane Collaborative systematic review that evaluated the impact of home-based palliative care services on several patient and caregiver outcomes, which found that for patients with cancer, home-based palliative care services increases the chance of dying at home for patients with cancer; a 2012 provisional clinical opinion from the American Society of Clinical Oncology that recommends consideration of palliative care early in the course of illness for patients with metastatic cancer and/or high symptom burden; and three individual studies that support the relationship of hospice admission to desired patient outcomes such as increased survival times and reductions in aggressive end-of-life care. • The Committee agreed that the updated evidence appears to be directionally the same since the last NQF endorsement evaluation. The Committee accepted the prior evaluation of this criterion without further discussion. • The developer provided group/practice level performance data from the ASCO Quality Oncology Practice Initiative registry (QOPI) for 2013-2015. The median performance score was 12.97 in 2013, 14.64 in 2014, and 15.38 in 2015, an increasing trend that might be explained by higher participation in the QOPI® registry. The developer provided additional practice-level disparities data after the Committee’s workgroup call. The Committee agreed these data indicated potential disparities in care for racial/ethnic. The Committee agreed that there is substantial room for improvement for this measure.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-0; M-18; L-3; I-0 2b. Validity: H-0; M-19; L-2; I-0Rationale: • This measure is specified for both claims and registry data. When questioned about identifying cancer deaths from claims data, the developer clarified that the denominator is derived from registry data (e.g., a death registry or other cancer registry that includes information on cancer deaths) while the numerator is derived from claims data or the ASCO Quality Oncology Practice Initiative (QOPI®) registry.• The Committee questioned limiting the measure to Medicare patients only. The developers noted that only Medicare data were available for testing, thus the requirement for Medicare hospice enrollment. They are hopeful, however, that with the measure’s inclusion in the AHIP oncology core set, enrollment data for other payers will be available for use. They also noted that the QOPI® registry is not limited to Medicare hospice enrollees.• The Committee questioned the developer about the rationale for specifying 3-days as the threshold for appropriate timeframe for hospice enrollment. The developers noted that the QOPI® registry actually collects both 3-day and 7-day enrollment information and future versions of this measure may consider a longer timeframe. One Committee member noted that that enough variation currently exists in hospice enrollment that continued improvement is needed within the 3 day timeframe. While acknowledging that longer hospice enrollment is better, the Committee found this rationale for the 3-day threshold acceptable.• For the 2012 evaluation, the developer conducted data element reliability testing for the QOPI® registry data by comparing QOPI® registry data to data that were re-abstracted from medical records by QOPI nurse abstractors, which was considered the gold standard (kappa=0.551, indicating acceptable agreement). • For the 2012 evaluation, the developer conducted data element validity testing for the measure numerator from claims data by comparing claims for 150 consecutive patients treated for advanced cancer at Boston’s Dana-Farber Cancer Institute and Brigham and Women´s Hospital to data from the full medical record (sensitivity=0.97; specificity=1.00). Although the developer did not conduct data element validity testing for the measure denominator, the Committee agreed that registry data (particularly death registry data), in general, are accurate and therefore additional testing is unnecessary.• The developer did not provide any updated reliability or validity testing.• The Committee was not concerned with the lack of risk-adjustment for this measure.
  
  
• Review for Feasibility: 3. Feasibility: H-3; M-16; L-2; I-0(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c. Data collection strategy can be implemented)Rationale: • The Committee did not note any concerns regarding feasibility, acknowledging that the data elements used to construct this measure are available in claims and the QOPI® Registry.
  
  
• Review for Usability: 4. Usability and Use: H-13; M-8; L-0; I-0(Used and useful to the intended audiences for 4a. Accountability and Transparency; 4b. Improvement; and 4c. Benefits outweigh evidence of unintended consequences) Rationale:• The measure is currently used in the QOPI® Registry, a practice-based quality improvement and benchmarking program, operated by the American Society of Clinical Oncology. It is also part of America’s Health Insurance Plans (AHIP) Medical Oncology Core Measure Set. The AHIP effort is a collaboration of both public and private stakeholders to identify measures that are meaningful to patients, consumers, and physicians and to reduce variability in measure selection, collection burden, and cost. Payers involved in the collaboration have committed to using these measures for reporting as soon as feasible, and CMS has agreed to consider this measure for inclusion in Medicare quality programs.• While the number of practices reporting to QOPI has increased between 2013 and 2015, the average performance has not changed. • In its 2016 review, the MAP, supported by public comments, requested the Standing Committee consider a longer timeframe (e.g., 7 days) for this measure. However, the Committee agreed that very short hospice stays remain a concern and therefore did not recommend changing the timeframe for the measure at this time. • The Committee acknowledged that the measure might create a disincentive to refer actively dying patients to hospice but agreed that the benefits of the measure outweigh the potential risk.
  
  
• Review for Related and Competing Measures: 5. Related and Competing Measures• This measure is related to four measures:o 0210: Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of lifeo 0211: Proportion of patients who died from cancer with more than one emergency department visit in the last 30 days of lifeo 0213: Proportion of patients who died from cancer admitted to the ICU in the last 30 days of lifeo 0215: Proportion of patients who died from cancer not admitted to hospice• These measures, all of which were developed by the American Society of Clinical Oncology, are harmonized to the extent possible.
  
  
• Endorsement Public Comments: NQF received 4 post-evaluation comments on this measure, all of which were supportive of the measure.
  
  
• Endorsement Committee Recommendation: Y-21; N-0
  
  

Measure Specifications

• NQF Number (if applicable): 213
  
  
• Description: Proportion of patients who died from cancer admitted to the ICU in the last 30 days of life
  
  
• Numerator: Patients who died from cancer and were admitted to the ICU in the last 30 days of life
  
  
• Denominator: Patients who died from cancer.
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Registry
  
  
• Measure Type: Intermediate Outcome
  
  
• Steward: American Society of Clinical Oncology
  
  
• Endorsement Status: Endorsed
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The measure should be specified, tested and NQF endorsed at the facility level in the hospital setting for the PPS-Exempt Cancer Hospital Quality Reporting Program.
  • Impact on quality of care for patients:This measure provides the proportion of patients who died from cancer and were admitted to the ICU in the last 30 days of life.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. This measure captures an intermediate outcome. A higher quality of life has been predicted in patients who avoid aggressive measures such as ICU stays in the last week of life (Zhang, 2012). Furthermore, a longitudinal population-based study found patients who enrolled in hospice (long-or short-term) vs. those who did not receive hospice services had a reduced likelihood of being admitted to an ICU in the last 30 days of life by approximately 75% (Kao, 2015). ICU admissions, particularly those that result in a patient dying in the ICU, are more likely to result in physical and emotional distress as well as a less positive death experience (Wright, 2010).
  
  
• Does the measure address a quality challenge? Yes. This measure was submitted to the NQF Palliative Care and End-of-Life project. Although specified at the clinican group/practice level, the developers provided system-level performance data from two integrated health systems, one showing an increase from 20% in Fall 2011 to 37% in Spring 2013 and the other showing an average performance of 9.02% between June 2013 to May 2015.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure is not duplicative of existing measures in the program.
  
  
• Can the measure can be feasibly reported? Yes. The measure is not currently in use but the Standing Committee did not note any concerns regarding feasibility, acknowledging that the data elementsused to construct this measure are available in electronic sources.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? Yes. This measure is specified at the group/clinician level and tested in the ambulatory care setting. The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The appeals period is scheduled to close November 25, 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The developers do not anticipate any unintended consequences as a result of implementing this measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Zhang B, Nilsson ME, Prigerson HG. Factors important to patients´ quality of life at the end of life. Arch Intern Med 2012;172:1133-1142.Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3806298/ Wright AA, Keating NL, Balboni TA, et al. Place of death: correlations with quality of life of patients with cancer and predictors of bereaved caregivers’ mental health. J Clin Oncol 2010; 28:4457–4464. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2988637/ Langton JM, Blanch B, Drew AK, et al. Retrospective studies of end of-life resource utilization and costs in cancer care using health administrative data: a systematic review. Palliat Med 2014;28:1167-1196. Available at: http://www.ncbi.nlm.nih.gov/pubmed/24866758. Kao YH, Chiang JK. Effect of hospice care on quality indicators of end-of-life care among patients with liver cancer: a national longitudinal population based study in Taiwan 2000-2011. BMC Palliat Care 2015: 14:39. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4545784/#CR5 Barbera L, Seow H, et al. Quality of end-of-life cancer care in Canada: a retrospective four-province study using administrative health care data. Curr Oncol 2015 Oct: 22(5): 341-355. Available at: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4608400/

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Palliative and End-of-Life Care Project 2015-2016
  
  
• Review for Importance: 1a. Evidence: H-2; M-20; L-0; I-0; 1b. Performance Gap: H-3; M-18; L-1; I-0; Rationale:• For the 2012 endorsement evaluation, the developers cited a 2011 study that examined trends in the aggressiveness of end-of-life (EOL) cancer care (including ICU admission within 30 days of death), and an expert consensus statement from 2003 that identified potential indicators of quality of end-of-life cancer care using administrative data. • For the current evaluation, developers updated the evidence by referencing: a 2013 Cochrane Collaborative systematic review that evaluated the impact of home-based palliative care services on several patient and caregiver outcomes, which found that for patients with cancer, home-based palliative care services increases the chance of dying at home for patients with cancer; a 2012 provisional clinical opinion from the American Society of Clinical Oncology that recommends consideration of palliative care early in the course of illness for patients with metastatic cancer and/or high symptom burden; and two individual studies that support the relationship of reduced ICU visits to desired patient outcomes. • The Committee also referenced an additional study of colorectal and lung cancer patients that found that ICU use in the last 30 days of life is did not align with patient preference and was associated with worse outcomes (Wright, et al., 2016). After considering this additional empirical evidence, the Committee agreed that there is a high certainty that benefits of avoiding the ICU in the last month of life outweighs undesirable effects. • Although specified at the clinician group/practice level, the developers provided system-level performance data from two integrated health systems, one showing an increase from 20% in Fall 2011 to 37% in Spring 2013 and the other showing an average performance of 9.02% between June 2013 to May 2015. • Given the variation in the results within and between the two systems, the Committee agreed that opportunity for improvement exists.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-0; M-14; L-1; I-7 2b. Validity: H-0; M-20; L-1; I-1Rationale: • This measure is specified for both claims and registry data. When questioned about identifying cancer deaths from claims data, the developer clarified that the denominator is derived from registry data (e.g., a death registry or other cancer registry that includes information on cancer deaths) while the numerator is derived from claims data. • For the 2012 evaluation, the developer conducted data element validity testing for the measure numerator by comparing claims for 150 consecutive patients treated for advanced cancer at Boston’s Dana-Farber Cancer Institute and Brigham and Women´s Hospital to data from the full medical record (sensitivity=0.87; specificity=0.97). Although the developer did not conduct data element validity testing for the measure denominator, the Committee agreed that registry data (particularly death registry data), in general, are accurate and therefore additional testing is unnecessary.• The developer did not provide any updated validity testing.• The developers did not conduct reliability testing for either the numerator or the denominator. However, per NQF guidance, because data element validity testing was done for the measure numerator, additional data element reliability testing for the numerator is not required. As noted, the Committee agreed that the registry data used in the measure denominator are accurate, and therefore members agreed that additional data element reliability testing is not needed. • The Committee agreed that because admission to the ICU is, for the most part, under the control of the provider, risk-adjustment is not needed for this measure.
  
  
• Review for Feasibility: 3. Feasibility: H-4; M-18; L-0; I-0Rationale: • The Committee did not note any concerns regarding feasibility, acknowledging that the data elements used to construct this measure are available in electronic sources.
  
  
• Review for Usability: 4. Usability and Use: H-6; M-16; L-0; I-0Rationale:• This measure is not currently in use. However, it is part of America’s Health Insurance Plans (AHIP) Medical Oncology Core Measure Set. The AHIP effort is a collaboration of both public and private stakeholders to identify measures that are meaningful to patients, consumers, and physicians and to reduce variability in measure selection, collection burden, and cost. Payers involved in the collaboration have committed to using these measures for reporting as soon as feasible, and CMS has agreed to consider this measure for inclusion in Medicare quality programs.• Because the developer provided limited longitudinal data, performance trends could not be inferred. • Neither the Committee nor the developers reported awareness of unintended consequences associated with this measure.
  
  
• Review for Related and Competing Measures: This measure is related to four measures:o 0210: Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of lifeo 0211: Proportion of patients who died from cancer with more than one emergency department visit in the last 30 days of lifeo 0215: Proportion of patients who died from cancer not admitted to hospiceo 0216: Proportion of patients who died from cancer admitted to hospice for less than 3 days• These measures, all of which were developed by the American Society of Clinical Oncology, are harmonized to the extent possible.
  
  
• Endorsement Public Comments: NQF received 5 post-evaluation comments on this measure, all of which were supportive of the measure.
  
  
• Endorsement Committee Recommendation: Y-22; N-0
  
  

Measure Specifications

• NQF Number (if applicable): 215
  
  
• Description: Proportion of patients who died from cancer not admitted to hospice
  
  
• Numerator: Proportion of patients not enrolled in hospice
  
  
• Denominator: Patients who died from cancer.
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Registry
  
  
• Measure Type: Process
  
  
• Steward: American Society of Clinical Oncology
  
  
• Endorsement Status: Endorsed
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure is not specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The measure should be specified, tested and NQF endorsed at the facility level in the hospital setting for the PPS-Exempt Cancer Hospital Quality Reporting Program.
  • Impact on quality of care for patients:This measure provides the proportion of patients who died from cancer and were not admitted to hospice.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. This is a process measure is related to improving coordination of patients with cancer. Patients who were enrolled in hospice experienced increased survival times along with a reduction in resource use such as aggressive end of life care and hospital admissions; benefits that increased the longer patients were enrollment in hospice (Lee, 2015; Langton, 2014). In addition, Medicare patients were less likely to enroll in hospice in the last 30 days of life than Medicare patients with only 51% of Medicaid patients enrolled versus 64% of Medicare patients (Guadagnolo, 2015).Many patients are enrolled in hospice less than 3 weeks before their death, which limits the benefit they may gain from these services.
  
  
• Does the measure address a quality challenge? Yes. This measure was submitted to the NQF Palliative Care and End-of-Life project. The developer provided group/practice level performance data from the ASCO Quality Oncology Practice Initiative registry (QOPI) for 2013-2015. The median performance score was 40.0 in 2013, 41.67 in 2014,and 41.42 in 2015.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This meausure captures a broad population and encourages improved care coordination between cancer centers and hospice services.
  
  
• Can the measure can be feasibly reported? Yes. This is a new measure never used in a program. However, it is included in the Quality Oncology Practice Initiative (QOPI), a practice based quality assessment and improvement program designed to foster a culture of self-examination and improvement in oncology.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is specified at the group/clinician level and tested in the ambulatory care setting. The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The appeals period is scheduled to close November 25, 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The developers do not anticipate any unintended consequences as a result of implementing this measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Smith, T. J., S. Temin, et al. (2012). "American Society of Clinical Oncology provisional clinical opinion: the integration of palliative care into standard oncology care." J Clin Oncol 30(8): 880-887. O´Connor, T. L., N. Ngamphaiboon, et al. (2015). "Hospice utilization and end-of-life care in metastatic breast cancer patients at a comprehensive cancer center." J Palliat Med 18(1): 50-55. Lee, Y. J., J. H. Yang, et al. (2015). "Association between the duration of palliative care service and survival in terminal cancer patients." Support Care Cancer 23(4): 1057-1062. Langton, J. M., B. Blanch, et al. (2014). "Retrospective studies of end-of-life resource utilization and costs in cancer care using health administrative data: a systematic review." Palliat Med 28(10): 1167-1196. Guadagnolo, B. A., K. P. Liao, et al. (2015). "Variation in Intensity and Costs of Care by Payer and Race for Patients Dying of Cancer in Texas: An Analysis of Registry-linked Medicaid, Medicare, and Dually Eligible Claims Data." Med Care 53(7): 591-598.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Palliative and End-of-Life Care Project 2015-2016
  
  
• Review for Importance: 1a. Evidence: Previous Evidence Evaluation Accepted 1b. Performance Gap: H-20; M-2; L-0; I-0 Rationale:• For the 2012 endorsement evaluation, the developers cited two studies indicating hospice admission did not have detrimental effect on survival among elderly patients with lung cancer and was associated with bereaved family members reporting a) higher quality of end-of-life care, b) no unmet need for help with anxiety or depression, and c) death in the decedent’s died in preferred location. The developer also cited a 2003 expert consensus paper identifying hospice enrollment as an indicator of quality of end-of-life cancer care. • For the current evaluation, developers updated the evidence by referencing: a 2013 Cochrane Collaborative systematic review that evaluated the impact of home-based palliative care services on several patient and caregiver outcomes, which found that for patients with cancer, home-based palliative care services increases the chance of dying at home for patients with cancer; a 2012 provisional clinical opinion from the American Society of Clinical Oncology that recommends consideration of palliative care early in the course of illness for patients with metastatic cancer and/or high symptom burden; and four individual studies that support the relationship of hospice admission to desired patient outcomes. • The Committee agreed that the updated evidence appears to be directionally the same since the last NQF endorsement evaluation. The Committee accepted the prior evaluation of this criterion without further discussion. • The developer provided group/practice level performance data from the ASCO Quality Oncology Practice Initiative registry (QOPI) for 2013-2015. The median performance score was 40.0 in 2013, 41.67 in 2014, and 41.42 in 2015. The developer provided additional practice-level disparities data after the Committee’s workgroup call. The Committee agreed these data indicated potential disparities in care men and racial/ethnic minorities. The Committee agreed that there is substantial room for improvement for this measure.
  
  
• Review for Scientific Acceptability: 2a. Reliability: Previous Reliability Evaluation Accepted 2b. Validity: Previous Validity Evaluation AcceptedRationale: • This measure is specified for both claims and registry data. When questioned about identifying cancer deaths from claims data, the developer clarified that the denominator is derived from registry data (e.g., a death registry or other cancer registry that includes information on cancer deaths) while the numerator is derived from claims data or the ASCO Quality Oncology Practice Initiative (QOPI®) registry.• For the 2012 evaluation, the developer conducted data element validity testing for the QOPI® registry data by, comparing QOPI® registry data to data that were re-abstracted from medical records by QOPI nurse abstractors, which was considered the gold standard (kappa=0.679, indicating acceptable agreement). • For the 2012 evaluation, the developer conducted data element validity testing for the measure numerator for claims data by comparing claims for 150 consecutive patients treated for advanced cancer at Boston’s Dana-Farber Cancer Institute and Brigham and Women´s Hospital to data from the full medical record (sensitivity=0.24; specificity=0.96). Although the developer did not conduct data element validity testing for the measure denominator, the Committee agreed that registry data (particularly death registry data), in general, are accurate and therefore additional testing is unnecessary.• The developer did not provide any updated reliability or validity testing.• The Committee agreed the previous reliability and validity testing were demonstrated the scientific acceptability of the measure and accepted the prior evaluation of this criterion without further discussion.
  
  
• Review for Feasibility: 3. Feasibility: H-2; M-20; L-0; I-0(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c. Data collection strategy can be implemented)Rationale: • The Committee did not note any concerns regarding feasibility, acknowledging that the data elements used to construct this measure are available in claims and the QOPI® Registry.
  
  
• Review for Usability: 4. Usability and Use: H-2; M-20; L-0; I-0(Used and useful to the intended audiences for 4a. Accountability and Transparency; 4b. Improvement; and 4c. Benefits outweigh evidence of unintended consequences) Rationale:• The measure is currently used in the QOPI® Registry, a practice-based quality improvement and benchmarking program, operated by the American Society of Clinical Oncology. It is also part of America’s Health Insurance Plans (AHIP) Medical Oncology Core Measure Set. The AHIP effort is a collaboration of both public and private stakeholders to identify measures that are meaningful to patients, consumers, and physicians and to reduce variability in measure selection, collection burden, and cost. Payers involved in the collaboration have committed to using these measures for reporting as soon as feasible, and CMS has agreed to consider this measure for inclusion in Medicare quality programs.• While the number of practices reporting to QOPI has increased between 2013 and 2015, the average performance has not changed. • Neither the Committee nor the developers reported awareness of any unintended consequences associated with this measure.
  
  
• Review for Related and Competing Measures: Related and Competing Measures• This measure is related to four measures:o 0210: Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of lifeo 0213: Proportion of patients who died from cancer admitted to the ICU in the last 30 days of lifeo 0211: Proportion of patients who died from cancer with more than one emergency department visit in the last 30 days of lifeo 0216: Proportion of patients who died from cancer admitted to hospice for less than 3 days• These measures, all of which were developed by the American Society of Clinical Oncology, are harmonized to the extent possible.
  
  
• Endorsement Public Comments: NQF received 5 post-evaluation comments on this measure, all of which were supportive of the measure.
  
  
• Endorsement Committee Recommendation: Y-22; N-0
  
  

Measure Specifications

• NQF Number (if applicable): 210
  
  
• Description: Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of life
  
  
• Numerator: Patients who died from cancer and received chemotherapy in the last 14 days of life
  
  
• Denominator: Patients who died from cancer.
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims (non-Medicare), Registry
  
  
• Measure Type: Process
  
  
• Steward: American Society of Clinical Oncology
  
  
• Endorsement Status: Endorsed
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Refine and Resubmit
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The measure should be specified, tested and NQF endorsed at the facility level in the hospital setting for the PPS-Exempt Cancer Hospital Quality Reporting Program.
  • Impact on quality of care for patients:The measure provides patients with the proportion of cancer patients who receive chemotherapy in the last 14 days of life.
  
  
  
• Does the measure address a critical quality objective not adequately addressed by the measures in the program set? Yes. This measure focuses on promoting effective communication and coordination of care.
  
  
• Is the measure evidence-based and is either strongly linked to outcomes or an outcome measure? Yes. Patients receive unnecessary treatments at the end of life, which can negatively impact the patient and caregiver experience. Patients continue to receive chemotherapy treatments at the end of life even when it is recognized that it is unnecessary. For example, more than 15% of patients with metastatic lung and colorectal cancer received chemotherapy in the last month of life (Mack, 2015). In addition, receipt of chemotherapy at the end of life can increase the potential for hospitalizations and intensive care admissions (El-Jawahri, 2015), which can negatively impact the patient's and caregiver's experience
  
  
• Does the measure address a quality challenge? Yes. The performance data submitted to the NQF Palliative Care and End-of-Life project demonstrated the median performance score from the ASCO Quality Oncology Practice Initiative registry (QOPI) was 9.88 in 2013, 11.45 in 2014 and 11.95 in 2015.
  
  
• Does the measure contribute to efficient use of resources and/or support alignment of measurement across programs? Yes. This measure is not duplicative of existing measures in the program.
  
  
• Can the measure can be feasibly reported? Yes. This measure is currently used the QOPI® registry and reported to CMS by the registry as a Qualified Clinical Data Registry and in the CMS PQRS program. The measure and its specifications have been in place for several years and ASCO continues to monitor and ensure that the measure and its specifications are up-to-date for widespread use. This measure has also been included in America´s Health Insurance Plans Medical Oncology Core Measure Set.
  
  
• Is the measure reliable and valid for the level of analysis, program, and/or setting(s) for which it is being considered? No. This measure is specified at the group/clinician level and tested in the ambulatory care setting. The measure has not been specified and tested at the facility level in the hospital setting. The Palliative Care and End-of-Life Standing Committee, CSAC and the NQF Executive Committee recommended the measure for endorsement at the group/clinician level in the ambulatory care setting. The appeals period is scheduled to close November 25, 2016.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, do the benefits of the measure outweigh any unreasonable implementation issues that have been identified? Yes. The developers do not anticipate any unintended consequences as a result of implementing this measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed. Endorsed
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
El-Jawahri, A. R., G. A. Abel, et al. (2015). "Health care utilization and end-of-life care for older patients with acute myeloid leukemia." Cancer 121(16): 2840-2848. Mack, J. W., A. Walling, et al. (2015). "Patient beliefs that chemotherapy may be curative and care received at the end of life among patients with metastatic lung and colorectal cancer." Cancer 121(11): 1891-1897.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2016
  
  
• Project for Most Recent Endorsement Review: Palliative and End-of-Life Care Project 2015-2016
  
  
• Review for Importance: 1a. Evidence: H-1; M-19; L-1; I-1; 1b. Performance Gap: H-1; M-21; L-0; I-0 Rationale:• For the 2012 endorsement evaluation, the developers cited three individual studies indicating continuing chemotherapy near death does not prolong survival and often results in undesirable outcomes (e.g. toxicity, inconvenience, increased costs, and lower patient rating of quality of care). The developer also cited a 2003 expert consensus statement that identified a short interval between last chemotherapy dose and death as an indicator of poor quality of end-of-life cancer care.• For the current evaluation, developers updated the evidence by referencing a 2013 Cochrane Collaborative systematic review that found that for patients with cancer, home-based palliative care services increases the chance of dying at home for patients with cancer and a 2012 provisional clinical opinion from the American Society of Clinical Oncology that recommends consideration of palliative care early in the course of illness for patients with metastatic cancer and/or high symptom burden• In general, the Committee agreed that the evidence presented during the 2012 evaluation was sufficient to support the measure at the time. However, some members noted that this older evidence does not speak to the relationship between newer chemotherapies (e.g., oral agents that may be less toxic than older chemotherapy options) to patient outcomes. One member cited a recent longitudinal, multi-site study by Prigerson et al. (2015) that was not included in the evidence submitted by the developer. Although this study demonstrated the relationship between chemotherapy at the end of-life and poor quality of life, it also did not include newer chemotherapies. Committee members noted that the performance rate for this measure should not be zero, as in some cases, a continuation of chemotherapy is beneficial. Members also noted that when considering this measure, the possibility of both potential harm as well as failure to benefit should be considered. The Committee eventually reached consensus that the evidence cited provided was sufficient for the measure. • The developer provided group/practice level performance data from the ASCO Quality Oncology Practice Initiative registry (QOPI) for 2013-2015. The median performance score was 9.88 in 2013, 11.45 in 2014, and 11.95 in 2015, an increasing trend that might be explained by higher participation in the QOPI® registry. The developer provided additional practice-level disparities data after the Committee’s workgroup call. The Committee agreed these data indicated potential disparities in care by sex and race. The Committee agreed there is substantial room for improvement for this measure.
  
  
• Review for Scientific Acceptability: 2a. Reliability: Previous Reliability Evaluation Accepted 2b. Validity: H-22; M-0; L-0; I-0Rationale: • This measure is specified for both claims and registry data. When questioned about identifying cancer deaths from claims data, the developer clarified that the denominator is derived from registry data (e.g., a death registry or other cancer registry that includes information on cancer deaths) while the numerator is derived from claims data. • The Committee questioned the developer about inclusion of oral and other new biologics in the measure numerator. The developer clarified that the specifications include all anti-neoplastic agents except for hormonal therapies. • For the 2012 evaluation, the developer conducted data element validity testing for the QOPI® registry data by, comparing QOPI® registry data to data that were re-abstracted from medical records by QOPI nurse abstractors, which was considered the gold standard (kappa=0.818, indicating acceptable agreement). • For the 2012 evaluation, the developer conducted data element validity testing for the measure numerator for claims data by comparing claims for 150 consecutive patients treated for advanced cancer at Boston’s Dana-Farber Cancer Institute and Brigham and Women´s Hospital to data from the full medical record (sensitivity=0.92; specificity=0.94). Although the developer did not conduct data element validity testing for the measure denominator, the Committee agreed that registry data (particularly death registry data), in general, are accurate and therefore additional testing is unnecessary.• The developer did not provide any updated validity testing.• The Committee again noted that the expected performance for this measure should not be zero, particularly for blood cancer. While members did not think this would be an argument for risk-adjustment at this point, the developers stated that they would consider this issue along with other risk-adjustment questions in the future • The Committee agreed the previous validity testing demonstrated the scientific acceptability of the measure. Members accepted the prior evaluation of the reliability sub criterion without further discussion. Members did vote on validity because there was no empirical testing of the denominator (from claims or registry).
  
  
• Review for Feasibility: 3. Feasibility: H-3; M-16; L-2; I-0Rationale: • The Committee did not note any concerns regarding feasibility, acknowledging that the data elements used to construct this measure are available in claims and the QOPI® Registry.
  
  
• Review for Usability: 4. Usability and Use: H-3; M-19; L-0; I-0Rationale:• The measure is currently used in the Quality Oncology Practice Initiative (QOPI), a practice-based quality improvement and benchmarking program, operated by the American Society of Clinical Oncology. The measure also is included in the PQRS program and is also a part of America’s Health Insurance Plans (AHIP) Medical Oncology Core Measure Set. The AHIP effort is a collaboration of both public and private stakeholders to identify measures that are meaningful to patients, consumers, and physicians and to reduce variability in measure selection, collection burden, and cost. Payers involved in the collaboration have committed to using for reporting as soon as feasible. By virtue of being included in the AHIP measure set, CMS will consider this measure for inclusion in other Medicare quality programs.• Data from 2013-2015 indicate mean practice performance slightly worsened from 11.47% of patients receiving chemotherapy in last 14 days of life to 13.16%. These results are based on data from the QOPI® registry and reflect slightly greater use of the registry over time, from 180 practices in 2013 to 222 in 2015.• Neither the Committee nor the developers reported awareness of unintended consequences associated with this measure.
  
  
• Review for Related and Competing Measures: This measure is related to four measures:o 0213: Proportion of patients who died from cancer admitted to the ICU in the last 30 days of lifeo 0211: Proportion of patients who died from cancer with more than one emergency department visit in the last 30 days of lifeo 0215: Proportion of patients who died from cancer not admitted to hospiceo 0216: Proportion of patients who died from cancer admitted to hospice for less than 3 days• These measures, all of which were developed by the American Society of Clinical Oncology, are harmonized to the extent possible.
  
  
• Endorsement Public Comments: NQF received 5 post-evaluation comments on this measure, all of which were supportive of the measure.
  
  
• Endorsement Committee Recommendation: Y-22; N-0
  
  

Program Index

• Ambulatory Surgical Center Quality Reporting Program 
  
  
• End-Stage Renal Disease Quality Incentive Program 
  
  
• Hospital Acquired Condition Reduction Program 
  
  
• Hospital Inpatient Quality Reporting and EHR Incentive Program 
  
  
• Hospital Outpatient Quality Reporting Program 
  
  
• Hospital Readmissions Reduction Program 
  
  
• Hospital Value-Based Purchasing Program 
  
  
• Inpatient Psychiatric Facility Quality Reporting Program 
  
  
• Prospective Payment System-Exempt Cancer Hospital Quality Reporting Program 
  
  

Full Program Summaries

Program History and Structure: The Ambulatory Surgical Center Quality Reporting Program (ASCQR) was established under the authority provided by Section 109(b) of the Medicare Improvements and Extension Act of 2006, Division B, Title I of the Tax Relief and Health Care Act (TRHCA) of 2006. The statute provides the authority for requiring ASCs paid under the ASC fee schedule (ASCFS) to report on process, structure, outcomes, patient experience of care, efficiency, and costs of care measures. ASCs receive a 2.0 percentage point payment penalty to their ASCFS annual payment update for not meeting program requirements. CMS implemented this program so that payment determinations were effective beginning with the Calendar Year (CY) 2014 payment update.

High Priority Domains for Future Measure Consideration:

High Priority Domains for Future Measure Consideration:

CMS identified the following categories as high-priority for future measure consideration:

1. Making Care Safer a. Measures of infection rates
2. Person and Family Engagement
   1. Measures that improve experience of care for patients, caregivers, and families.
   2. Measures to promote patient self-management.
3. Best Practice of Healthy Living
   1. Measures to increase appropriate use of screening and prevention services.
   2. Measures which will improve the quality of care for patients with multiple chronic conditions.
   3. Measures to improve behavioral health access and quality of care.
4. Effective Prevention and Treatment a. Surgical outcome measures
5. Communication/Care Coordination
   1. Measures to embed best practice to manage transitions across practice settings.
   2. Measures to enable effective health care system navigation.
   3. To reduce unexpected hospital/emergency visits and admissions

Measure Requirements:

CMS applies criteria for measures that may be considered for potential adoption in the ASCQR. At a minimum, the following requirements will be considered in selecting measures for ASCQR implementation:

1. Measure must adhere to CMS statutory requirements.
   1. Measures are required to reflect consensus among affected parties, and to the extent feasible, be endorsed by the national consensus entity with a contract under Section 1890(a) of the Social Security Act
   2. The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a) of the Social Security Act, as long as endorsed measures have been given due consideration
2. Measure must address a NQS priority/CMS strategy goal, with preference for measures addressing the high priority domains for future measure consideration.
3. Measure must address an important condition/topic for which there is analytic evidence that a performance gap exists and that measure implementation can lead to improvement in desired outcomes, costs, or resource utilization.
4. Measure must be field tested for the ASC clinical setting.
5. Measure that is clinically useful.
6. Reporting of measure limits data collection and submission burden since many ASCs are small facilities with limited staffing.
7. Measure must supply sufficient case numbers for differentiation of ASC performance.
8. Measure must promote alignment across HHS and CMS programs.
9. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: For more than 30 years, monitoring the quality of care provided to end-stage renal disease (ESRD) patients by dialysis facilities has been an important component of the Medicare ESRD payment system. The ESRD quality incentive program (QIP) is the most recent step in fostering improved patient outcomes by establishing incentives for dialysis facilities to meet or exceed performance standards established by CMS. The ESRD QIP is authorized by section 1881(h) of the Social Security Act, which was added by section 153(c) of Medicare Improvements for Patients and Providers (MIPPA) Act (the Act). CMS established the ESRD QIP for Payment Year (PY) 2012, the initial year of the program in which payment reductions were applied, in two rules published in the Federal Register on August 12, 2010, and January 5, 2011 (75 FR 49030 and 76 FR 628, respectively). Subsequently, CMS published rules in the Federal Register detailing the QIP requirements for PY 2013 through FY 2016. Most recently, CMS published a rule on November 6, 2014 in the Federal Register (79 FR 66119), providing the ESRD QIP requirements for PY2017 and PY 2018, with the intention of providing an additional year between finalization of the rule and implementation in future rules. Section 1881(h) of the Act requires the Secretary to establish an ESRD QIP by (i) selecting measures; (ii) establishing the performance standards that apply to the individual measures; (iii) specifying a performance period with respect to a year; (iv) developing a methodology for assessing the total performance of each facility based on the performance standards with respect to the measures for a performance period; and (v) applying an appropriate payment reduction to facilities that do not meet or exceed the established Total Performance Score (TPS).

High Priority Domains for Future Measure Consideration:

CMS identified the following 3 domains as high-priority for future measure consideration:

1. Care Coordination: ESRD patients constitute a vulnerable population that depends on a large quantity and variety medication and frequent utilization of multiple providers, suggesting medication reconciliation is a critical issue. Dialysis facilities also play a substantial role in preparing dialysis patients for kidney transplants, and coordination of dialysis-related services among transient patients has consequences for a non-trivial proportion of the ESRD dialysis population.
2. Safety: ESRD patients are frequently immune-compromised, and experience high rates of blood stream infections, vascular access-related infections, and mortality. Additionally, some medications provided to treat ESRD patients may cause harmful side effects such as heart disease and a dynamic bone disease. Recently, oral-only medications were excluded from the bundle payment, increasing need for quality measures that protect against overutilization of oral-only medications.
3. Patient- and Caregiver-Centered Experience of Care: Sustaining and recovering patient quality of life was among the original goals of the Medicare ESRD QIP. This includes such issues as physical function, independence, and cognition. Quality of Life measures should also consider the life goals of the particular patient where feasible, to the point of including Patient-Reported Outcomes.
4. Access to Transplantation: Obtaining a transplant is an extended process for dialysis patients, including education, referral, waitlisting, transplantation, and follow-up care. The care and information available from dialysis facilities are integral to the process. Complicating the issue of attribution are the role of transplant facilities in setting criteria and making decisions about transplant candidates and the limited availability of donor organs. Measures for the ESRD QIP must balance the role of the facility and other providers with the need to make transplants accessible to as many candidate recipients as possible.

Measure Requirements:

1. Measures for anemia management reflecting FDA labeling, as well as measures for dialysis adequacy.
2. Measure(s) of patient satisfaction, to the extent feasible.
3. Measures of iron management, bone mineral metabolism, and vascular access, to the extent feasible.
4. Measures should be NQF endorsed, save where due consideration is given to endorsed measures of the same specified area or medical topic.
5. Must include measures considering unique treatment needs of children and young adults.
6. May incorporate Medicare claims and/or CROWNWeb data, alternative data sources will be considered dependent upon available infrastructure.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: Section 3008 of the Patient Protection and Affordable Care Act of 2010 (ACA) established the HospitalAcquired Condition Reduction Program (HACRP). Created under Section 1886(p) of the Social Security Act (the Act), the HACRP provides an incentive for hospitals to reduce the number of HACs. Effective Fiscal Year (FY) 2014 and beyond, the HACRP requires the Secretary to make payment adjustments to applicable hospitals that rank in the top quartile of all subsection (d) hospitals relative to a national average of HACs acquired during an applicable hospital stay. HACs include a condition identified in subsection 1886(d)(4)(D)(iv) of the Act and any other condition determined appropriate by the Secretary. Section 1886(p)(6)(C) of the Act requires the HAC information be posted on the Hospital Compare website. CMS finalized in the FY 2014 IPPS/LTCH PPS final rule that hospitals will be scored using a Total HAC Score based on measures categorized into two (2) domains of care, each with a different set of measures. Domain 1 consists of Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSI), and Domain 2 consists of Hospital Associated Infections (HAI) as collected by the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN). Both domains of the HAC Reduction Program are categorized under the National Quality Strategy (NQS) priority of “Making Care Safer.” The Total HAC Score is the sum of the two weighted domain scores, with Domain 1 weighted at 15% and Domain 2 weighted at 85%.

High Priority Domains for Future Measure Consideration:

For FY 2017 federal rulemaking, CMS may propose the adoption, removal, and/or suspensionof measures for fiscal years 2018 and beyond of the HACRP. CMS identified the following topics as areas within the NQS priority of “Making Care Safer” for future measure consideration:

Making Care Safer:

1. Adverse Drug Events
2. Ventilator Associated Events
3. Additional Surgical Site Infection Locations
4. Outcome Risk-Adjusted Measures
5. Diagnostic Errors
6. All-Cause Harm

Measure Requirements:

CMS applies criteria for measures that may be considered for potential adoption in the HACRP. At a minimum, the following requirements must be met for consideration in the HACRP:

• Measures must be identified as a HAC under Section 1886(d)(4)(D) or be a condition identified by the Secretary.
• Measures must address high cost or high volume conditions.
• Measures must be easily preventable by using evidence-based guidelines.
• Measures must not require additional system infrastructure for date submission and collection.
• Measures must be risk adjusted.
• Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: The Hospital Inpatient Quality Reporting (HIQR) Program was established by Section 501(b) of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 and expanded by the Deficit Reduction Act of 2005. The program requires hospitals paid under the Inpatient Prospective Payment System (IPPS) to report on process, structure, outcomes, patient perspectives on care, efficiency, and costs of care measures. Hospitals that fail to meet the requirements of the HIQR will result in a reduction of one-fourth to their fiscal year IPPS annual payment update (the annual payment update includes inflation in costs of goods and services used by hospitals in treating Medicare patients). Hospitals that choose to not participate in the program receive a reduction by that same amount. Hospitals not included in the HIQR, such as critical access hospitals and hospitals located in Puerto Rico and the U.S. Territories, are permitted to participate in voluntary quality reporting. Performance of quality measures are publicly reported on the CMS Hospital Compare website. The American Recovery and Reinvestment Act of 2009 amended Titles XVIII and XIX of the Social Security Act to authorize incentive payments to eligible hospitals (EHs) and critical access hospitals (CAHs) that participate in the EHR Incentive Program, to promote the adoption and meaningful use of certified electronic health record (EHR) technology (CEHRT). EHs and CAHs are required to report on electronically-specified clinical quality measures (eCQMs) using CEHRT in order to qualify for incentive payments under the Medicare and Medicaid EHR Incentive Programs. All EHR Incentive Program requirements related to eCQM reporting will be addressed in IPPS rulemaking including, but not limited to, new program requirements, reporting requirements, reporting and submission periods, reporting methods, alignment efforts between the HIQR and the Medicare EHR Incentive Program for EHs and CAHs, and information regarding the eCQMs.

High Priority Domains for Future Measure Consideration:

CMS identified the following categories as high-priority for future measure consideration:

1. Patient and Family Engagement:
   1. Measures that foster the engagement of patients and families as partners in their care.
2. Best Practices of Healthy Living:
   1. Measures that promote best practices to enable healthy living.
3. Making Care Affordable:
   1. Measures that effectuate changes in efficiency and reward value over volume.

Measure Requirements:

CMS applies criteria for measures that may be considered for potential adoption in the HIQR program. At a minimum, the following criteria will be considered in selecting measures for HIQR program implementation:

1. Measure must adhere to CMS statutory requirements.
   1. Measures are required to reflect consensus among affected parties, and to the extent feasible, be endorsed by the national consensus entity with a contract underSection 1890(a) of the Social Security Act; currently the National Quality Forum(NQF)
   2. The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a)of the Social Security Act, as long as endorsed measures have been given due consideration
2. Measure must be claims-based or an electronically specified clinical quality measure(eCQM).
   1. A Measure Authoring Tool (MAT) number must be provided for all eCQMs, createdin the HQMF format
   2. eCQMs must undergo reliability and validity testing including review of the logic and value sets by the CMS partners, including, but not limited to, MITRE and the National Library of Medicine
   3. eCQMs must have successfully passed feasibility testing
3. Measure may not require reporting to a proprietary registry.
4. Measure must address an important condition/topic for which there is analytic evidence thata performance gap exists and that measure implementation can lead to improvement indesired outcomes, costs, or resource utilization.
5. Measure must be fully developed, tested, and validated in the acute inpatientsetting.
6. Measure must address a NQS priority/CMS strategy goal, with preference for measures addressing the high priority domains and/or measurement gaps for future measure consideration.
7. Measure must promote alignment across HHS and CMS programs.
8. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: The Hospital Outpatient Quality Reporting (OQR) Program was established by Section 109 of the Tax Relief and Health Care Act (TRHCA) of 2006. The program requires subsection (d) hospitals providing outpatient services paid under the Outpatient Prospective Payment System (OPPS) to report on process, structure, outcomes, efficiency, costs of care, and patient experience of care. Hospitals receive a 2.0 percentage point reduction of their annual payment update (APU) under the Outpatient Prospective Payment System (OPPS) for non-participation in the program. Performance on quality measures is publicly reported on the CMS Hospital Compare website.

High Priority Domains for Future Measure Consideration: CMS identified the following categories as high-priority for future measure consideration:

1. Making Care Safer:
1. Measures that address processes and outcomes designed to reduce risk in the delivery of health care, e.g., emergency department overcrowding and wait times.
2. Best Practices of Healthy Living:
1. Measures that focus on primary prevention of disease or general screening for early detection of disease unrelated to a current or prior condition.
3. Patient and Family Engagement:
1. Measures that address engaging both the person and their family in their care.
2. Measures that address cultural sensitivity, patient decision-making support or care that reflects patient preferences.
4. Communication/Care Coordination:
1. Measures to embed best practices to manage transitions across practice settings.
2. Measures to enable effective health care system navigation.
3. Measures to reduce unexpected hospital/emergency visits and admissions.

Measure Requirements: CMS applies criteria for measures that may be considered for potential adoption in the HOQR program. At a minimum, the following criteria will be considered in selecting measures for HOQR program implementation:

1. Measure must adhere to CMS statutory requirements.
1. Measures are required to reflect consensus among affected parties, and to the extent feasible, be endorsed by the national consensus entity with a contract under Section 1890(a) of the Social Security Act
2. The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a) of the Social Security Act, as long as endorsed measures have been given due consideration
2. Measure must address a NQS priority/CMS strategy goal, with preference for measures addressing the high priority domains for future measure consideration.
3. Measure must address an important condition/topic for which there is analytic evidence that a performance gap exists and that measure implementation can lead to improvement in desired outcomes, costs, or resource utilization.
4. Measure must be fully developed, tested, and validated in the hospital outpatient setting.
5. Measure must promote alignment across HHS and CMS programs.
6. Feasibility of Implementation: An evaluation of feasibility is based on factors including, but not limited to
1. The level of burden associated with validating measure data, both for CMS and for the end user.
2. Whether the identified CMS system for data collection is prepared to accommodate the proposed measure(s) and timeline for collection.
3. The availability and practicability of measure specifications, e.g., measure specifications in the public domain.
4. The level of burden the data collection system or methodology poses for an end user.
7. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: Section 3025 of the Patient Protection and Affordable Care Act of 2010 (ACA) established the Hospital Readmissions Reduction Program (HRRP). Codified under Section 1886(q) of the Social Security Act (the Act), the HRRP provides an incentive for hospitals to reduce the number of excess readmissions that occur in their settings. Effective Fiscal Year (FY) 2012 and beyond, the HRRP requires the Secretaryto establish readmission measures for applicable conditions and to calculate an excess readmissionratio for each applicable condition, which will be used to determine a payment adjustment to those hospitals with excess readmissions. A readmission is defined as an admission to an acute care hospital within 30 days of a discharge from the same or another acute care hospital. A hospital’s excess readmission ratio measures a hospital’s readmission performance compared to the national average for the hospital’s set of patients with that applicable condition. Applicable conditions in the FY 2017 HRRP program currentlyinclude measures for acute myocardial infarction, heart failure, pneumonia, chronic obstructivepulmonary disease, elective total knee and total hip arthroplasty, and coronaryartery bypass graft surgery. Planned readmissions are excluded from the excess readmission calculation.

High Priority Domains for Future Measure Consideration:

For FY 2017 federal rulemaking, CMS may propose the adoption, removal, refinement, and or suspension of measures for fiscal year 2018 and subsequent years of the HRRP. CMS continuesto emphasize the importance of the NQS priority of “Communication/Care Coordination” for this program.

• Care Coordination
  • Measures that address high impact conditions identified by the Medicare Payment Advisory Commission or the Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP)reports.

Measure Requirements:

CMS applies criteria for measures that may be considered for potential adoption in the HRRP. At a minimum, the following criteria and requirements must be met for consideration in the HRRP:

• CMS is statutorily required to select measures for applicable conditions, which are defined as conditions or procedures selected by the Secretary in which readmissions are high volumeor high expenditure.
• Measures selected must be endorsed by the consensus-based entity with a contract under Section 1890 of the Act. However, the Secretary can select measures which are feasibleand practical in a specified area or medical topic determined to be appropriate by the Secretary, that have not been endorsed by the entity with a contract under Section 1890 of the Act, as longas endorsed measures have been given due consideration.
• Measure methodology must be consistent with other readmissions measures currently implemented or proposed in the HRRP.
• Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: The Hospital Value-Based Purchasing (HVBP) Program was established by Section 3001(a) of the Affordable Care Act, under which value-based incentive payments are made each fiscal year to hospitals meeting performance standards established for a performance period for such fiscal year. The Secretary shall select measures, other than measures of readmissions, for purposes of the Program. In addition, measures of five conditions (acute myocardial infarction, pneumonia, heart failure, surgeries, and healthcare-associated infections), the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey, and efficiency measures must be included. Measures are eligible for adoption in the HVBP Program based on the statutory requirements, including specification under the Hospital Inpatient Quality Reporting (HIQR) Program and posting dates on the Hospital Compare website.

High Priority Domains for Future Measure Consideration:

CMS identified the following categories as high-priority for future measure consideration:

1. Patient and Family Engagement:
   1. Measures that foster the engagement of patients and families as partners in their care.
2. Making Care Affordable:
   1. Measures that effectuate changes in efficiency and reward value over volume.

Measure Requirements:

CMS applies criteria for measures that may be considered for potential adoption in the HVBP Program. At a minimum, the following criteria will be considered in selecting measures for HVBP Program implementation:

1. Measure must adhere to CMS statutory requirements, including specification under the Hospital IQR Program and posting dates on the Hospital Compare website.
   • Measures are required to reflect consensus among affected parties, and to the extent feasible, be endorsed by the national consensus entity with a contract under Section 1890(a) of the Social Security Act; currently the National Quality Forum (NQF)
   • The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a) of the Social Security Act, as long as endorsed measures have been given due consideration
2. Measure may not require reporting to a proprietary registry.
3. Measure must address an important condition/topic for which there is analytic evidence that a performance gap exists and that measure implementation can lead to improvement in desired outcomes, costs, or resource utilization.
4. Measure must be fully developed, tested, and validated in the acute inpatient setting.
5. Measure must address a NQS priority/CMS strategy goal, with preference for measures addressing the high priority domains and/or measurement gaps for future measure consideration.
6. Measure must promote alignment across HHS and CMS programs.
7. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: The Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program was established by Section 1886(s)(4) of the Social Security Act, as added by sections 3401(f)(4) and 10322(a) of the Patient Protection and Affordable Care Act (the Affordable Care Act). Under current regulations, the program requires participating inpatient psychiatric facilities (IPFs) to report on 16 quality measures or face a 2.0 percentage point reduction to their annual update. Reporting on these measures apply to payment determinations for Fiscal Year (FY) 2017 and beyond.

High Priority Domains for Future Measure Consideration:

CMS identified the following categories as high-priority for future measure consideration:

1. Patient and Family Engagement
   1. Patient experience of care
2. Effective Prevention and Treatment
   1. Inpatient psychiatric treatment and quality of care of geriatric patients and other adults, adolescents, and children
   2. Quality of prescribing for antipsychotics and antidepressants
3. Best Practices of Healthy Living
   1. Screening and treatment for non-psychiatric comorbid conditions for which patients with mental or substance use disorders are at higher risk
   2. Access to care
4. Making Care Affordable
   1. Measures which effectuate changes in efficiency and that reward value over volume.

Measure Requirements: CMS applies criteria for measures that may be considered for potential adoption in the IPFQR. At a minimum, the following criteria will be considered in selecting measures for IPFQR implementation: Measure must adhere to CMS statutory requirements. Measures are required to reflect consensus among affected parties, and to the extent feasible, be endorsed by the national consensus entity with a contract under Section 1890(a) of the Social Security Act The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a) of the Social Security Act, as long as endorsed measures have been given due consideration Measure must address an important condition/topic for which there is analytic evidence that a performance gap exists and that measure implementation can lead to improvement in desired outcomes, costs, or resource utilization. The measure assesses meaningful performance differences between facilities. The measure addresses an aspect of care affecting a significant proportion of IPF patients. Measure must be fully developed, tested, and validated in the acute inpatient setting. Measure must address a NQS priority/CMS strategy goal, with preference for measures addressing the high priority domains for future measure consideration. Measure must promote alignment across HHS and CMS programs. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Program History and Structure: Section 3005 of the Affordable Care Act added new subsections (a)(1)(W) and (k) to section 1866 of the Social Security Act (the Act). Section 1866(k) of the Act establishes a quality reporting programfor hospitals described in section 1886(d)(1)(B)(v) of the Act (referred to as a “PPS-Exempt Cancer Hospital” or PCHQR). Section 1866(k)(1) of the Act states that, for FY 2014 and each subsequent fiscal year, a PCH shall submit data to the Secretary in accordance with section 1866(k)(2) of the Act with respect to such a fiscal year. In FY 2014 and each subsequent fiscal year, each hospital described in section 1886(d)(1)(B)(v) of the Act shall submit data to the Secretary on quality measures (QMs) specified under section 1866(k)(3) of the Act in a form and manner, and at a time, specified by the Secretary. The program requires PCHs to submit data for selected QMs to CMS. PCHQR is a voluntaryquality reporting program, in which data will be publicly reported on a CMS website. In the FY 2012 IPPSrule, five NQF endorsed measures were adopted and finalized for the FY 2014 reporting period, which was the first year of the PCHQR. In the FY 2013 IPPS rule, one additional measure wasadopted. Twelve new measures were adopted in the FY 2014 IPPS rule and one measure was adopted in theFY 2015 IPPS rule. Data collection for the FY 2017 and FY 2018 reporting periods is underway.

High Priority Domains for Future Measure Consideration:

CMS identified the following categories as high-priority for future measure consideration:

1. Communication and Care Coordination
   • Measures regarding care coordination with other facilities and outpatient settings, such as hospice care.
   • Measures of the patient’s functional status, quality of life, and end of life.
2. Making Care Affordable
   • Measures related to efficiency, appropriateness, and utilization (over/under-utilization) of cancer treatment modalities such as chemotherapy, radiation therapy, and imaging treatments.
3. Person and Family Engagement
   • Measures related to patient-centered care planning, shared decision-making, and quality of life outcomes.

Measure Requirements: The following requirements will be considered by CMS when selecting measures forprogram implementation: Measure is responsive to specific program goals and statutory requirements. Measures are required to reflect consensus among stakeholders, and to the extent feasible, be endorsed by the national consensus entity with a contract underSection 1890(a) of the Social Security Act; currently the National Quality Forum(NQF) The Secretary may select a measure in an area or topic in which a feasible and practical measure has not been endorsed, by the entity with a contract under Section 1890(a)of the Social Security Act, as long as endorsed measures have been given due consideration Measure specifications must be publicly available. Measure steward will provide CMS with technical assistance and clarifications on the measure as needed. Promote alignment with specific program attributes and across CMS and HHSprograms. Measure alignment should support the measurement across the patient’s episode of care, demonstrated by assessment of the person’s trajectory across providers and settings. Potential use of the measure in a program does not result in negative unintended consequences (e.g., inappropriate reduced lengths of stay, overuse or inappropriate use of care ortreatment, limiting access to care). Measures must be fully developed and tested, preferably in the PCHenvironment. Measures must be feasible to implement across PCHs, e.g., calculation, and reporting. Measure addresses an important condition/topic with a performance gap and has a strong scientific evidence base to demonstrate that the measure when implemented can lead to the desired outcomes and/or more appropriate costs. CMS has the resources to operationalize and maintain the measure.

Current Measures: NQF staff have compiled the program's measures in a presentation organized according to concepts.

Index of Measures (by Program)

General Comments

• General comments
  
  

• Ambulatory Breast Procedure Surgical Site Infection (SSI) Outcome Measure (Public comments received:1; MUC ID: MUC16-155)
  
  
• Hospital Visits after Orthopedic Ambulatory Surgical Center Procedures (Public comments received:1; MUC ID: MUC16-152)
  
  
• Hospital Visits after Urology Ambulatory Surgical Center Procedures (Public comments received:1; MUC ID: MUC16-153)
  
  

• Hemodialysis Vascular Access: Long-term Catheter Rate (Public comments received:3; MUC ID: MUC16-309)
  
  
• Hemodialysis Vascular Access: Standardized Fistula Rate (Public comments received:2; MUC ID: MUC16-308)
  
  
• Standardized Transfusion Ratio for Dialysis Facilities (Public comments received:2; MUC ID: MUC16-305)
  
  

• Alcohol & Other Drug Use Disorder Treatment Provided or Offered at Discharge and Alcohol & Other Drug Use Disorder Treatment at Discharge (Public comments received:3; MUC ID: MUC16-180)
  
  
• Alcohol Use Brief Intervention Provided or Offered and Alcohol Use Brief Intervention (Public comments received:3; MUC ID: MUC16-178)
  
  
• Alcohol Use Screening (Public comments received:4; MUC ID: MUC16-179)
  
  
• Appropriate Documentation of a Malnutrition Diagnosis (Public comments received:3; MUC ID: MUC16-344)
  
  
• Communication about Pain During the Hospital Stay (Public comments received:2; MUC ID: MUC16-263)
  
  
• Communication about Treating Pain Post-Discharge (Public comments received:4; MUC ID: MUC16-264)
  
  
• Completion of a Malnutrition Screening within 24 Hours of Admission (Public comments received:4; MUC ID: MUC16-294)
  
  
• Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition within 24 Hours of a Malnutrition Screening (Public comments received:2; MUC ID: MUC16-296)
  
  
• Follow-Up After Hospitalization for Mental Illness (No public comments received; MUC ID: MUC16-165)
  
  
• Hospital-Wide Risk Standardized Mortality Measure (Public comments received:3; MUC ID: MUC16-260)
  
  
• Measure of Quality of Informed Consent Documents for Hospital-Performed, Elective Procedures (Public comments received:1; MUC ID: MUC16-262)
  
  
• Nutrition Care Plan for Patients Identified as Malnourished after a Completed Nutrition Assessment (Public comments received:14; MUC ID: MUC16-372)
  
  
• Patient Panel Smoking Prevalence IQR (Public comments received:1; MUC ID: MUC16-068)
  
  
• Safe Use of Opioids – Concurrent Prescribing (Public comments received:2; MUC ID: MUC16-167)
  
  

• Influenza Immunization (IMM-2) (Public comments received:1; MUC ID: MUC16-053)
  
  
• Tobacco Use Screening (TOB-1) (Public comments received:1; MUC ID: MUC16-050)
  
  
• Tobacco Use Treatment Provided or Offered (TOB-2)/Tobacco Use Treatment (TOB-2a) (Public comments received:1; MUC ID: MUC16-051)
  
  
• Tobacco Use Treatment Provided or Offered at Discharge (TOB-3)/Tobacco Use Treatment at Discharge (TOB-3a) (Public comments received:3; MUC ID: MUC16-052)
  
  
• Use of Antipsychotics in Older Adults in the Inpatient Hospital Setting (No public comments received; MUC ID: MUC16-041)
  
  

• Median Time from ED Arrival to ED Departure for Discharged ED Patients (Public comments received:7; MUC ID: MUC16-055)
  
  
• Median Time to Pain Management for Long Bone Fracture (Public comments received:2; MUC ID: MUC16-056)
  
  
• Safe Use of Opioids – Concurrent Prescribing (Public comments received:4; MUC ID: MUC16-167)
  
  

• Communication about Pain During the Hospital Stay (Public comments received:3; MUC ID: MUC16-263)
  
  
• Communication about Treating Pain Post-Discharge (Public comments received:3; MUC ID: MUC16-264)
  
  

• Identification of Opioid Use Disorder (Public comments received:4; MUC ID: MUC16-428)
  
  
• Medication Continuation following Inpatient Psychiatric Discharge (No public comments received; MUC ID: MUC16-048)
  
  
• Medication Reconciliation at Admission (No public comments received; MUC ID: MUC16-049)
  
  

• Localized Prostate Cancer: Bowel function (No public comments received; MUC ID: MUC16-375)
  
  
• Localized Prostate Cancer: Sexual function (No public comments received; MUC ID: MUC16-377)
  
  
• Localized Prostate Cancer: Urinary Frequency, Obstruction, and/or Irritation (No public comments received; MUC ID: MUC16-379)
  
  
• Localized Prostate Cancer: Urinary Incontinence (No public comments received; MUC ID: MUC16-380)
  
  
• Localized Prostate Cancer: Vitality (No public comments received; MUC ID: MUC16-381)
  
  
• PRO utilization in in non-metastatic prostate cancer patients (Public comments received:2; MUC ID: MUC16-393)
  
  
• Proportion of patients who died from cancer admitted to hospice for less than 3 days (Public comments received:2; MUC ID: MUC16-274)
  
  
• Proportion of patients who died from cancer admitted to the ICU in the last 30 days of life (Public comments received:1; MUC ID: MUC16-273)
  
  
• Proportion of patients who died from cancer not admitted to hospice (Public comments received:3; MUC ID: MUC16-275)
  
  
• Proportion of patients who died from cancer receiving chemotherapy in the last 14 days of life (Public comments received:1; MUC ID: MUC16-271)
  
  

Full Comments (Listed by Measure)

• General comment-We were concerned that no measures were approved for either hospital acquired conditions or hospital readmissions per Appendix C. Although hospital readmissions are down this year, data indicates that 30% of pediatric readmissions are preventable (source: https://pediatrics.aappublications.org/content/early/2016/07/20/peds.2015-4182). Hospital acquired conditions data has improved as CMS notes “across the FY 2015 and FY 2016 programs, the average performance across eligible hospitals improved on two of the three measures included in both program years” (source: https://www.acep.org/Clinical---Practice-Management/Health-Care-Acquired---Provider-Preventable-Conditions-FAQ/.) Nevertheless, there is increasing awareness of “superbugs” and most hospital acquired infections by their very nature are preventable. Addressing this will decrease costs and improve health care outcomes. (Submitted by: Statewide Parent Advocacy Network/Family Voices NJ)
  
  
• · No quality measure should be publicly reported without having been collected and reported in the same fashion and subject to the same processes as a HEDIS first year measure. · Any publicly reported quality measure must at least meet the NQF criteria for measure endorsement. The NQF criteria require the measure be: o Important to measure and report, where the evidence is highest that measurement can have a positive impact on healthcare quality. o Scientifically acceptable, so that the measure when implemented will produce consistent (reliable) and credible (valid) results about the quality of care. o Useable and relevant to ensure that intended users — consumers, purchasers, providers, and policy makers — can understand the results of the measure and are likely to find them useful for quality improvement and decision making. o Feasible to collect with data that can be readily available for measurement and retrievable without undue burden." · Performance reports aimed at consumers must be displayed in a way that is easily understood by a consumer. Performance reports developed for clinicians would require a different, more detailed format. (Submitted by: Kaiser Permanente)
  
  
• Asking whether or not a patient received pain medication during their visit automatically ensures negative responses in many cases. These questions should focus on pain assessment and treatment in general, not on the prescribing of medication. (Submitted by: Community Health Network)
  
  
• Centers for Medicare & Medicaid Services Department of Health and Human Services Mail Stop C4-26-05 Baltimore, MD 21244-8050 Re: MAP Pre-Rulemaking 2016-2017: Comment on Measures Under Consideration CVS Health is pleased to provide comments in response to the Centers for Medicare & Medicaid Services (CMS) request for comments on the list of Measures Under Consideration (MUC) for NQF’s Measure Applications Partnership (MAP), which provides input to HHS and private sector initiatives on measures for use in public reporting, performance-based payment, and other programs. CVS Health is a pharmacy innovation company helping people on their path to better health. Through its more than 7,900 retail drugstores, more than 1,000 walk-in medical clinics, a leading pharmacy benefits manager with more than 70 million plan members, a dedicated senior pharmacy care business serving more than one million patients per year, and expanding specialty pharmacy services, the Company enables people, businesses and communities to manage health in more affordable, effective ways. This unique integrated model increases access to quality care, delivers better health outcomes and lowers overall health care costs. The Pharmacy Services Segment provides a full range of pharmacy benefit management (PBM) services to our clients consisting primarily of employers, insurance companies, unions, government employee groups, managed care organizations (MCOs) and other sponsors of health benefit plans and individuals throughout the United States. Background The Centers for Medicare & Medicaid Services (CMS) issued the List of Measures under Consideration (MUC) to comply with Section 1890A(a)(2) of the Social Security Act (the Act), which requires the Department of Health and Human Services (DHHS) to make publicly available a list of certain categories of quality and efficiency measures it is considering for adoption through rulemaking for the Medicare program. Among the measures, the list includes measures CMS is considering that were suggested to by the public. When organizations, such as physician specialty societies, request that CMS consider measures, CMS attempts to include those measures and make them available to the public so that the Measure Applications Partnership (MAP), the multistakeholder groups convened as required under 1890A of the Act, can provide their input on all potential measures and ensure alignment where appropriate. The list is larger than what will ultimately be adopted by CMS for optional or mandatory reporting programs in Medicare. CMS will continue its goal of aligning measures across programs. Measure alignment includes establishing core measure sets for use across similar programs, and looking first to existing program measures for use in new programs. Further, CMS programs must balance competing goals of establishing parsimonious sets of measures, while including sufficient measures to facilitate multispecialty provider participation. CVS Health Comments CVS Health appreciates the opportunity to provide comments, especially as it pertains to measures for inclusion in the the Merit-based Incentive Payment System (MIPS). PBMs, pharmacies, and pharmacists play an integral role in health quality outcomes. With the Medicare Access & CHIP Reauthorization Act (MACRA) moving health plans and health care providers into alternative payment models, pharmacists are in an important position within the value-based care transition to assist in quality metrics that have an emphasis on medication management and optimization of medication use. Providing comprehensive pharmacy care management services, such as immunization, diabetes, hypertension, high cholesterol management and medication reconciliation post inpatient discharge helps to drive population health and chronic disease management. Pharmacists have an important role in partnering with the health care team. Through the MIPS program CMS proposes that most MIPS-eligible clinicians would be required to report on at least six quality measures, including at least one cross-cutting measure and an outcome measure if available. Evidence supports that optimal prescription utilization has a positive impact on reducing the total cost of care, increasing patient safety and improving clinical outcomes. A successful MIPS strategy will be dependent on a clear definition of goals and measures to monitor the effectiveness of the value based approach. Prescription drugs have been shown to lower overall medical costs through reduced hospitalization, emergency room utilization and outpatient visits, while medication therapy management programs and pharmacy counseling play an important role in optimizing prescription adherence to improve quality outcomes for individuals with chronic conditions. Through the implementation of the Medicare Part D program, prescription coverage has been shown to reduce Medicare Parts A and B medical expenses for beneficiaries compared to those with no or limited prior drug coverage. Research conducted by CVS Health also indicates that investment in resources to improve drug adherence among Medicare Part D beneficiaries has been shown to lower overall medical costs through reduced hospitalization, emergency room utilization and outpatient visits. CVS Health encourages balance and parsimony in the selection of quality measures to monitor the quality performance. In pursuit of consistency, parsimony, and reducing the burden of measurement and reporting, the alignment of measures across federal programs should be an important health system priority. Alignment, or use of the same or related high value measures when appropriate, is a critical strategy for accelerating improvement in priority areas, reducing duplicative data collection and enhancing comparability and transparency of quality performance. CVS Health was encouraged by the alignment of MIPS measures with measures used in other government programs (e.g., Medicare STARS, Medicaid Core Sets, Health Insurance Marketplaces, etc.) when possible. Therefore we were pleased to see several pharmacy influenced measures proposed for MIPS, such as: • Antidepressant medication management • Medication management for people with Asthma • Medication reconciliation post-discharge and Management in Women who had a Fracture • Controlling high blood pressure, etc. CVS Health would like recommend the following measures that align with measures used in other Federal programs for inclusion: Measure Recommendations Rationale Proportion of Days Covered – 3 rates While measures such as “Documentation of Current Medications in the Medical Record” and “Medication Reconciliation Post-Discharge” are key indicators of high quality medication management, additional measures that assess medication adherence are necessary to ensure that patients are actually receiving the therapy they need. A strong case can be made for the importance of physician insight into their patients’ medication adherence enabling them to make informed decisions regarding therapeutic choices, and which could improve patient empowerment to take their medications. We would recommend the “Proportion of Days Covered (PDC) – three rates” measure be included in the MIPs due to its proven ability to help improve medication adherence and health outcomes in the Medicare Stars program. Proportion of Days Covered (PDC) is the Pharmacy Quality Alliance (PQA)-recommended metric for estimation of medication adherence for patients using chronic medications. This metric is also endorsed by the National Quality Forum (NQF). The metric identifies the percentage of patients taking medications in a particular drug class that have high adherence (PDC > 80% for the individual). The measure tracks medication adherence for conditions that are highly prevalent in Medicare-Medicaid populations. It includes three rates - one for blood pressure medications (renin angiotensin system antagonists [RASA]), one for cholesterol medications (statins), and one for diabetes medications (roll-up across 4 classes of oral diabetes drugs). A form of this measure is currently being used in Medicare STARS and the Health Insurance marketplaces. Inclusion in MIPS would allow further alignment across programs to promote consistent performance measurement where it can have the most impact and give a more complete view of the quality of care delivered across healthcare settings. Proportion of days covered: Antiretroviral adherence for HIV-specialists. Again, while the Prescription of HIV Antiretroviral Therapy measure is a key indicator of high quality medication management, evaluation of medication adherence is necessary to ensure that patients are actually receiving the therapy they need. Human immunodeficiency virus (HIV) can cause life-long infection that results in a chronic debilitating disease usually ending in death. Adherence to multiple anti-HIV medications has been shown to dramatically slow the progression of disease and prolong survival. This measure is used to assess the percentage of patients 18 years and older who filled a prescription for at least two individual antiretroviral drugs (as single agents or as a combination) on two unique dates of service who met the Proportion of Days Covered (PDC) threshold of 90% during the measurement period. Antiretroviral adherence is currently a Part D Patient Safety measure, reported monthly though the Acumen Patient Safety Analysis website. Rheumatoid Arthritis (RA): Disease Modifying Anti-Rheumatic Drug (DMARD) Therapy This measure is used to monitor the percentage of patients aged 18 years and older who were diagnosed with rheumatoid arthritis (RA) and were prescribed, dispensed, or administered at least one ambulatory prescription for a disease-modifying anti-rheumatic drug (DMARD). This measure calculates the percent of plan members with Rheumatoid Arthritis who got one or more prescription(s) for a DMARD, pivotal to long term treatment. Further, inclusion of the RA measure would align with the measure used in the Medicare STARS program. Antipsychotic Use in Persons with Dementia (APD) CMS has been particularly concerned with the unnecessary use of antipsychotic drugs particularly in nursing homes and, as a result, has pursued strategies to increase awareness of antipsychotic use in long term care settings. In 2013, CMS began to calculate a general atypical antipsychotic utilization rate, called Rate of Chronic Use of Atypical Antipsychotics by Elderly Beneficiaries in Nursing Homes, for inclusion in the Part D display measures. The average rates decreased from approximately 24.0% in 2011 to 21.4% in 2013. There continues to be increased attention on this important issue. The United States Government Accountability Office (GAO) released a report in January 2015 describing the inappropriate use of antipsychotics in Part D beneficiaries with dementia, in both community (i.e., outside of nursing homes) and long-stay nursing home residents during 2012, with Antipsychotic Drug Use. The GAO conducted this study due to concerns raised regarding the use of antipsychotic drugs to address the behavioral symptoms associated with dementia, the FDA’s boxed warning that these drugs may cause an increased risk of death when used by older adults with dementia, and because the drugs are not approved for this use. HHS has Initiatives to reduce use among older adults in nursing homes, but should consider expanding efforts to other settings. Further, inclusion would align with the Medicare display measure and Part D Patient Safety measure. Statin Use in Persons with Diabetes The American College of Cardiology/American Heart Association (ACC/AHA) guidelines recommend moderate- to high-intensity statin therapy for primary prevention for persons aged 40 to 75 years with diabetes. This measure is used to assess the percentage of patients ages 40 to 75 years who were dispensed a medication for diabetes that receive a statin medication. This measure is very much prescriber influenced and inclusion will align with the health care system goals. Further, inclusion of “Statin Use in Persons with Diabetes” would align with the Medicare display measure and Part D Patient Safety measure. Use of Opioids from Multiple Providers or at High Dosage in Persons Without Cancer CVS Health recommends the inclusion of all three measures. • Measure 1: Use of Opioids at High Dosage • Measure 2: Use of Opioids from Multiple Providers • Measure 3: Use of Opioids at High Dosage and from Multiple Providers Measure one can be directly influenced by providers while measure 3 would also align with the Medicaid adult core set measure adopted in 2016. These measures are currently Part D Patient Safety measures, reported monthly though the Acumen Patient Safety Analysis website. CVS Health appreciates the opportunity to provide comments to CMS. If you have any questions, please feel free to contact Emily Kloeblen at Emily.Kloeblen@cvshealth.com. Sincerely, Emily Kloeblen Director, Government Performance Measures CVS Health (Submitted by: CVS Health)
  
  
• I am not commenting by individual MUC but some general thoughts/concerns. I would still like to see us focus on strategy that drives us selecting the critical few measures that will build a healthy American and place them in the appropriate program where the responsibility lies verses in some of the inpatient measures where the patient is for such a short time and there really is no way the intervention will be sustained.I was concerned about the tobacco measures since I thought those were topped out and did not know why they were back in. Are the opiods in the correct program to be fully managed and see ongoing improvement of the user of the opiod? The EHR use for med rec in the behavioral health measure may not be feasible due to the lack of sophistication of the EHR in the behavioral world but the concept of the med rec is good. I also think that the cancer measures are a lot and have artificial boundaries for outpatient and inpatient. in this disease like many of the chronic illnesses it is about the patients treatment plan not the location of the care. I (Submitted by: coordinating committee)
  
  
• General Comments: The Federation of American Hospitals (FAH) appreciates the opportunity to provide comments on the Measures Under Consideration (MUC) list prior to the individual workgroup discussions and voting. The FAH believes that the Measures Application Partnership (MAP) should support only those measures that truly represent the quality of care provided within a hospital, physician or other provider. Any new measures added to these programs should focus on a targeted set of issues and topics, effectively leverage electronic health record systems and other health information technologies, and drive improvement in the overall delivery of patient care. In addition, we ask that the MAP be judicious in selecting measures where there is limited evidence that improvements (or lack thereof) on the process or outcome of interest are within the control of the measure entity (e.g., follow-up after hospitalization for mental illness) or where performance has proven to be generally high (e.g., the tobacco use measures). (Submitted by: Federation of American Hospitals )
  
  

• The Joint Commission developed and implemented TOB-1 as a chart-based measure that was developed for use in multiple care settings, in 2012. The Joint Commission strongly supports adoption of the eMeasure in the Hospital Inpatient Quality Reporting Program and for the Medicare and Medicaid EHR Incentive Program for Eligible Hospitals and Critical Access Hospitals. Comment: Tobacco use is the single greatest cause of disease in the United States today and accounts for over 400,000 deaths each year. Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, and many other diseases. Tobacco use creates a heavy cost to society as well as to individuals. The Joint Commission currently includes the chart-based measure TOB-1: Tobacco Use Screening in the Tobacco Treatment (TOB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This chart-based measure is currently being reported on by over 700 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. Additionally, The Joint Commission has been actively involved with the CMS subcontractor responsible for the retooling of this measure to an eMeasure. The pilot testing for the eMeasure is currently in process. (Submitted by: The Joint Commission)
  
  

• The Joint Commission developed and implemented TOB-2/2a as a chart-based measure that was developed for use in multiple care settings, in 2012. The Joint Commission strongly supports adoption of the eMeasure in the Hospital Inpatient Quality Reporting Program and for the Medicare and Medicaid EHR Incentive Program for Eligible Hospitals and Critical Access Hospitals. Comment: Tobacco use is the single greatest cause of disease in the United States today and accounts for over 400,000 deaths each year. Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, and many other diseases. Tobacco use creates a heavy cost to society as well as to individuals. There is strong and consistent evidence that tobacco dependence interventions significantly reduce the user's risk of suffering from tobacco-related disease and improve outcomes for those already suffering from a tobacco-related disease. Effective, evidence-based tobacco dependence interventions have been clearly identified and include brief clinician advice, individual, group, or telephone counseling, and use of FDA-approved medications. Hospitalization (both because hospitals are a tobacco-free environment and because patients may be more motivated to quit as a result of their illness) offers an ideal opportunity to provide cessation assistance that may promote the patient's medical recovery. Patients who receive even brief advice and intervention from their care providers are more likely to quit than those who receive no intervention. The Joint Commission currently includes the chart-based measure TOB-2: Tobacco Use Treatment Provided or Offered and TOB-2a: Tobacco Use Treatment, in the Tobacco Treatment (TOB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This measure is currently being reported on by over 700 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. Additionally, The Joint Commission has been actively involved with the CMS subcontractor responsible for the retooling of this measure to an eMeasure. The pilot testing for the eMeasure is currently in process. (Submitted by: The Joint Commission)
  
  

• We fully support and highly recommend the inclusion of MUC 16-052 (TOB 3 and Tob 3a) because smoking is the leading cause of morbidity and mortality in the United States. After identification of patients who use tobacco and provision of an evidence-based tobacco cessation treatment intervention during the hospitalization, the evidence-based tobacco cessation treatment intervention outlined in this measure is crucial to help people to continue and maintain the patient's quit attempt. Especially important is to take advantage of the patient's decision to make and initiate a quit attempt. (Submitted by: University of Wisconsin Center for Tobacco Research and Intervention)
  
  
• The Joint Commission developed and implemented TOB-3/3a as a chart-based measure that was developed for use in multiple care settings, in 2012. The Joint Commission strongly supports adoption of the eMeasure in the Hospital Inpatient Quality Reporting Program and for the Medicare and Medicaid EHR Incentive Program for Eligible Hospitals and Critical Access Hospitals. Comment: Tobacco use is the single greatest cause of disease in the United States today and accounts for over 400,000 deaths each year. Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, and many other diseases. Tobacco use creates a heavy cost to society as well as to individuals. There is strong and consistent evidence that tobacco dependence interventions significantly reduce the user's risk of suffering from tobacco-related disease and improve outcomes for those already suffering from a tobacco-related disease. Effective, evidence-based tobacco dependence interventions have been clearly identified and include brief clinician advice, individual, group, or telephone counseling, and use of FDA-approved medications. Hospitalization (both because hospitals are a tobacco-free environment and because patients may be more motivated to quit as a result of their illness) offers an ideal opportunity to provide cessation assistance that may promote the patient's medical recovery. Patients who receive even brief advice and intervention from their care providers are more likely to quit than those who receive no intervention. The Joint Commission currently includes the chart-based measure TOB-3: Tobacco Use Treatment Provided or Offered at Discharge and TOB-3a: Tobacco Use Treatment at Discharge, in the Tobacco Treatment (TOB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This measure is currently being reported on by over 700 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. Additionally, The Joint Commission has been actively involved with the CMS subcontractor responsible for the retooling of this measure to an eMeasure. The pilot testing for the eMeasure is currently in process. (Submitted by: The Joint Commission)
  
  
• We thank NQF for including this activity. According to the CDC, smoking among people with mental illness is 75 percent more prevalent than in those without. A third of all cigarettes manufactured are smoked by people with mental illness. Also, people with severe mental illness have a markedly shorter life expectancy, due in part to the consequences of smoking. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  

• Improving flu vaccination rates would add value and improve outcomes. Our hospital currently screens and vaccinates patients, so this may be a mild reporting burden for us. However, I am not sure what the policies are for other hospitals. If there are hospitals who do not already perform this service, then I think that it should be done, and the benefits of having a program would outweigh the reporting requirements. (Submitted by: The Society for Healthcare Epidemiology of America)
  
  

• MUC16-55 Median time ER arrival to departure. Have concerns as we work to address issues with patients and looking at alternatives to hospitalization, ER providers will be pressured by this metric to admit patients. Even if we looking at median, these patients will adversely impact these numbers thus discouraging the work. (Submitted by: Banner Health)
  
  
• Overcrowding is a known problem. However, judging EDs on median time to discharge is a misguided attempt to tackle it. Overcrowding is rarely due to patients who are evaluated, treated, and discharged from the ED. Rather, a large component is boarding of admitted patients. A physician who comes to work to find that 75% of her ED beds are occupied by boarding patients will have longer median to discharge than her colleague working in an ED with < 10% of her beds occupied by boarding patients. Why would CMS want to judge her performance based on those factors? While doing so might cause her hospital administration to address boarding, which would be positive, the more valuable metric for assessing overcrowding would be to measure median time to inpatient bed for admitted patients. Most importantly, this measure prioritizes speed above safety. When EDs are being evaluated by speed and not quality of care, patients will be subjected to unnecessary testing and unnecessary admission. CMS has an interest in decreasing unnecessary admissions. A measure that rates hospitals on median time to discharge of ED patients will certainly cause ED providers to “just admit” that patient who has been in the department for a bit longer than anticipated, perhaps for example, for serial abdominal examinations (in an attempt to avoid an unnecessary CT scan, or admission.) In a world in which we are judged by median disposition time, indeed who would have time for serial abdominal exams? No, we will just CT scan everyone and admit many of them. Our need for speed will lead to far more patients being exposed to radiation and the dangers associated with hospital admission. Who will have time for to wait for a 2nd troponin and discharge a patient with very low risk for acute coronary syndrome? No, we will get one troponin and admit them all. For departments without observation units, who will have time for anything other than immediate triage? Another problem: My department does something wonderful for society; it goes to great effort to find psychiatric beds at other hospitals for voluntary psychiatric admissions because these patients have no place else to go. Until an accepting facility has been identified, these patients have no disposition. Such a program would be in jeopardy because it would absolutely destroy our median disposition time. When speed is a priority over care, our society's last safety net will become even less safe. This measure would also be tremendously unfair to hospitals that do not have as many observation beds (or any.) Perhaps such a measure would cause administrations to give us more resources. That would be welcome. But more likely, it will lead to finger pointing towards the ED (which is often not the source of the problem), a reduction in services for our patients, and over-testingand overadmitting in others. CMS should take up the issue of over-crowding in EDs. But this approach is dead on arrival. It should be removed and a new measure should be developed in collaboration by stakeholder groups such as ACEP and perhaps the Society of Hospital Medicine. (Submitted by: Emergency Physician (these are not comments on behalf of any organization) )
  
  
• Finally, it has been established that overcrowding in the emergency department often depends on factors outside the ED (bed availability inpatient, OR schedules). Overcrowding directly affects our ability to discharge patients in a timely manner. Implementing this measure will lead to a situation in which the ED is held to a metric that it does not have full control over. While the Emergency Departments always work outside departments regarding flow, the motivation of these outside department to change to improve ED time to discharge will be less to, as it does not affect their own metrics, but only the EDs. (Submitted by: Lincoln Medical Center )
  
  
• Appropriate stratification has to be considered in order to meaningfully compare like organizations. Comparing a large urban public teaching institution's median ED LOS for discharged patients to a small rural private for-profit facility's ED LOS doesn't hold much value. Consider how different just their population of patients are, the types of complaints, baseline health status and access, etc. (Submitted by: San Francisco General Hospital)
  
  
• While I support data transparency, and think time to discharge is an important metric that most EDs already collect, I do worry about a couple unintended side effects of this potential measure. Could we learn from England's 4 hour rule? I do get worried about the potential for providers to stop taking time for serial abdominal exams, and just CT scanning more individuals; or not taking time for a 2nd troponin and discharging of low-risk CP, but rather only getting one troponin and admit such patients in order to get a 'better discharge LOS metric'. I work in an ED without an observation unit, with many patients with substance abuse issues and mental illness that do require observation before they are sober. I could see our safety-net EDs, or EDs with high substance abuse, or EDs without observation units being perceived as poor performers on this metric, and then subsequently being penalized if CMS attaches pay-for-performance incentives or places the data on Hospital Compare. Regardless, I do think this is an important concept/metric, but would recommend the measure creators to incorporate risk-adjustment and to consider how to craft the metric in a way that avoids/mitigates the chance of unintended consequences. (Submitted by: Zuckerberg San Francisco General Hospital; San Francisco Health Network)
  
  
• Under the Affordable Care Act, the CMS ruling making process requires a comment period for all measures under consideration during the “measure implementation” part of a measure lifecycle. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures/Pre-Rule-Making.html A comment period would seem to fail to comply with federal law if public-facing information (by either CMS or the NQF) failed to provide accurate information about a proposed measure; without accurate information, the public and other stakeholders would be unable to meaningfully participate. In such an instance, a proposed measure would fail to comply with the requirements in the Affordable Care Act. Such appears to be the case with MUC16-55.  All of the materials in the December 1, 2016 MAP state that measure MUC16-55 was never approved by the NQF (http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=83923) and (http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=83924). Therefore the information on this proposed measure is nowhere to be found for members of the public and stakeholders wishing to provide input (which is a legally required opportunity.) As I was curious as to what the provisions of MU16-55 were, I searched for further information, which I could not initially find. However, several individuals more familiar with MUC16-55 told me that indeed the proposed measure is based upon NQF 496. Unless I had emailed them asking for more information about the proposed measure, I never would have known this. The published list of measures under consideration (Dec 1, 2016; see links above) states that MUC16-55 is "fully developed," but was never approved by the NQF and has no NQF ID number in the JIRA. And yet those I spoke to who were more familiar with the inside processes said this was not true, and that MUC16-55 was indeed NQF approved and its provisions and rationale can be found on the NQF website by searching for NQF 496. How can the public comment on a measure when even health policy professionals do not agree about the facts about what it says, who developed it, who wrote it, who endorsed it, and who validated it? Even now, I do not know whether MUC16-55 is directly related to NQF 496, or not. I must not be alone.   I believe this discrepancy between public-facing information and the MUC16-55’s actual origin and history renders it non-complaint with CMS’s implementation of the Affordable Care Act rule making process. Because there is no time to give the public correct information on this—and therefore to provide important input that is required under the federal law known as the Affordable Care Act—I believe this proposed rule under consideration must be withdrawn from this year’s measure cycle. (Submitted by: self)
  
  
• I applaud NQF's interest in issues related to care in the nation's emergency departments, and wish to share two points about this proposal. Prompt treatment is vital to patient safety. However, door to discharge time is a poor measure of adequacy of care, and in fact, emphasis on “good” (meaning rapid) turnaround times may be counter to NQF’s and the patient’s interest. Emergency medicine is rapidly changing, and extensive evaluations and treatments have, in many cases, served to stabilize and diagnose patients, eliminating the need for hospital admission. This takes time. Examples include TIA, syncope, and chest pain. As an example, our previous practice was to admit many chest pain patients for further inpatient evaluation. Such patients would rapidly move through the ED to the inpatient unit, with a typical length of ED stay of 2-3 hours (i.e. what the measure would call “good”). With a chest pain “rule out” protocol similar to ones adopted in many emergency departments, we have avoided admitting well over 1000 patients per year. However, this comes at an expense - time. To do such a rule out typically takes 8-10 hours (compared to what was typically a 2 day admission). In short, much of the inpatient workup which used to take several days has spilled into the emergency department, but requires a significant increase in ED LOS. I view this, as do many, as a major step forward in patient care, safety, satisfaction, and cost containment. The response to a door to discharge measure will encourage hospitals to reverse this trend, either by admitting the patient or placing all patients whose ED LOS is greater than a few hours on observation, at great cost and less optimal care for the patient. My second point is regarding a greater concern. The introduction of ED measures was in part an effort by CMS to focus attention on ED crowding and throughput. We applaud the interest in this issue. I am concerned, however, that we are measuring the wrong thing. The medical literature has thoroughly documented that ED crowding is, in large part, driven by boarding of admitted patients in the ED due to lack of hospital capacity. Boarding of admitted patients has been clearly associated with delays in care, sentinel events, increased medical error, and increased mortality. To focus attention on ED flow rather than hospital flow focuses on where the problem may sit, but not where the problem is. Boarding is the single most important impediment to ED flow, and I would please that boarding be the focus of any measure. It’s important to note that there are known fixes to this problems, including smoothing the scheduling of elective admissions; early discharge of patients; and enhanced weekend discharges. All have been shown to dramatically decrease boarding, decrease hospital length of stay, improve patient safety, and decrease cost. They do not require additional resources or costs, but they do require leadership and will. Equally important, although there is an entire industry of quality improvement, no other interventions (other than costly expansion) have been shown to be effective at addressing hospital capacity and flow. None. Small “improvements” simply are not of sufficient scale to address this issue. One institution recently looked at why patients waited more than an hour to get in a room to be seen in the ED. They wanted to see how much was due to “being too busy” vs. lack of space due to boarding. Here are the results. Of 100,000 visits, 16,800 patients waited over an hour for a room because of lack of space. The the number waiting for a room 1+ hour was exceeded by the number boarding by 19. Had those boarders not been present, there would have been readily available space for the patient. In contrast, the number who waited more than an hour because of “being too busy” (i.e. not explained by boarding) was 253 of the 16,800 patients. Clearly, in this setting, boarding is the driving force for inadequate space to see a patient in a timely fashion. Emergency departments throughout the country have had to jury-rig “solutions” to this problem by moving providers out the triage and treating people in the waiting room. It is a sad commentary on our practice that this is considered a “solution”. I would plead that the focus of NQF be on boarding, not ED turnaround time. We need to place our focus on the most serious problem endangering the care of emergency patients: boarding of admissions in the ED. If I can be of any help in further explaining my comments or sharing my concerns, I would be happy to help in any way possible. Thank you. (Submitted by: Stony Brook University Medical Center)
  
  

• Adventist Health System is concerned about the consideration of this measure. While we support further development of this important measure topic, we strongly recommend that the NQF Measure Applications Partnership avoid any indication of approval of this measure, conditional or otherwise, prior to the completion of a full NQF evaluation. It is our view that measures must achieve NQF endorsement before they can be recommended for use in federal programs. We believe this is the best way to ensure that quality measures used in federal programs meet the highest standards of validity, reliability and science. (Submitted by: Adventist Health System)
  
  
• CAPC recommends the use of this measure for the HOQR program. (Submitted by: Center to Advance Palliative Care)
  
  

• The AAMC opposes inclusion of this measure in the IQR program. In the materials, CMS did not provide an explanation as to how providers would be assessed under this measure. While we support reduction in smoking prevalence, we question whether it is appropriate to hold providers accountable for activity that is largely outside of their control. In addition, it is unclear as to how this measure would be applied and adjusted to account for factors, such as age, race/ethnicity, education, socioeconomic status, and geographic region. Before any new measure is submitted for inclusion in the IQR program, CMS and the MAP should ensure that the measure’s value added is greater than the burden required to collect and submit such data. (Submitted by: Association of American Medical Colleges)
  
  

• This measure is still in development, and therefore we believe its inclusion on the MUC List is premature. Testing to support its specifications and risk adjustment models is not yet complete. We would welcome consideration of this measure at some point in the future, after the results and analysis of testing have been made available to the measure developer’s Technical Expert Panel and to the public. We also believe the developers should directly assess the validity of the measure through pilot testing at ASCs to ensure that the measure does not inappropriately penalize centers with a more complex case mix. Given that the measure is still in development, it is not possible for the MAP to arrive at an informed decision regarding its merits at this point in time. We support a “Refine and Resubmit” recommendation, which we believe is the only rational option currently available to the Hospital Workgroup. (Submitted by: ASC Quality Collaboration)
  
  

• This measure is also still in development, and therefore we believe its inclusion on the MUC List is premature. Testing to support its specifications and risk adjustment models is not yet complete. We would welcome consideration of this measure at some point in the future, after the results and analysis of testing have been made available to the measure developer’s Technical Expert Panel and to the public. As with the related orthopedic measure, we believe the developers should directly assess the validity of the measure through pilot testing at ASCs to ensure that the measure does not inappropriately penalize centers with a more complex case mix. Given that the measure is still in development, it is not possible for the MAP to arrive at an informed decision regarding its merits at this point in time. We support a “Refine and Resubmit” recommendation, which we believe is the only rational option currently available to the Hospital Workgroup. (Submitted by: ASC Quality Collaboration)
  
  

• The ASC Quality Collaboration supports this measure and believes the MAP Hospital Workgroup should issue a “Support for Rulemaking” recommendation. The measure focuses on a significant surgical outcome and could fill an identified measure gap in the ASCQR Program. The measure is fully developed and tested and is already being used for public reporting by ASCs in selected States. The measure is being considered by the NQF for endorsement. Although MAP Measure Selection Criterion #1 states, “NQF-endorsed measures are required for program measure sets, unless no relevant endorsed measures are available to achieve a critical program objective,” we believe NQF endorsement is, in fact, not required. We base this on a direct reading of the Social Security Act, with corroboration from CMS, which has repeatedly stated NQF endorsement of measures is not required. A recent example of such a statement in rulemaking asserted, “…section 1833(t)(17)(C)(i) of the Act does not [emphasis added] require that each measure CMS adopts for the ASCQR Program be endorsed by a national consensus building entity, or the NQF specifically. Further, under section 1833(i)(7)(B) of the Act, section 1833(t)(17)(C)(i) of the Act applies to the ASCQR Program, except as the Secretary may otherwise provide. Under this provision, the Secretary has further authority to adopt non-endorsed measures. While we strive to adopt NQF-endorsed measures when possible, we believe the requirement that measures reflect consensus among affected parties can be achieved in other ways, including through the measure development process, through broad acceptance and use of the measure, and through public comments.” (81 FR 79808, November 14, 2016) (Submitted by: ASC Quality Collaboration)
  
  

• CAPC does not recommend this measure for inclusion in the HIQR, HOQR, and EHR Incentive/EH/CAH programs. We understand the need for measures that will help address the epidemic of opioid overdose fatalities, but are concerned that this particular measure has not been fully tested and could result in significant unintended consequences. There are a number of seriously ill patients who do not have cancer or are not receiving palliative care for whom concurrent opioid and benzodiazepine prescriptions are clinically appropriate. It is important that physicians caring for these patients have the autonomy to make medication determinations without concern of blanket financial repercussions. (Submitted by: Center to Advance Palliative Care)
  
  
• M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. With this in mind M3 recommends the endorsement by NQF of NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC16-167 (safe use of opioids) – M3 applauds the attention to the opioid epidemic through addressing unintentional opioid overdoses. M3 recommends continued patient follow-up through routine screening and measurement with a multidimensional mental health and substance use disorder tool. This would identify individuals continuing to use opioids who may have other underlying mental health diagnoses exacerbated by the opioid use. One tool with multiple cloud based screens and measures decreases the clinical workflow burden. The challenge is for NQF to endorse NQF-2620. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  

• This should be measured at the physician practice level as well. Most concurrent prescriptions continue chronically at the primary care level. (Submitted by: Community Health Network)
  
  
• The National Coalition for Hospice and Palliative Care, comprised of eight national organizations representing the hospice and palliative care field, does not recommend this measure for inclusion in the HIQR, HOQR, and EHR Incentive/EH/CAH programs. We understand the need for measures that will help address the epidemic of opioid overdose fatalities, but are concerned that this particular measure has not been fully tested and could result in significant unintended consequences. There are a number of seriously ill patients who do not have cancer or are not receiving palliative care for whom concurrent opioid and benzodiazepine prescriptions are clinically appropriate. It is important that physicians caring for these patients have the autonomy to make medication determinations without concern for punitive financial repercussions. (Submitted by: National Coalition for Hospice and Palliative Care)
  
  
• CAPC does not recommend this measure for inclusion in the HIQR, HOQR, and EHR Incentive/EH/CAH programs. We understand the need for measures that will help address the epidemic of opioid overdose fatalities, but are concerned that this particular measure has not been fully tested and could result in significant unintended consequences. There are a number of seriously ill patients who do not have cancer or are not receiving palliative care for whom concurrent opioid and benzodiazepine prescriptions are clinically appropriate. It is important that physicians caring for these patients have the autonomy to make medication determinations without concern of blanket financial repercussions. (Submitted by: Center to Advance Palliative Care)
  
  
• AAHPM does not recommend this measure for inclusion in the HIQR, HOQR, and EHR Incentive/EH/CAH programs. We understand the need for measures that will help address the epidemic of opioid overdose fatalities, but are concerned that this particular measure has not been fully tested and could result in significant unintended consequences. There are a number of seriously ill patients who do not have cancer or are not receiving palliative care for whom concurrent opioid and benzodiazepine prescriptions are clinically appropriate. Similarly, such seriously ill patients might also appropriately benefit from concurrent opioid prescriptions (e.g. long-acting scheduled and short-acting for breakthrough pain). It is important that physicians caring for these patients have the autonomy to make individualized clinical decisions with regard to medication determinations without concern of blanket financial repercussions. (Submitted by: American Academy of Hospice and Palliative Medicine)
  
  

• The Joint Commission developed and implemented this measure that was developed for use in multiple care settings, in 2012. The Joint Commission strongly supports adoption of this measure in the Hospital Inpatient Quality Reporting Program. Comment: Excessive use of alcohol and drugs has a substantial harmful impact on health and society in the United States. It is a drain on the economy and a source of enormous personal tragedy. Patients with substance-use problems have a greater risk for serious injury and other medical problems. Clinical trials have demonstrated that brief interventions, especially prior to the onset of addiction, significantly improve health and reduce costs. Studies have demonstrated that there is a gap in care respecting patients with addiction who are referred for treatment. Hospitalization provides a prime opportunity to address the entire spectrum of substance use problems within the health care system. The Joint Commission currently includes SUB-2: Patients who screened positive for unhealthy alcohol use who received or refused a brief intervention during the hospital stay and 2a: Patients who received the brief intervention during the hospital stay in the Substance Use (SUB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This measure is currently being reported on by over 160 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. (Submitted by: The Joint Commission)
  
  
• M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. M3 recommends MUC adopt NQF-2620. With this in mind M3 recommends the endorsement by NQF of NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC16-178 (alcohol brief intervention) – excessive alcohol use has a significant harmful effect on an individual’s health, health care system, society and the economy. Alcohol and other substance use disorders should be routinely addressed by clinicians across all health care settings and done in a non-stigmatizing way. Serial screening and measurement provide tools for clinicians to understand recidivism, an essential part of the equation. M3 recommends continued patient follow-up through routine screening, measurement and treatment which can be accomplished through one cloud based patient rated tool that decreases the clinical workflow burden. The challenge is for NQF to endorse NQF-2620. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  
• Dear Colleagues, Given the importance of eMeasures in the delivery of healthcare I was to share the below with you. HHS (under contracts, first with ASPE and now with SAMHSA) is in the process of retooling the Joint Commission (TJC) measures SUD-1, SUD-2 and SUD-3 (i.e., MUC 16-178, -179 and -180) for use as eMeasures. Given that these measures are already required for the Medicare Inpatient Psychiatric Facility (IPF) Quality Reporting program ASPE and SAMHSA coordinated with IPF CMS staff on this effort. The initial ASPE contract (in partnership with SAMHSA) was for the re-specification work and Alpha testing; TJC staff served on the TEP for this work. ASPE also submitted the re-specified SUD eMeasures to CMS’s eMeasure contractor (Miter) for their specification review. In late September, 2016 this eMeasure project transitioned to a SAMHSA contractor for the Beta testing work, etc.; SAMHSA plans to continue involving TJC on their new TEP. Hope this helps in your evaluations. D.E.B. Potter, Office of the Assistant Secretary for Planning and Evaluation (ASPE) and Ex-Officio Member of the MAP Dual Eligible Workgroup cc: Lisa Patton, Substance Abuse and Mental Health Services Administration (SAMHSA) and Ex-Officio Member of the MAP PAC/LTC Workgroup (Submitted by: Office of the Assistant Secretary for Planning and Evaluation (ASPE))
  
  

• The Joint Commission developed and implemented this measure that was developed for use in multple care settings, in 2012. The Joint Commission strongly supports adoption of this measure in the Hospital Inpatient Quality Reporting Program. Comment: Excessive use of alcohol and drugs has a substantial harmful impact on health and society in the United States. It is a drain on the economy and a source of enormous personal tragedy. Patients with substance-use problems have a greater risk for serious injury and other medical problems. The Joint Commission currently includes SUB-1: Alcohol Use Screening in the Substance Use (SUB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This measure is currently being reported on by over 160 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. (Submitted by: The Joint Commission)
  
  
• M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. M3 recommends MUC adopt NQF-2620. With this in mind M3 recommends the endorsement by NQF of NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC16-179 – excessive alcohol use has a significant harmful effect on an individual’s health, health care system, society and the economy. Alcohol and other substance use disorders should be routinely addressed by clinicians across all health care settings and done in a non-stigmatizing way. Serial screening and measurement provide tools for clinicians to understand recidivism, an essential part of the equation. M3 recommends continued patient follow-up through routine screening, measurement and treatment which can be accomplished through one cloud based patient rated tool that decreases the clinical workflow burden. The challenge is for NQF to endorse NQF-2620. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  
• It is well established that behavioral health disorders are the largest cost driver in the US with a price tag of over $200 billion annually (Roehring, C Hlth Aff 2016 35 (6)). Annual anxiety prevalence is 18% which is greater than that of depression at 6.6% annually (NIMH 2016 https://www.nimh.nih.gov/health/statistics/index.shtml). In the Department of Health and Human Services’ (HHS) Top 20 High-Impact Medicare Conditions Crosswalk (2015 National Impact Assessment of CMS Quality Measures Report) major depression is ranked number one. This HHS report lists cardiovascular, diabetes, cerebrovascular, and cancer as the next highest high-impact disorders. Thirty-five percent of patients with chronic medical conditions have a mental illness (2014 Milliman Report for the American Psychiatric Association). The underdiagnosed and undertreated mental health disorders in these high-impact categories should be expanded, addressing these unmet patient needs in order to improve outcomes, decrease costs and improve the experience of patients. There should be a national imperative to diagnose and treat these conditions in primary and specialty care considering the prevalence and comorbidity with chronic medical conditions. Use of multidimensional mental health screens that provide measures can drive the healthcare system to higher performance and can be accomplished through minimal disruption in clinical workflow. M3 recommends the adoption of measures that incentivize comprehensive assessment of a patient’s risk for a behavioral health condition and fit seamlessly into the physician workflow. M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. With this in mind M3 recommends NQF endorse multidimensional measures similar to NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC16-179 – excessive alcohol use has a significant harmful effect on an individual’s health, health care system, society and the economy. Alcohol and other substance use disorders should be routinely addressed by clinicians across all health care settings and done in a non-stigmatizing way. Serial screening and measurement provide tools for clinicians to understand recidivism, an essential part of the equation. M3 recommends continued patient follow-up through routine screening, measurement and treatment which can be accomplished through one cloud based patient rated tool that decreases the clinical workflow burden. The challenge is the lack of multidimensional measures. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  
• Dear Colleagues, Given the importance of eMeasures in the delivery of healthcare I was to share the below with you. HHS (under contracts, first with ASPE and now with SAMHSA) is in the process of retooling the Joint Commission (TJC) measures SUD-1, SUD-2 and SUD-3 (i.e., MUC 16-178, -179 and -180) for use as eMeasures. Given that these measures are already required for the Medicare Inpatient Psychiatric Facility (IPF) Quality Reporting program ASPE and SAMHSA coordinated with IPF CMS staff on this effort. The initial ASPE contract (in partnership with SAMHSA) was for the re-specification work and Alpha testing; TJC staff served on the TEP for this work. ASPE also submitted the re-specified SUD eMeasures to CMS’s eMeasure contractor (Miter) for their specification review. In late September, 2016 this eMeasure project transitioned to a SAMHSA contractor for the Beta testing work, etc.; SAMHSA plans to continue involving TJC on their new TEP. Hope this helps in your evaluations. D.E.B. Potter, Office of the Assistant Secretary for Planning and Evaluation (ASPE) and Ex-Officio Member of the MAP Dual Eligible Workgroup cc: Lisa Patton, Substance Abuse and Mental Health Services Administration (SAMHSA) and Ex-Officio Member of the MAP PAC/LTC Workgroup (Submitted by: Office of the Assistant Secretary for Planning and Evaluation (ASPE))
  
  

• The Joint Commission developed and implemented this measure that was developed for use in multiple care settings, in 2012. The Joint Commission strongly supports adoption of this measure in the Hospital Inpatient Quality Reporting Program. Comment: Excessive use of alcohol and drugs has a substantial harmful impact on health and society in the United States. It is a drain on the economy and a source of enormous personal tragedy. Patients with substance-use problems have a greater risk for serious injury and other medical problems. Clinical trials have demonstrated that brief interventions, especially prior to the onset of addiction, significantly improve health and reduce costs. Studies have demonstrated that there is a gap in care respecting patients with addiction who are referred for treatment. Hospitalization provides a prime opportunity to address the entire spectrum of substance use problems within the health care system. The Joint Commission currently includes SUB-3: Patients who are identified with alcohol or drug use disorder who receive or refuse at discharge a prescription for FDA-approved medications for alcohol or drug use disorder, OR who receive or refuse a referral for addictions treatment and 3a: Patients who are identified with alcohol or drug disorder who receive a prescription for FDA-approved medications for alcohol or drug use disorder OR a referral for addictions treatment in the Substance Use (SUB) core measure set as an option for selection in their ORYX performance measurement reporting program. The Joint Commission’s ORYX® initiative integrates outcomes and other performance measurement data into the accreditation process. ORYX measurement requirements are intended to support Joint Commission-accredited organizations in their quality improvement efforts. In addition, these measures are reported on Quality Check® which is the Joint Commission’s public website that allows consumers to: search for accredited and certified organizations by city and state, by name or by zip code (up to 250 miles); find organizations by type of service provided within a geographic area; download free hospital performance measure results; and, print a list of Joint Commission certified disease-specific care programs and health care staffing firms. This measure is currently being reported on by over 160 health care organizations. The Joint Commission continuously monitors and revises their core performance measures based on feedback from the field in order to clarify measure specifications. There have been no reports of difficulty implementing this measure. (Submitted by: The Joint Commission)
  
  
• It is well established that behavioral health disorders are the largest cost driver in the US with a price tag of over $200 billion annually (Roehring, C Hlth Aff 2016 35 (6)). Annual anxiety prevalence is 18% which is greater than that of depression at 6.6% annually (NIMH 2016 https://www.nimh.nih.gov/health/statistics/index.shtml). In the Department of Health and Human Services’ (HHS) Top 20 High-Impact Medicare Conditions Crosswalk (2015 National Impact Assessment of CMS Quality Measures Report) major depression is ranked number one. This HHS report lists cardiovascular, diabetes, cerebrovascular, and cancer as the next highest high-impact disorders. Thirty-five percent of patients with chronic medical conditions have a mental illness (2014 Milliman Report for the American Psychiatric Association). The underdiagnosed and undertreated mental health disorders in these high-impact categories should be expanded, addressing these unmet patient needs in order to improve outcomes, decrease costs and improve the experience of patients. There should be a national imperative to diagnose and treat these conditions in primary and specialty care considering the prevalence and comorbidity with chronic medical conditions. Use of multidimensional mental health screens that provide measures can drive the healthcare system to higher performance and can be accomplished through minimal disruption in clinical workflow. M3 recommends the adoption of measures that incentivize comprehensive assessment of a patient’s risk for a behavioral health condition and fit seamlessly into the physician workflow. M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. With this in mind M3 recommends NQF endorse multidimensional measures similar to NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC16-180 – excessive alcohol use has a significant harmful effect on an individual’s health, health care system, society and the economy. Alcohol and other substance use disorders should be routinely addressed by clinicians across all health care settings and done in a non-stigmatizing way. Serial screening and measurement provide tools for clinicians to understand recidivism, an essential part of the equation. M3 recommends continued patient follow-up through routine screening, measurement and treatment which can be accomplished through one cloud based patient rated tool that decreases the clinical workflow burden. The challenge is the lack of multidimensional measures. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  
• Dear Colleagues, Given the importance of eMeasures in the delivery of healthcare I was to share the below with you. HHS (under contracts, first with ASPE and now with SAMHSA) is in the process of retooling the Joint Commission (TJC) measures SUD-1, SUD-2 and SUD-3 (i.e., MUC 16-178, -179 and -180) for use as eMeasures. Given that these measures are already required for the Medicare Inpatient Psychiatric Facility (IPF) Quality Reporting program ASPE and SAMHSA coordinated with IPF CMS staff on this effort. The initial ASPE contract (in partnership with SAMHSA) was for the re-specification work and Alpha testing; TJC staff served on the TEP for this work. ASPE also submitted the re-specified SUD eMeasures to CMS’s eMeasure contractor (Miter) for their specification review. In late September, 2016 this eMeasure project transitioned to a SAMHSA contractor for the Beta testing work, etc.; SAMHSA plans to continue involving TJC on their new TEP. Hope this helps in your evaluations. D.E.B. Potter, Office of the Assistant Secretary for Planning and Evaluation (ASPE) and Ex-Officio Member of the MAP Dual Eligible Workgroup cc: Lisa Patton, Substance Abuse and Mental Health Services Administration (SAMHSA) and Ex-Officio Member of the MAP PAC/LTC Workgroup (Submitted by: Office of the Assistant Secretary for Planning and Evaluation (ASPE))
  
  

• The AAMC opposes inclusion of this measure in the IQR program at this time. The Hospital-Wide Mortality measure is incomplete and still under development. Members of the MAP do not have sufficient information in which to determine its appropriateness for the IQR program. Until the measure is fully developed, considered for SES adjustment, and reviewed by the NQF, it should not be included in any quality programs. CMS should withdraw the measure until that time. (Submitted by: Association of American Medical Colleges )
  
  
• GYNHA opposes including the Hospital-Wide Risk-Standardized Mortality (MUC16-260) measure in HIQR partly because this measure is not fully developed, even though the Excel file that lists the 2016 measures under consideration says that it is. The measure developer, YNHHS/CORE, put preliminary specifications out for comment in October 2016, and comments are not due until December 14, 2016. YNHHS/CORE will complete development of this measure based on the comments it receives and will then put fully-developed specifications out for a second round of comments. The other reason we oppose this measure is that we do not believe that only 15 service line divisions can provide adequate risk adjustment. For example, the risk of mortality from heart attack and heart failure is estimated from a single regression model for the non-surgical cardiac division in the hospital-wide mortality measure, even though: 1) certain risk factors (i.e., AMI) have opposite effects on mortality in YNHHS/CORE’s separate heart attack and heart failure condition-specific models; 2) other risk factors (i.e., coronary atherosclerosis and other heart disease) have quite dissimilar effects on mortality in the condition-specific models; and 3) other risk factors (e.g., diabetes and stroke) that are omitted from the hospital-wide measure have significant effects on mortality in the condition-specific models. We will share these and other concerns with YNHHS/CORE. (Submitted by: Greater New York Hospital Association)
  
  
• This measure is consistent with MUC 16-274 and MUC 16-275 in encouraging hospice care for cancer patients. We encourage the exploration of expanding the types of diagnoses excluded from the hospital-wide risk standardized mortality measure to encompass more appropriate use of hospice care for beneficiaries. We further encourage extension of the metric to 48 hours/2 days of the index admission. Limiting the exclusion to the first day of the index admission does not allow for the capture of those beneficiaries arriving in the later hours of the day and identified as appropriate for hospice. By the time the patient has been seen in the emergency department, tests performed and results reviewed, a diagnosis made and determination that hospice is necessary, the clock often has reached midnight/the hospice is not contacted in time to get the patient admitted on this first day of the index admission. (Submitted by: National Association for Home Care & Hospice Care)
  
  
• To: Measure Applications Partnership Hospital Workgroup and Coordinating Committee From: Thomas M. Priselac President and Chief Executive Officer Date: December 5, 2016 Subject: Hospital-Wide (All Condition, All Procedure) Risk-Standardized Mortality Measure Cedars-Sinai Health System appreciates the opportunity to provide public comments to the MAP Hospital Workgroup in anticipation of its meeting on December 9 to review the measures currently being considered for public reporting and performance improvement programs. CSHS supports public reporting of outcome measures that represent actionable opportunities for hospitals to improve quality of care and that provide consumers with meaningful information about differences in hospital performance. However, there is no evidence that an “all condition, all procedure” mortality measure can achieve these goals, as detailed below. We would encourage the MAP Hospital Workgroup to recommend “do not support for rulemaking” in making its final recommendations to the Coordinating Committee. The Draft Measure Methodology notes that, “through input from the TEP and all of the work groups, we heard the importance of providing more detailed information than a single summary score for the usability of this measure for both clinicians and patients.” In other words, neither provider nor patient representatives believe that a single, aggregated measure will be useful on its own. More detailed 30-day mortality measures already exist, in the form of the five CMS condition-specific measures for AMI, heart failure, pneumonia, stroke, and CABG. In each of these conditions or procedures, there is a demonstrated linkage between hospital care and short-term mortality, specific steps that hospitals can take to reduce mortality, and sufficient volume of cases to develop reliable risk-adjustment models. For many other conditions, there is not strong evidence of a link between hospital quality of care and mortality, and the proportion of preventable deaths may be small. The Draft Measure Methodology submitted by Yale New Haven Health System/Center for Outcomes Research & Evaluation (YNHHS/CORE) shows that this measure is still at the conceptual stage. The statistical model has not been completed, and so there are no results on which to test reliability or validity. The exclusions and proposed risk variables have not been finalized, and the proposed aggregation of results into specialty cohorts has not been tested. We question why this measure was included on the Measures Under Consideration list when the CMS Technical Expert Panel has yet to review a fully-developed measure or made any final recommendations. The Draft Measure Methodology appears to be based largely on the methodology used for the hospital-wide 30-day readmission measure. Unlike 30-day readmission, however, mortality is a relatively rare outcome, particularly for the conditions that are not already reported by existing mortality measures. Whereas readmission risks include a care transition period common to all patients, the clinical differences between patients are much more relevant to the risk of mortality. The risk-adjustment approach described in the draft methodology is limited to 19 comorbidities based on administrative data. This is clearly inadequate to distinguish differences in hospital performance from differences in patient populations. Risk-adjusted mortality models with statistical and clinical credibility, such as those developed by the Society for Thoracic Surgery, the American College of Cardiology, and the American College of Surgeons National Surgical Quality Improvement Program, all incorporate multiple clinical data elements specific to the procedures being measured. After investing billions in the implementation of electronic health records, CMS should be working to incorporate such data into the quality measurement process. Another issue that is clear from the draft methodology is the lack of adequate volume in the majority of hospitals for development of reliable models. Based on the preliminary data presented, half of all hospitals would discharge 15 or fewer Medicare fee-for-service patients with cancer or cancer surgery, meaning that a difference of a single patient death would change the mortality rate by more than 6.7 percentage points. It does not appear feasible for this measure to meet either portion of its stated goal “to be able to measure more broadly the quality of care across hospitals and also to be able to measure the quality of care in smaller volume hospitals.” In conclusion, we do not believe the Hospital-Wide (All Condition, All Procedure) Risk-Standardized Mortality Measure would make a positive contribution to the gains in hospital quality and outcomes that have been accomplished through the CMS reporting process, and we suggest that CMS focus its limited resources on more meaningful measures and advancing the science of outcomes measurement. CSHS would like to thank the MAP for its work in developing consensus among diverse stakeholders and for considering these comments. (Submitted by: Cedars-Sinai Health System)
  
  
• December 5, 2016 TO: Measures Application Partnership Hospital Workgroup and Coordinating Committee FROM: California Hospital Association SUBJECT: Hospital-Wide (All Condition, All Procedure) Risk-Standardized Mortality Measure The California Hospital Association (CHA) appreciates the opportunity to provide public comments in anticipation of the MAP Hospital Workgroup meeting regarding the measures currently being considered for public reporting and performance improvement programs. While we continue to review the complete list of measures under consideration released by CMS, we wish to focus our initial comments on Hospital-Wide Risk Standardized Mortality Measure (MUC ID16-260). CHA agrees with CMS that mortality is an important hospital outcome measure for quality improvement and in public reporting. However, we question the importance and ability of providers to have a meaningful impact on this particular all condition, all procedure mortality measure. Further, the this measure would add to the set of currently specified condition specific mortality measures, which despite their limitations, are far superior to the proposed aggregated measure. We would encourage the MAP workgroup “do not support for rulemaking” as its final recommendation to the coordinating committee for the following reasons. First, the interim final report provided by CMS lacks the information necessary for the MAP to come to any other conclusion other than “do not support” at this time. The measure is firmly in the concept stage and lacks specific measure testing for any substantive evaluation to determine if such a concept is feasible and if the measure preforms as intended. We were disappointed to see this measure find its way to the MUC list knowing that the CMS Technical Expert Panel had not made its final recommendations or concluded its work. Second, we were disappointed to see that the YALE/CORE team has used the same methodology that continues to have its limitations, which are only further magnified at this more aggregated level. We see no attempt at the use of more granular clinical data from the electronic health records as we have seen in other mortality measure development efforts, nor do we see any other methodological changes that advance the science and improve on the current existing condition specific measures. Finally, this measure lacks the significant risk adjustment needed to limit what we believe to be inherent bias in these measures that make it nearly impossible to distinguish differences in performance as opposed to differences in patient populations served by hospitals. When we look at the progress to date over many years in this process, the measures reported and the quality improvement gains, we do not believe that this measure would further those efforts. Rather we believe CMS discontinue development of this measure and focus their limited resources on more impactful and meaningful measures. We look forward to working with CMS to further advance those goals. (Submitted by: California Hospital Association)
  
  

• America’s Essential Hospitals understands that patient-centered care improves patient outcomes and satisfaction. CMS implemented the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey as one method of formally recognizing that patient experience is central to health care. It is important that CMS continuously monitor and refine the questions contained in the HCAHPS survey to avoid any unintended consequences and ensure that the right questions are being asked. America’s Essential Hospitals has an interest in a strategic, high-impact set of quality metrics for use in Federal programs. We emphasize the importance of streamlining measures to promote greater alignment and harmonization and to reduce redundancies and inefficiencies. Measures should be used in programs only if they reveal meaningful differences in performance across providers. The measures should also be administratively simple to collect and report. Alignment—between hospitals, physicians, and others—should be the goal, across the care continuum, to reduce unnecessary data collection and reporting efforts. The MUC list contains several measures that lack a clear rationale for inclusion in the reporting programs, among them the Measure of Quality of Informed Consent Documents (MUC16-262). It is difficult to determine whether or how each of these measures would contribute to a specific national goal for improvement, and whether these measures are the most effective in promoting achievement of the desired improvement. For example, while informed consent is an important activity for which hospitals should develop meaningful documents and processes, we fail to see how a national measure of informed consent makes the consent process any better or more meaningful. There are numerous ways in which hospitals are currently held accountable for obtaining informed consent—CMS Conditions of Participation, The Joint Commission standards, state laws and regulations—and this new measure does not further the goal of developing an aligned set of measures and improvement activities. (Submitted by: America's Essential Hospitals)
  
  

• The AAMC thanks CMS for developing new pain management questions for the HCAHPS survey, but believes that MAP consideration of these measures is premature. CMS is still collecting data on these questions from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment. Until data collection is complete, and CMS has had the opportunity to analyze results and address any underlying concerns, the measures should not be considered by the MAP. The Hospital Workgroup cannot be asked to make an assessment of a measure that is not yet fully developed or NQF endorsed. The AAMC requests that CMS resubmit these measures after this process is complete. (Submitted by: Association of American Medical Colleges)
  
  
• CAPC recommends the use of this measure for the HIQR and HVBP programs. (Submitted by: Center to Advance Palliative Care)
  
  

• HP2, HP3, HP5 best questions for measurement of performance/improvement HP1 & HP4 do not reflect improved communication about pain medication (Submitted by: Community Health Network)
  
  
• CMS has submitted these two measures simultaneously for the IQR and VBP program. AAMC does not support these measures for the VBP program, since they have not been publicly reported for at least one year. Measures should be publicly reported on Hospital Compare - before being reviewed by the MAP - to allow stakeholders time to identify any deficiencies or unexpected concerns with the measure (Submitted by: Association of American Medical Colleges)
  
  
• CAPC recommends the use of this measure for the HIQR and HVBP programs. (Submitted by: Center to Advance Palliative Care)
  
  

• Please consider adding these questions: DP4: Did staff describe how to prevent or reduce serious side effects? DP5: Did staff tell you how to dispose of left-over prescribed pain medicine safely? (Submitted by: University of Michigan Health Systems)
  
  
• The AAMC thanks CMS for developing new pain management questions for the HCAHPS survey, but believes that MAP consideration of these measures is premature. CMS is still collecting data on these questions from discharged patients at 50 hospitals that participated in the HCAHPS mode experiment. Until data collection is complete, and CMS has had the opportunity to analyze results and address any underlying concerns, the measures should not be considered by the MAP. The Hospital Workgroup cannot be asked to make an assessment of a measure that is not yet fully developed or NQF endorsed. The AAMC requests that CMS resubmit these measures after this process is complete. (Submitted by: Association of American Medical Colleges)
  
  
• CAPC recommends the use of this measure for the HIQR and HVBP programs. (Submitted by: Center to Advance Palliative Care)
  
  
• We applaud CMS’s efforts to adjust the pain questions collected as part of the HCAHPS survey. The questions in this domain are an improvement over the current questions; however, Press Ganey is concerned about the number of questions and the burden associated with increasing the length of the survey. We recommend that the fewest number possible be added to the survey. (Submitted by: Press Ganey)
  
  

• SHM greatly appreciates that CMS has recognized the potential unintended consequences and perverse incentives for opioid prescribing associated with the existing pain management questions in the HCAHPS Survey. We believe the modified questions in MUC16-264 are a step forward towards centering the assessment around communication for pain management. However, SHM does not recommend the MAP support this question set for inclusion into the HCAHPS. We strongly encourage CMS continue to work with provider groups to address concerns with the measures prior to implementing in federal programs. We have concerns that this set of questions does not have a similar response-based exclusion that ascertains whether a patient has pain, and therefore whether the DP questions are appropriate for the patient. We also believe this question set may present an opportunity for CMS to reframe patient expectations for pain management. A question in this set could ask whether staff discussed expectations for pain management, which would squarely assess that pain is being addressed broadly as part of overall patient care and discharge planning. This could be augmented with a question around a broader field of interventions for pain management, adapting language similar to question 15 of the Outpatient and Ambulatory Surgery (OAS) CAHPS which asks, “Some ways to control pain include prescription medication, OTC pain relievers or ice packs. Did your doctor or anyone from the facility about what to do if you had pain as a result of your procedure?” This would expand the potential field of interventions to include alternative, non-opioid therapies and create realistic expectations for pain and pain management. (Submitted by: Society of Hospital Medicine)
  
  
• CMS has submitted these two measures simultaneously for the IQR and VBP program. AAMC does not support these measures for the VBP program, since they have not been publicly reported for at least one year. Measures should be publicly reported on Hospital Compare - before being reviewed by the MAP - to allow stakeholders time to identify any deficiencies or unexpected concerns with the measure. (Submitted by: Association of American Medical Colleges)
  
  
• CAPC recommends the use of this measure for the HIQR and HVBP programs. (Submitted by: Center to Advance Palliative Care)
  
  

• CAPC recommends the use of this measure for the PCHQR program. (Submitted by: Center to Advance Palliative Care)
  
  

• CAPC recommends the use of this measure for the PCHQR program. (Submitted by: Center to Advance Palliative Care)
  
  

• The National Coalition for Hospice and Palliative Care, comprised of the eight leading national organizations representing the hospice and palliative care field, recommends the use of both this measure, 274, alongside MUC16-275 (Proportion of patients who died from cancer not admitted to hospice). Both of these measures are recommended for PHQR quality reporting programs, but with the stipulation that they be considered a measure pair – i.e., that implementation of one measure without the other is not acceptable. Providers might be inclined to circumvent measure MUC16-274 by simply not referring patients who are imminently dying to hospice if that measure alone is required. Likewise, providers can be in compliance with MUC16-275 by referring imminently dying patients to hospice if that measure alone is required. Therefore, both measures must be implemented to achieve the desired quality of care afforded by hospice for patients dying from cancer. (Submitted by: National Coalition for Hospice and Palliative Care)
  
  
• CAPC recommends the use of measures MUC16-274 and MUC16-275 for the PCHQR quality reporting programs, but with the stipulation that they be considered a measure pair – i.e., that implementation of one measure without the other is not acceptable. Providers might be inclined to circumvent measure MUC16-274 by simply not referring patients who are imminently dying to hospice if that measure alone is required. Likewise, providers can be in compliance with MUC16-275 by referring imminently dying patients to hospice if that measure alone is required. Therefore, both measures must be implemented to achieve the desired quality of care afforded by hospice for patients dying from cancer. (Submitted by: Center to Advance Palliative Care)
  
  

• The National Coalition for Hospice and Palliative Care recommends the use of both of these measures (274 and 275) for PHQR quality reporting programs, but with the stipulation that they be considered a measure pair – i.e., that implementation of one measure without the other is not acceptable. Providers might be inclined to circumvent measure MUC16-274 by simply not referring patients who are imminently dying to hospice if that measure alone is required. Likewise, providers can be in compliance with MUC16-275 by referring imminently dying patients to hospice if that measure alone is required. Therefore, both measures must be implemented to achieve the desired quality of care afforded by hospice for patients dying from cancer. (Submitted by: National Coalition for Hospice and Palliative Care)
  
  
• CAPC recommends the use of measures MUC16-274 and MUC16-275 for the PCHQR quality reporting programs, but with the stipulation that they be considered a measure pair – i.e., that implementation of one measure without the other is not acceptable. Providers might be inclined to circumvent measure MUC16-274 by simply not referring patients who are imminently dying to hospice if that measure alone is required. Likewise, providers can be in compliance with MUC16-275 by referring imminently dying patients to hospice if that measure alone is required. Therefore, both measures must be implemented to achieve the desired quality of care afforded by hospice for patients dying from cancer. (Submitted by: Center to Advance Palliative Care)
  
  
• While written comments were not provided, the commenter indicated their support for this measure in this program (Submitted by: American Society for Radiation Oncology (ASTRO))
  
  

• Baxter Healthcare Corporation supports the inclusion of the measure Completion of a Malnutrition Screening within 24 Hours of Admission (MUC16-294) in the Centers for Medicare & Medicaid Services (CMS) Hospital Inpatient Quality Reporting (HIQR) program. We appreciate that CMS has included this measure for consideration in its upcoming proposed hospital inpatient prospective payment rule and believe that this is an important step in better examining and addressing malnutrition in hospitalized patients, which is a serious health issue in hospitals nationwide. There is expert consensus that supports the benefits of documenting malnutrition diagnosis, which both improves patient outcomes and reduces healthcare costs, and we strongly urge the Measure Applications Partnership (MAP) to put forth the measure for consideration. Baxter is a global leader in assisting healthcare professionals and their patients with the treatment of complex medical conditions, including cancer, infectious diseases, kidney disease, trauma, and other conditions. The company applies its expertise in medical devices and pharmaceuticals, to make a meaningful difference in patients’ lives and has been an innovator in intravenous nutritional support products since the 1940’s. The new measure Completion of a Malnutrition Screening within 24 Hours of Admission is part of a set of harmonized measures which address malnutrition, an ongoing healthcare issue with demonstrated impacts on patients and the health care system. Malnutrition is a condition that remains underdiagnosed and untreated, especially with respect to our nation’s elderly patients, with rates of malnutrition as high as 39%,1, 2 and with recent data that show that the problem is not improving. We understand that there has been concern expressed about the burden of screening each hospitalization (patients 18 and older) within 24 hours, regardless of patient risk or condition. Screening for malnutrition, however, is straightforward, and there are tools available with sensitivity that allows for the identification of those at risk for malnutrition. The burden on hospitals, therefore, is not great, especially in light of the significant benefits that such screening can bring in improving patient outcomes and reducing healthcare costs. Nationally, hospital stays involving malnutrition accounted for over 12 percent of aggregate hospital costs among nonmaternal and nonneonatal stays in 2013, according to a statistical brief issued by the Agency for Healthcare and Research Quality (AHRQ).3 Evidence shows that hospitalizations with a diagnosis of malnutrition have a longer length of stay, higher costs, more comorbidities, and five times the likelihood of death, compared with other adult hospital stays. In addition, the AHRQ brief showed that patients with malnutrition are half as likely to be discharged home and 4.9 times more likely to result in in-hospital death than the average of all inpatient non-maternal/non-neonatal stays. Global research published in the last five years addressing the identification of malnutrition risk is consistent with these findings and also demonstrates that malnutrition and the risk of malnutrition are predictors of mortality, hospitalization costs and length of stay. Researchers in Australia reported that malnutrition is associated with greater length of stay and readmission rates4, while European researchers reported that malnutrition risk affects three in five hospitalized patients and is associated with increased mortality and costs.5 Finally, a 2015 Swiss study of over 3,000 patients reported that malnutrition risk is highly prevalent (27.8%) and also associated with adverse clinical outcomes, impairments in functional ability and higher costs.6 These findings were also reported in 2016 in Canada7, the Netherlands8, Portugal9 and in the UK.10 We believe that the recommendation to complete malnutrition screening should be widely adopted in line with best-practice guidelines to effectively target and decrease the potential negative impact of malnutrition.11, 12, 13, 14, 15 Malnutrition screening within 24 hours of admission has long been a Joint Commission Standard, yet currently, there are no quality measures in place to reliably evaluate performance across Joint Commission-accredited hospitals. For these reasons and in light of the evidence presented, we urge the MAP to recommend inclusion of Completion of a Malnutrition Screening within 24 Hours of Admission (MUC16-294) for hospitalized patients into the HIQR program. Thank you for your time and consideration of our comments. Sincerely, Crystal A. Riley, PharmD, MHA, MBA Senior Manager, Healthcare Policy & Reimbursement Baxter Healthcare 1. Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. 2. Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. 3. Weiss AJ, Fingar KR, Barrett ML, Elixhauser A, Steiner CA, Guenter P, Brown MH. Characteristics of Hospital Stays Involving Malnutrition, 2013. HCUP Statistical Brief #210. September 2016. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb210-Malnutrition-Hospital-Stays-2013.pdf. 4. Agarwal E, Ferguson M, Banks M, Batterham M, Bauer J, Capra S, & Isenring E. Malnutrition and poor food intake are associated with prolonged hospital stay, frequent readmissions, and greater in-hospital mortality: Results from the Nutrition Care Day Survey 2010. Clinical Nutrition. 2013; 32(5):737-745. 5. Khalatbari-soltani S, Marques-vidal P. Impact of nutritional risk screening in hospitalized patients on management, outcome and costs: A retrospective study. Clin Nutr. 2016; S0261-5614(16)00069-8. 6. Allard JP, Keller H, Jeejeebhoy KN, et al. Malnutrition at Hospital Admission-Contributors and Effect on Length of Stay: A Prospective Cohort Study From the Canadian Malnutrition Task Force. JPEN J Parenter Enteral Nutr. 2016;40(4):487-97. 7. Kruizenga H, Van keeken S, Weijs P, et al. Undernutrition screening survey in 564,063 patients: patients with a positive undernutrition screening score stay in hospital 1.4 d longer. Am J Clin Nutr. 2016;103(4):1026-32. 8. Guerra RS, Sousa AS, Fonseca I, et al. Comparative analysis of undernutrition screening and diagnostic tools as predictors of hospitalisation costs. J Hum Nutr Diet. 2016;29(2):165-73. 9. Gomes F, Emery PW, Weekes CE. Risk of Malnutrition Is an Independent Predictor of Mortality, Length of Hospital Stay, and Hospitalization Costs in Stroke Patients. J Stroke Cerebrovasc Dis. 2016;25(4):799-806. 10. Mueller C, Compher C & Druyan ME and the American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Board of Directors. A.S.P.E.N. Clinical Guidelines: Nutrition Screening, Assessment, and Intervention in Adults. J Parenter Enteral Nutr. 2011;35: 16-24. 11. Kondrup J, Allison SP, Elia M, Vellas B, Plauth M. ESPEN guidelines for nutrition screening 2002. Clin Nutr. 2003;22(4):415-21. 12. National Collaborating Centre for Acute Care, February 2006. Nutrition support in adults Oral nutrition support, enteral tube feeding and parenteral nutrition. National Collaborating Centre for Acute Care, London. Available from www.rcseng.ac.uk 13. White JV, Guenter P, Jensen G, et al. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN J Parenter Enteral Nutr. 2012;36(3):275-83. 14. Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2016; http://dx.doi.org/10.1016/j.clnu.2016.09.004. (Submitted by: Baxter Healthcare Corporation)
  
  
• The Joint Commission appreciates the opportunity to submit comments in support of inclusion of this measure in the Hospital Inpatient Quality Reporting Program and the suite of measures (MUC16-294, MUC16-296, MUC16-344 and MUC16-372) addressing malnutrition developed by Avalere and the Academy of Nutrition and Dietetics. Joint Commission standards have long reflected the importance of nutrition screening, assessment of at-risk hospitalized patients, diagnosis of malnutrition and appropriate intervention. Malnutrition is an ongoing healthcare issue with demonstrated impacts on patient outcomes. It is a condition that remains underdiagnosed and untreated, especially with respect to our nation’s elderly patients, with rates for elderly patients in the hospital as high as 39%.[1], [2] The Joint Commission welcomes the advent of performance measures to quantify the degree to which these best practices are carried out. These evidence-based measures were developed in accordance with a rigorous, multi-stakeholder process. They have been completely tested and have been shown to have the capacity to significantly improve the health and well-being of patients. ________________________________________ [1] Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. [2] Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. (Submitted by: The Joint Commission)
  
  
• MUC16-294 Completion of a Malnutrition Screening within 24 Hours of Admission Given the critical role of nutrition in improving patient outcomes and reducing costs, and the lack of associated quality measures, AdvaMed urges the MAP to support adoption of MUC16-294 Completion of a Malnutrition Screening within 24 Hours of Admission in the Hospital Inpatient Quality Reporting Program (HIQR). Malnutrition is prevalent and costly in hospitalized adults. Studies estimate that 20-50% of hospital inpatients are either malnourished or at-risk for malnutrition upon admission , depending on the particular patient population and the criteria used to assess the patients. Malnutrition is associated with increased mortality, adverse clinical outcomes, decreased functional status and costs. , , , , , As many as 31% of malnourished patients and 38% of well-nourished patients will experience nutritional decline during their hospital stay due to loss of appetite, inability to swallow, or various other factors. In addition, many patients continue to lose weight after discharge and patients with weight loss are at increased risk for readmission . Further, a recent AHRQ Statistical Brief presenting data on hospital discharges involving malnutrition shows that malnourished inpatients tend to be older, have up to 100% longer lengths of stay and can have significant increases in episode costs; up to $25,000 versus $12,500 per episode for non-malnourished adults. While 20-50% of hospitalized patients are estimated to be malnourished or at-risk only 7.1% of patients are reported to have a documented malnutrition diagnosis upon discharge. This new analysis also estimates the economic impact of malnutrition in the hospital to be $42 billion. As recovery, rehabilitation time and functional independence may be significantly improved by preventing and treating malnutrition, MUC16-294 is a “measure that matters” for patients, families and providers. Identifying malnutrition risk begins with a low-burden simple screening process conducted by a nurse or technician upon admission and has been a hospital standard for almost twenty years. For example the MST, a validated screening tool, uses two questions to identify the patient population that is at-risk. Screening for hospitalized patients starts the cascade of team-based care to assessment, diagnosis, care plan development, and nutrition interventions as warranted. Without identifying this initial patient population, the true population that should be assessed for findings of malnutrition would be vastly under-identified and patients would be left potentially untreated. Reporting MUC16-294 is low burden as it is an electronic clinical quality measure (eCQM). Effective and timely screening is essential to help providers make accurate diagnoses and early nutrition interventions have been shown to substantially reduce readmission rates as well as complication rates, length of stay, cost of care, and mortality. In summary, the malnutrition electronic clinical quality measures (eCQMs) are fully developed and data collection is low burden. The malnutrition eCQM set addresses CMS HIQR priorities as these process measures collectively will help to fill a measure gap, improve quality across the patient-focused episode of care, and engage patients and their families as partners in care delivery. The malnutrition eCQMs also align with NQS priorities by improving patient safety (decreased preventable readmissions and complications), care coordination, patient and family centered care (activation/engagement), population health (prevention and management of elderly and high impact Medicare conditions), and efficiency (reduced costs). (Submitted by: AdvaMed)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: Cleveland Clinic Center for Human Nutrition)
  
  

• Baxter Healthcare Corporation supports Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition within 24 hours of a Malnutrition Screening (MUC16-296). We appreciate that the Centers for Medicare & Medicaid Services (CMS) has included it in is list of measures under consideration for inclusion in the Hospital Inpatient Quality Reporting (HIQR) program. New evidence has emerged to support the importance of completing nutrition assessments for patients at-risk of malnutrition as such assessments enable appropriate follow up care to patients. For the reasons discussed below, we strongly urge the MAP to recommend inclusion of this measure to CMS. Baxter is a global leader in assisting healthcare professionals and their patients with the treatment of complex medical conditions, including cancer, infectious diseases, kidney disease, trauma, and other conditions. The company applies its expertise in medical devices and pharmaceuticals, to make a meaningful difference in patients’ lives. Baxter has been an innovator in intravenous nutritional support products since the 1940’s and a collaborator in the examination of malnutrition in conjunction with external healthcare organizations and the Federal government. MUC16-296 is part of a set of harmonized measures all of which address the ongoing challenges related to malnutrition. Malnutrition remains underdiagnosed and untreated, especially with respect to our nation’s elderly patients with rates of malnutrition as high as 39%, and recent data show that the problem is not improving.1, 2 As illustrated in the Agency for Healthcare and Research Quality’s recently published statistical brief, malnutrition tends to have a greater impact on the elderly, it increases lengths of stay up to 100%, it can lead to twice as costly episodes of care, reduce discharges to home and is associated more often to in-hospital death than the average of all inpatient nonmaternal/non-neonatal stays.3 Stakeholders such as the Joint Commission are acknowledging the importance of completing nutrition assessments for at-risk patients by including the practice in their Provision of Care standards (PC.01.02.01, EP 2) for hospital evaluation.4 In addition, new evidence, which has emerged to support the importance of completing nutrition assessments for patients at-risk of malnutrition, shows that for patients who, through a dietitian’s full assessment, are found to be malnourished, the nutritional assessment allows for the development of a care plan with appropriate interventions and follow up care to patients.5, 6, 7, 8 Furthermore, despite high prevalence of malnutrition across multiple studies, there is still a significant gap in identification and treatment.9 When proper follow up for at-risk patients does not occur, patients for whom there could have been intervention do not receive the necessary care to address their condition10, resulting in adverse outcomes such as prolonged length of stay11, 12, 13, 14 which can translate into higher healthcare costs.15 There is also a significant opportunity for improvement, as demonstrated in the results of a survey of over 1,700 providers of nutrition care in the hospital. More can and should be done to follow through on patients who are identified as at-risk of malnutrition. The survey showed that only 26% of providers always base their diagnosis of malnutrition for patients on nutrition assessments.16 The same survey reported that in 40% of participating hospitals, clinicians are missing 50% of their patients who screened positive for malnutrition risk. In conclusion, we believe the evidence shows that the measure Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition within 24 hours of a Malnutrition Screening (MUC16-296) would have a positive impact on patients and health care costs, and we urge the MAP to recommend its inclusion in the HIQR program to CMS. Thank you for your time and consideration of our comments. Sincerely, Crystal A. Riley, PharmD, MHA, MBA Senior Manager, Healthcare Policy & Reimbursement Baxter Healthcare 1. Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. 2. Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. 3. Weiss AJ, Fingar KR, Barrett ML, Elixhauser A, Steiner CA, Guenter P, Brown MH. Characteristics of Hospital Stays Involving Malnutrition, 2013. HCUP Statistical Brief #210. September 2016. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb210-Malnutrition-Hospital-Stays-2013.pdf. 4. Standards information for hospitals. The Joint Commission. https://www.jointcommission.org/accreditation/hap_standards_information.aspx. Accessed October 11, 2016. 5. Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2016; http://dx.doi.org/10.1016/j.clnu.2016.09.004. 6. British Association for Parenteral and Enteral Nutrition. Malnutrition Matters, A Toolkit for Clinical Commissioning Groups and providers in England. Published 2012. Retrieved from: http://www.bapen.org.uk/pdfs/bapen_pubs/bapen-toolkit-for-commissioners-and-providers.pdf. 7. Academy of Nutrition & Dietetics. CI: Nutrition Assessment of Critically Ill Adults 2012. Academy of Nutrition & Dietetics Evidence Analysis Library. Published 2012. Retrieved from: http://www.andeal.org/topic.cfm?menu=4800. 8. White JV, Guenter P, Jensen G, et al. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN J Parenter Enteral Nutr. 2012;36(3):275-83. 9. Volkert D, Saeglitz C, Gueldenzoph H, Sieber CC, Stehle P. Undiagnosed malnutrition and nutrition-related problems in geriatric patients. J Nutr Health Aging. 2010;14(5):387-92. 10. Tappenden KA, Quatrara B, Parkhurst ML, Malone AM, Fanjiang G, Ziegler TR. Critical role of nutrition in improving quality of care: an interdisciplinary call to action to address adult hospital malnutrition. JPEN J Parenter Enteral Nutr. 2013;37(4):482-97. 11. Allard JP, Keller H, Jeejeebhoy KN, et al. Decline in nutritional status is associated with prolonged length of stay in hospitalized patients admitted for 7 days or more: A prospective cohort study. Clin Nutr. 2016;35(1):144-52. 12. Jeejeebhoy KN et al. Nutritional assessment: comparison of clinical assessment and objective variables for the prediction of length of hospital stay and readmission. Am J Clin Nutr 2015; 101: 956-965. 13. Almeida AI, Correia M, Camilo M, Ravasco P. Length of stay in surgical patients: nutritional predictive parameters revisited. Br J Nutr. 2013;109(2):322-8. 14. Allard JP, Keller H, Jeejeebhoy KN, et al. Malnutrition at Hospital Admission-Contributors and Effect on Length of Stay: A Prospective Cohort Study From the Canadian Malnutrition Task Force. JPEN J Parenter Enteral Nutr. 2016;40(4):487-97. 15. Braunschweig C, Gomez S, Sheean PM. Impact of declines in nutritional status on outcomes in adult patients hospitalized for more than 7 days. J Am Diet Assoc. 2000;100(11):1316-22. 16. Patel V, Romano M, Corkins MR, et al. Nutrition Screening and Assessment in Hospitalized Patients: A Survey of Current Practice in the United States. Nutr Clin Pract. 2014;29(4):483-490. (Submitted by: Baxter Healthcare Corporation)
  
  
• MUC16-296 Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition Within 24 hours of a Malnutrition Screening Given the critical role of nutrition in improving patient outcomes and reducing costs, and the lack of associated quality measures, AdvaMed urges the MAP to support adoption of MUC16-296 Completion of a Nutrition Assessment for Patients Identified as At-Risk for Malnutrition Within 24 hours of a Malnutrition Screening, in the Hospital Inpatient Quality Reporting Program (HIQR). Malnutrition is prevalent and costly in hospitalized older adults. Estimates of malnutrition in the acute care setting for elderly patients reach 39% based on screening and assessment data. , Malnutrition can either be a contributing cause or a consequence of many disease conditions, acute conditions or illnesses. Increasing the risk of malnutrition is the presence of chronic conditions which may impair the person’s ability to ingest or absorb nutrients causing increased energy needs or requiring dietary restrictions. This includes high-impact and costly conditions such as cardiovascular disease, stroke, diabetes, cancer, chronic obstructive pulmonary disease (COPD), renal disease, depression, and dementia. Significantly the morbidity, mortality, and direct medical costs associated with Disease-Associated Malnutrition (DAM) in the U.S. are estimated to be $51.3 billion for people age 65 years and older. In an epidemiologic analysis of 887,189 major surgery cases drawn from the Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS), malnutrition was associated with an increased risk of severe events. Patients with malnutrition were four times more likely to develop pressure ulcers, two times more likely to develop surgical site infections, 16 times more likely to develop intravascular device infections, and five times more likely to develop catheter-associated urinary tract infections. As recovery, rehabilitation time and functional independence may be significantly improved by preventing and treating malnutrition, MUC16-296 is a “measure that matters” for patients, families and providers. A dietitian conducts the assessment and the results of the assessment are the primary source of information for other clinicians regarding the patient’s nutritional status and signs of malnutrition. In turn, it guides diagnoses, recommendations for interventions, and care plans to address the patient’s malnutrition and prevent nutritional decline. , , , Evidence has been recently published that illustrates that when proper follow up for patients identified as at-risk during the screening does not occur, patients who are potentially malnourished do not receive the necessary care and interventions to address their condition, resulting in adverse outcomes such as prolonged length of stay, higher risk of hospital-acquired conditions, and greater likelihood of readmissions. , , , Reporting MUC16-296 is low burden as it is an eCQM and can help clinicians conduct timely assessment and communication of nutritional status across the interdisciplinary care team. This measure can help close performance gaps in malnutrition care beyond the initial screen and improve quality of evaluation, care coordination and patient outcomes. In summary, the malnutrition electronic clinical quality measures (eCQMs) are fully developed and data collection is low burden. The malnutrition eCQM set addresses CMS HIQR priorities as these process measures collectively will help to fill a measure gap, improve quality across the patient-focused episode of care, and engage patients and their families as partners in care delivery. The malnutrition eCQMs also align with NQS priorities by improving patient safety (decreased preventable readmissions and complications), care coordination, patient and family centered care (activation/engagement), population health (prevention and management of elderly and high impact Medicare conditions), and efficiency (reduced costs). (Submitted by: AdvaMed)
  
  

• NKF believes that a transfusion avoidance measure is important to protecting patients from unnecessary transfusions. Risks of red blood cell transfusions in dialysis patients include hyperkalemia, volume overload and antigen sensitization for a potential future kidney transplant. However, a transfusion avoidance measure should be stratified to appropriately capture blood transfusions that could have been prevented by the dialysis facility and exclude other reasons for transfusions. To this end, we appreciate the exclusions of certain patient populations that are likely to experience anemia and may require blood transfusions due to other comorbid conditions. NKF acknowledges tracking blood transfusion data are critical to understanding patient safety hazards. NKF also recognizes that since most blood transfusions are provided outside of the dialysis setting how transfusions are reported and submitted as claims to CMS may vary by hospital and by patient. This could cause variation in performance on the StR. NKF encourages CMS to explore ways to ensure hospitals appropriately report and standardize reporting on blood transfusions for dialysis patients. (Submitted by: National Kidney Foundation)
  
  
• MUC16-305—Standardized Transfusion Ratio for Dialysis Facilities (STrR; NQF 2979). KCP opposes this measure. As for the NQF Renal 2016-2017 Project, KCP again expresses concern about the reliability of the STrR for small facilities. Specifically, testing yielded IURs of 0.30-0.41 for small facilities for each of 2011, 2012, 2013, and 2014, indicating approximately 60-70% of a small facility’s score is due to random noise. CMS does not identify a minimum sample in the specifications, although the developer’s empirical testing clearly demonstrates poor reliability in the facilities with small samples in which the testing was conducted. Additionally, we again note that physicians independently (or following hospital protocols) make decisions about whether or not to transfuse a specific patient; the measure does not adjust for the hospital- and physician-related transfusion practices that are out of dialysis facility control. (Submitted by: Kidney Care Partners (KCP))
  
  

• The National Kidney Foundation strongly supports this measure and its pairing with the long-term catheter rate measure (MUC16-309). NKF is particularly pleased with the additional exclusions that acknowledge catheter use for patients with limited life expectancy. These changes align with NKF’s previous recommendations on endorsement of these measures. We do note that clarity around sole access use would strengthen this measure. Specifically, credit for this measure should only apply if the patient does not have a catheter. As written it could be interpreted that the facility would get credit for a patent with a catheter as long as the catheter was not being used for dialysis. The presence of a catheter increases patients risk for infection and therefore no credit should be given if the patient has a catheter. In contrast if a patient has an AV graft that is not being used credit for the measures should still apply as the risk of AV graft infection is low, but there is associated risk with removal. (Submitted by: National Kidney Foundation)
  
  
• MUC16-308—Hemodialysis Vascular Access: Standardized Fistula Rate (NQF 2977). KCP supports MUC16-308, but recommends the developer consider modifications to improve the measure prior to incorporation into the ESRD QIP portfolio of measures: o KCP believes the specifications are imprecise as to whether facilities would receive credit for patients using an AVF as the sole means of access, but who also have in place a graft or catheter that is no longer being used. A numerator that specifies the patient must be on maintenance hemodialysis “using an AVF with two needles and without a dialysis catheter present” would remove ambiguity. o KCP believes two additional vasculature risk variables would strengthen the model: a history of multiple prior accesses and the presence of a cardiac device. (Submitted by: Kidney Care Partners (KCP))
  
  

• There are numerous advantages to using an arteriovenous (AV) fistula (AVF) for hemodialysis as compared to a catheter or AV graft. The use of AVF 90 days after the initiation of hemodialysis has been found to be associated with reduced cardiovascular and all-cause mortality. Additionally, the use of an AVF is recognized as the optimal type of hemodialysis vascular access for its longer patency and fewer infection complications, and is associated with lower all-cause mortality compared with the AV graft or central venous catheter (CVC). In those circumstances in which hemodialysis patients are unable to successfully establish or maintain an AVF, the American Nephrology Nurses Association (ANNA) acknowledges that an AV graft is an acceptable alternative. Moreover, we recognize that for those patients in whom kidney disease has progressed quickly, there may be insufficient time to prepare permanent vascular access before dialysis treatments are started. Choosing peritoneal dialysis as the treatment modality, rather than starting hemodialysis with a CVC catheter, has a mortality advantage of one to two years. For patients choosing peritoneal dialysis as their kidney replacement therapy, ANNA believes that urgent-start peritoneal dialysis to initiate dialysis is a superior alternative to initiating hemodialysis with a CVC for many patients. Research studies have demonstrated that the use of a CVC increases mortality risk compared with incident dialysis patients who initiated treatment with peritoneal dialysis, AVF, or an AV graft. The long-term catheter rate measure fails to account for those individuals with end-stage renal disease (ESRD) who are unable to support internal access and whose only choice is a CVC. ANNA has concerns the long-term catheter rate measure will inappropriately penalize a dialysis facility that receives into its care a patient with a CVC who has transferred from a different facility or unit during the measurement period. ANNA encourages CMS not to adopt the measure at this time and instead consider how to account for such patients and avoid penalizing dialysis facilities and units in such circumstances. ANNA greatly appreciates the opportunity to share our comments on the long-term catheter rate measure. As the leading professional association representing nephrology nurses, we look forward to continuing to work with CMS and the National Quality Forum’s Measure Applications Partnership on these important issues. (Submitted by: American Nephrology Nurses Association)
  
  
• The National Kidney Foundation strongly supports this measure and its pairing with the standardized fistula rate measure (MUC16-308. NKF is particularly pleased with the four additional exclusions that acknowledge catheter use is appropriate for patients with limited life expectancy. These changes align with NKF’s previous recommendations. We do note that clarity around catheter use continuously would strengthen this measure. Specifically, the numerator should include all patients with a catheter in place for the reporting period, whether the hemodialysis catheter is in continuous use or not. The presence of a catheter increases the risk for infection even if it is not in use. (Submitted by: National Kidney Foundation)
  
  
• MUC16-309—Hemodialysis Vascular Access: Long-Term Catheter Rate (NQF 2978). KCP supports MUC16-309. (Submitted by: Kidney Care Partners)
  
  

• Baxter Healthcare Corporation supports the proposed new quality measure, Appropriate Documentation of Malnutrition Diagnosis (MUC16-344) for inclusion in the Centers for Medicare & Medicaid Services (CMS) Hospital Inpatient Quality Reporting (HIQR) program. For the reasons discussed below, we strongly urge the Measure Applications Partnership (MAP) to recommend MUC16-344 for further consideration. Baxter is a global leader in assisting healthcare professionals and their patients with the treatment of complex medical conditions, including cancer, infectious diseases, kidney disease, trauma, and other conditions. The company applies its expertise in medical devices and pharmaceuticals, to make a meaningful difference in patients’ lives. Baxter has been an innovator in intravenous nutritional support products since the 1940’s and a collaborator in the examination of malnutrition in conjunction with external healthcare organizations and the Federal government. Currently, a substantial gap exists between findings from surveillance of assessment data on patients with malnutrition and the identification of these patients with malnutrition at a national level. This demonstrates that patients with malnutrition are not being formally diagnosed by medical providers using assessment data as recommended by expert consensus.1,2,3 When looking at screening and assessment data, for example, estimates of malnutrition in the acute care settings for elderly patients are as high as 39%.4,5 However, a recent Agency for Healthcare Research and Quality (AHRQ) report on malnutrition-involved discharges indicated that only 7.1% of discharges in U.S. hospitals are coded for malnutrition.6 Documentation of malnutrition in a patient’s record plays a significant role in care transitions and care coordination between acute and post-acute settings. The Centers for Medicare & Medicaid Services agrees with this perspective, noting that documentation of a malnutrition diagnosis is an important component of proper discharge planning and/or transitions of care to post-acute providers.7 For example, recent national data shows that patients with malnutrition in the hospital were half as likely to be discharged home, 4.9 times more likely to result in in-hospital death, have up to 100% longer lengths of stay, and twice as costly episodes of care than the average inpatient stay. Reviews of the evidence have identified an increasing incidence of and diagnosis for malnutrition.8 (It has been suggested that this increasing incidence of malnutrition may be a coincidental effect of the increasing rate of screening for malnutrition.) The gap in evidence regarding the assignment of formal medical diagnosis of malnutrition during an inpatient stay, however, is both a reflection of a low rate of performance as well as a process that is misaligned with best practices. The medical diagnosis serves as the nexus of documentation of the findings of the care delivery team, including the nutrition support staff members, and the implementation of evidence-based interventions intended to reduce the impact of malnutrition on patient morbidity and mortality9 A 2014 survey of over 1,700 providers of nutrition care illustrates the gap in care evident in real world practice. Only 69% of surveyed providers are documenting findings of the screening in their medical record, and even more concerning is that as many as 40% of providers are not following through with at-risk patients more than 50% of the time, leaving many without a proper assessment or subsequent diagnosis.10 We believe that the measure addresses a major gap in care and that its use could help avoid preventable adverse outcomes for patients in the hospital. For these reasons and in light of the evidence presented, we urge the Measure Applications Partnership to recommend the inclusion of MUC16-344: Appropriate Documentation of Malnutrition Diagnosis in the CMS HIQR program. Thank you for your time and consideration of our comments. Sincerely, Crystal A. Riley, PharmD, MHA, MBA Senior Manager, Healthcare Policy & Reimbursement Baxter Healthcare 1. White JV, Guenter P, Jensen G, et al. Consensus statement of the Academy of Nutrition and Dietetics/American Society for Parenteral and Enteral Nutrition: Characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). J Acad Nutr Diet. 2012;112(5):730-738. 2. Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2016; http://dx.doi.org/10.1016/j.clnu.2016.09.004. 3. British Association for Parenteral and Enteral Nutrition. Malnutrition Matters, A Toolkit for Clinical Commissioning Groups and providers in England. Published 2012. Retrieved from: http://www.bapen.org.uk/pdfs/bapen_pubs/bapen-toolkit-for-commissioners-and-providers.pdf. 4. Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. 5. Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. 6. Weiss AJ, Fingar KR, Barrett ML, Elixhauser A, Steiner CA, Guenter P, Brown MH. Characteristics of Hospital Stays Involving Malnutrition, 2013. HCUP Statistical Brief #210. September 2016. Agency for Healthcare Research 7. Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Policy Changes and Fiscal Year 2017 Rates, 81 FR 56761 (22 August 2016), pp. 1985. 8. Corkins MR, Guenter P, Dimaria-ghalili RA, et al. Malnutrition diagnoses in hospitalized patients: United States, 2010. JPEN J Parenter Enteral Nutr. 2014;38(2):186-95. 9. Hand RK, Murphy WJ, Field LB, et al. Validation of the Academy/A.S.P.E.N. Malnutrition Clinical Characteristics. J Acad Nutr Diet. 2016;116(5):856-64. 10. Patel V, Romano M, Corkins MR, et al. Nutrition Screening and Assessment in Hospitalized Patients: A Survey of Current Practice in the United States. Nutr Clin Pract. 2014;29(4):483-490. (Submitted by: Baxter Healthcare Corporation)
  
  
• The Joint Commission appreciates the opportunity to submit comments in support of inclusion of this measure in the Hospital Inpatient Quality Reporting Program and the suite of measures (MUC16-294, MUC16-296, MUC16-344 and MUC16-372) addressing malnutrition developed by Avalere and the Academy of Nutrition and Dietetics. Joint Commission standards have long reflected the importance of nutrition screening, assessment of at-risk hospitalized patients, diagnosis of malnutrition and appropriate intervention. Malnutrition is an ongoing healthcare issue with demonstrated impacts on patient outcomes. It is a condition that remains underdiagnosed and untreated, especially with respect to our nation’s elderly patients, with rates for elderly patients in the hospital as high as 39%.[1], [2] The Joint Commission welcomes the advent of performance measures to quantify the degree to which these best practices are carried out. These evidence-based measures were developed in accordance with a rigorous, multi-stakeholder process. They have been completely tested and have been shown to have the capacity to significantly improve the health and well-being of patients. ________________________________________ [1] Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. [2] Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. (Submitted by: The Joint Commission)
  
  
• MUC16-344 Appropriate Documentation of a Malnutrition Diagnosis Given the critical role of nutrition in improving patient outcomes and reducing costs, and the lack of associated quality measures, AdvaMed urges the MAP to support adoption of MUC16-344 Appropriate Documentation of a Malnutrition Diagnosis in the Hospital Inpatient Quality Reporting Program (HIQR). Malnutrition is prevalent and costly in hospitalized adults. Global research published in the last five years confirms these findings, highlighting that malnutrition risk affects three in five hospitalized patients and is associated with increased mortality and costs, as well as greater LOS and readmission rates. It is also associated with adverse clinical outcomes, decreased functional status, and higher costs. , , , , Further, a recent AHRQ Statistical Brief presenting data on hospital discharges involving malnutrition demonstrates malnourished inpatients tend to be older, have up to 100% longer lengths of stay and can have significant increases in episode costs; up to $25,000 versus $12,500 per episode for non-malnourished adults. Despite the negative impact on patient outcomes, malnutrition diagnoses are not made in a large number of clinically indicated cases. The AHRQ analysis reports only 7.1% of patients discharged from U.S. hospitals have a documented malnutrition diagnosis. This new study also estimates the economic impact of malnutrition in the hospital to be $42 billion. Similar evidence confirms that many patients showing clinical signs of malnutrition fail to receive diagnoses by medical providers as recommended by expert consensus. , , As recovery, rehabilitation time and functional independence may be significantly improved by preventing and treating malnutrition, MUC16-344 is a “measure that matters” for patients, families and providers. Diagnosis of malnutrition and appropriate documentation is an important step to confirm results of a nutrition assessment, communicate nutritional status to other providers within the hospital to ensure the care plan is implemented and that malnutrition is included on the condition list to provide continuity of care with integration into discharge planning. The dietitian conducts an assessment and makes a recommendation of nutritional status in the medical record, but until the physician documents the diagnosis the care plan and nutrition orders are not consistently implemented and nutritional status is not consistently communicated to the next in line provider. CMS has also acknowledged that documentation of a malnutrition diagnosis is an important component of proper discharge planning and/or transitions of care to post-acute providers. Reporting MUC16-344 is low burden as it is an eCQM and can help the interdisciplinary care team close gaps and to deliver high quality malnutrition care; i.e., improve quality of initial management, care coordination, follow-up care and patient outcomes. In summary, the malnutrition electronic clinical quality measures (eCQMs) are fully developed and data collection is low burden. The malnutrition eCQM set addresses CMS HIQR priorities as these process measures collectively will help to fill a measure gap, improve quality across the patient-focused episode of care, and engage patients and their families as partners in care delivery. The malnutrition eCQMs also align with NQS priorities by improving patient safety (decreased preventable readmissions and complications), care coordination, patient and family centered care (activation/engagement), population health (prevention and management of elderly and high impact Medicare conditions), and efficiency (reduced costs). (Submitted by: AdvaMed)
  
  

• Baxter Healthcare Corporation supports the proposed new quality measure, MUC16-372: Nutrition Care Plan for Patients Identified as Malnourished After a Completed Nutrition Assessment. We appreciate that Centers for Medicare & Medicaid Services (CMS) has considered this measure and included it on its list for evaluation by the Measure Applications Partnership (MAP). For the reasons discussed below, we strongly urge the MAP to recommend the measure for inclusion in the Hospital Inpatient Quality Reporting (HIQR) program. Baxter is a global leader in assisting healthcare professionals and their patients with the treatment of complex medical conditions, including cancer, infectious diseases, kidney disease, trauma, and other conditions. The company applies its expertise in medical devices and pharmaceuticals, to make a meaningful difference in patients’ lives. Baxter has been an innovator in intravenous nutritional support products since the 1940’s and a collaborator in the examination of malnutrition in conjunction with external healthcare organizations and the Federal government. Malnutrition remains an underdiagnosed and untreated condition, especially with respect to our nation’s elderly patients, with rates of malnutrition as high as 39%, and with recent data that show that the problem is not improving.1,2 As illustrated in the Agency for Healthcare and Research Quality’s recently published statistical brief, malnutrition tends to have a greater impact on the elderly, it increases lengths of stay up to 100%, it can lead to twice as costly episodes of care, reduce discharges to home and is associated more often to in-hospital death than the average of all inpatient nonmaternal/non-neonatal stays.3 Quality measure MUC16-372 is critically important to reducing the variation in care that exists across different institutions in terms of following through with the recommended nutrition care process and accurately documenting the findings of each step in a standardized fashion. Hospitals that implement validated assessment processes should have standardized terminology for documenting assessment results as well as the components of a nutrition care plan.5 In the literature, the variation across institutions with respect to following through with the recommended nutrition care process and accurately documenting the findings of each step is evident in highly underreported rates of malnutrition using claims-based data sources which do not agree with dozens of studies showing significantly higher rates of malnutrition. By using MUC16-372 which will track the follow-through with standardized nutrition assessment processes as recommended by multiple guidelines 6,7,8 hospitals will begin to improve their performance on this metric. Such success would facilitate achievement of the quality improvement goal of proper nutrition care planning and documentation of malnutrition findings in order to allow for proper continuity of care and coordination of services. A 2014 survey of over 1,700 providers of nutrition care illustrates the gap in care evident in real world practice: only 69% of surveyed providers are documenting findings of the nutrition screening in their medical record, and even more concerning is that as many as 40% of providers are not following through with the care for at-risk patients more than 50% of the time, leaving many without a proper assessment and nutrition care plan if they are found to be malnourished.9 We strongly believe that MUC16-372: Nutrition Care Plan for Patients Identified as Malnourished After a Completed Nutrition Assessment will help to address a major gap in care that, if left unaddressed, will continue to lead to preventable adverse outcomes for hospitalized patients and urge the MAP to recommend inclusion in the HIQR program. Thank you for your time and consideration of our comments. Sincerely, Crystal A. Riley, PharmD, MHA, MBA Senior Manager, Healthcare Policy & Reimbursement Baxter Healthcare 1. Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. 2. Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. 3. Weiss AJ, Fingar KR, Barrett ML, Elixhauser A, Steiner CA, Guenter P, Brown MH. Characteristics of Hospital Stays Involving Malnutrition, 2013. HCUP Statistical Brief #210. September 2016. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb210-Malnutrition-Hospital-Stays-2013.pdf. 4. White JV, Guenter P, Jensen G, et al. Consensus statement: Academy of Nutrition and Dietetics and American Society for Parenteral and Enteral Nutrition: characteristics recommended for the identification and documentation of adult malnutrition (undernutrition). JPEN J Parenter Enteral Nutr. 2012;36(3):275-83. 5. Cederholm T, Barazzoni R, Austin P, et al. ESPEN guidelines on definitions and terminology of clinical nutrition. Clin Nutr. 2016; http://dx.doi.org/10.1016/j.clnu.2016.09.004. 6. British Association for Parenteral and Enteral Nutrition. Malnutrition Matters, A Toolkit for Clinical Commissioning Groups and providers in England. Published 2012. Retrieved from: http://www.bapen.org.uk/pdfs/bapen_pubs/bapen-toolkit-for-commissioners-and-providers.pdf. 7. Academy of Nutrition & Dietetics. CI: Nutrition Assessment of Critically Ill Adults 2012. Academy of Nutrition & Dietetics Evidence Analysis Library. Published 2012. Retrieved from: http://www.andeal.org/topic.cfm?menu=4800. 8. Patel V, Romano M, Corkins MR, et al. Nutrition Screening and Assessment in Hospitalized Patients: A Survey of Current Practice in the United States. Nutr Clin Pract. 2014;29(4):483-490. (Submitted by: Baxter Healthcare Corporation)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: American Society for Parenteral and Enteral Nutrition)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: The American Society for Parenteral and Enteral Nutrition)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: Rocky Mountain Hospital for Children)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: Computrition, Inc.)
  
  
• Malnutrition treatment can lead to reduction in complications and readmissions. While we support the concept of these measures they should be field tested and reviewed for NQF endorsement. For example, field testing and endorsement should consider if there are condition-specific exclusions that may cause malnutrition (e.g. cancer). While it is still necessary to address malnutrition for patients with those conditions, the screening tools and treatment needed to address malnutrition will vary (Submitted by: Premier)
  
  
• The Joint Commission appreciates the opportunity to submit comments in support of inclusion of this measure in the Hospital Inpatient Quality Reporting Program and the suite of measures (MUC16-294, MUC16-296, MUC16-344 and MUC16-372) addressing malnutrition developed by Avalere and the Academy of Nutrition and Dietetics. Joint Commission standards have long reflected the importance of nutrition screening, assessment of at-risk hospitalized patients, diagnosis of malnutrition and appropriate intervention. Malnutrition is an ongoing healthcare issue with demonstrated impacts on patient outcomes. It is a condition that remains underdiagnosed and untreated, especially with respect to our nation’s elderly patients, with rates for elderly patients in the hospital as high as 39%.[1], [2] The Joint Commission welcomes the advent of performance measures to quantify the degree to which these best practices are carried out. These evidence-based measures were developed in accordance with a rigorous, multi-stakeholder process. They have been completely tested and have been shown to have the capacity to significantly improve the health and well-being of patients. ________________________________________ [1] Kaiser MJ, Bauer JM, Rämsch C, et al. Frequency of malnutrition in older adults: a multinational perspective using the mini nutritional assessment. J Am Geriatr Soc. 2010;58(9):1734-8. [2] Pereira GF, Bulik CM, Weaver MA, Holland WC, Platts-mills TF. Malnutrition among cognitively intact, noncritically ill older adults in the emergency department. Ann Emerg Med. 2015;65(1):85-91. (Submitted by: The Joint Commission)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: American Nurses Association (ANA))
  
  
• Upon malnutrition screening and appropriate assessment of at-risk patients, the nutrition intervention is developed using the NCP. Use of appropriate malnutrition language and terminologies (via the mapping of eNCPT to clinical and/or reimbursement terminologies), the intervention can be included in the electronic Care Plan. Selection of appropriate terminology possible for a problem-etiology-signs/symptoms documentation allows for structured coded data which is consistent with other areas of an EHR. Health IT systems can be designed with clinical decision support embedded in the nutrition assessment component by pulling discrete data from elsewhere in the patient’s record. Innovation in system design can be leveraged to confirm and prompt appropriate assessment using check boxes for etiology of malnutrition. To assure that nutrition care plans and critical nutrition data follows patients across care settings, the Academy has worked to have the NCP included in the HL7 Consolidated Clinical Document Architecture (C-CDA) Release 2.1 . Malnutrition data should be submitted via the appropriate guidance according to the document type utilized. Nutrition is included in 7 different document templates (including a Care Plan document template), has a Nutrition Section-level template and three entry-level templates. Academy work is underway to provide additional guidance and collaborate with EHR vendors to make nutrition care plans interoperable across care settings. Design of EHR systems which supports coded and free text nutrition data can be interoperable via the HL7 C-CDA R2.1 standard; this also supports use of clinical data for malnutrition reporting via the malnutrition eCQMs. (Submitted by: Lindsey Hoggle, MS RDN PMP)
  
  
• Ignore J&J prior submission for this measure, as commented our recommendation pertained to 16-72 (not 16-372). At this time we are not commenting on MUC 16-372. Thank you. (Submitted by: Johnson & Johnson )
  
  
• MUC16-372 Nutrition Care Plan for Patients Identified as Malnourished after a Completed Nutrition Assessment Given the critical role of nutrition intervention in improving patient outcomes and reducing costs, and the lack of associated quality measures, AdvaMed urges the MAP to support adoption of MUC16-372 Nutrition Care Plan for Patients Identified as Malnourished after a Completed Nutrition Assessment in the Hospital Inpatient Quality Reporting Program (HIQR). As recovery, rehabilitation time and functional independence may be significantly improved by preventing and treating malnutrition, MUC16-372 is a “measure that matters” for patients, families and providers. Documenting recommendations for care in a care plan is recommended by numerous guidelines to deliver standard, consistent, high quality care. , , Development and documentation of the nutrition care plan is driven by the nutrition assessment and is required to record vital patient care information, including nutrition status, diagnosis, monitoring recommendations, and interventions. Standardized terminology should be implemented for documenting assessment results, as well as the components of a nutrition care plan. This is critical for care plan implementation and continuity of care upon discharge. The nutrition assessment-based care plan is the communication mechanism to all clinicians who interact with the patient. Moreover, it reflects the patient’s preferences, the care provided in the hospital setting and becomes the information communicated to the next-in-line provider. As such, documentation of the care plan in a standardized, structured, and consistent manner is a critical activity for care provision in the acute setting and to support care transitions and appropriate nutrition support beyond the hospital. Reporting MUC16-372 is low burden as it is an eCQM and will help the interdisciplinary care team close gaps and deliver quality malnutrition care; i.e., improve quality of initial management, follow-up care, care coordination, and patient outcomes. Malnutrition is an independent predictor of mortality, length of stay, unplanned readmissions and hospital costs. Malnutrition is also an underlying risk factor for other HHS priorities including patient safety (HACs), high impact and multiple chronic conditions, diabetes control , and healthcare disparities. Patients who are malnourished while in the hospital have a greater risk of complications, falls, pressure ulcers, infections, readmissions, and length of stay, which is associated with up to a 300% increase in costs Studies have also shown hospital patients at risk for malnutrition are more likely to be discharged to another facility or require ongoing health services after leaving the hospital than patients not at risk for malnutrition. In summary, the malnutrition electronic clinical quality measures (eCQMs) are fully developed and data collection is low burden. The malnutrition eCQM set addresses CMS HIQR priorities as these process measures collectively will help to fill a measure gap, improve quality across the patient-focused episode of care, and engage patients and their families as partners in care delivery. The malnutrition eCQMs also align with NQS priorities by improving patient safety (decreased preventable readmissions and complications), care coordination, patient and family centered care (activation/engagement), population health (prevention and management of elderly and high impact Medicare conditions), and efficiency (reduced costs). (Submitted by: AdvaMed)
  
  
• Upon identification of risk, the second step involves completing a nutrition assessment for patients found to be at risk of malnutrition by a registered dietitian, as addressed in MUC16-296. The completion of a nutrition assessment allows dietitians to assess comprehensively the nutritional status of a patient based on multiple clinical characteristics and is an important activity to confirm the nutritional status of at-risk patients. It also facilitates appropriate follow up care for patients who are found to be malnourished, as the dietitian’s assessment and associated results typically forms the foundation for the development of a care plan with appropriate interventions. The third step, development and documentation of a nutrition care plan as reflected in MUC16-372, uses the information from the nutrition assessment to capture recommended care for the patient and communicate this information to other providers. The information contained in the nutrition care plan also forms the basis for information communicated to the next-in-line provider, a critical activity to enable effective care transitions beyond the hospital. After the nutrition assessment is completed and concurrent with care plan development, a medical provider should review the results of the dietitian assessment to confirm findings and document a diagnosis for patients found to be malnourished, as captured in MUC16-344. Lack of provider diagnosis frequently limits the communication of important patient information to other clinicians and next-in-line providers, leading patients’ malnutrition to go unrecognized and potentially contributing to negative patient outcomes. (Submitted by: Academy of Nutrition and Dietetics & Avalere Health)
  
  
• Malnutrition is an independent predictor of negative patient outcomes including morbidity, mortality, length of hospital stay, preventable readmissions, and hospitalization costs reaching approximately $42 billion in 2013. Despite recent research that finds that 33% to 54% of hospitalized older adults have malnutrition, there are currently no quality measures addressing the appropriate identification and treatment of malnutrition in the hospital. Therefore, we strongly recommend that the four electronic clinical quality measures (eCQMs) submitted by the Academy of Nutrition and Dietetics that address screening, assessment, care planning, and diagnosis of malnutrition in the hospital be included in the Hospital Inpatient Quality Reporting Program. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: University of Michigan Health System)
  
  
• As Chief Science Officer of the Academy of Nutrition and Dietetics, I strongly support the measure for nutrition care plan for patients identified as malnourished after a completed nutrition assessment be included in the Hospital Inpatient Quality Reporting Program. It is widely recognized that patients diagnosed with malnutrition have worse outcomes and have higher costs than patients who are well nourished. Patients who have malnutrition need a comprehensive and multidisciplinary nutrition care to ameliorate the potential negative impact of the condition. Incorporating these four eCQMs into the program will allow hospitals to more comprehensively track whether appropriate malnutrition care is being delivered and will generate the necessary building blocks to a comprehensive malnutrition outcome measure. (Submitted by: Academy of Nutrition and Dietetics)
  
  

• The AUA is generally supportive of PROMs and the use of tools to assess functional status outcomes. (Submitted by: American Urological Association)
  
  
• Support under the following conditions: change description from "non-metastatic prostate cancer patients" to "patients with non-metastatic prostate cancer." Patients do not equal their cancer. In this context, cancer is an adjective describing the patient but should be a noun, distinct from the patient. (Submitted by: National Comprehensive Cancer Network)
  
  

• M3 is appreciative of the MUCs listed that incorporate behavioral health issues such as: • tobacco use screening & treatment (MUC16-50 to 52) • alcohol screening & treatment (MUC16-178 to 180) • opioid safety, screening & use (MUC16-167 & 428) • anxiety related to hospice care (MUC16-39) • harm to self for patients with dementia & their caregivers (MUC16-317) The current list of MUC touches on several mental health issues in tangential ways as seen from the list above. The MAP can drive the healthcare system to higher performance through the use mental measurement system that can be used across healthcare settings, reports functional status, addresses patient safety, provides longitudinal comparisons, reports results electronically, and fills gaps for multiple behavioral health conditions, rather than just depression. With this in mind M3 recommends the endorsement by NQF of NQF-2620. NQF-2620 measures the percentage of people in primary care settings who have had an annual multi-dimensional mental health screening assessment, which is operationally defined as "a validated screening tool that screens for the presence or risk of having the more common psychiatric conditions, which for this measure include major depression, bipolar disorder, PTSD, one or more anxiety disorders (specifically, panic disorder, generalized anxiety disorder, obsessive-compulsive disorder, and/or social phobia), and substance abuse." (Kessler RC, NEJM 2005; 352(24): 2515) among the most common behavioral health conditions, and there exist multi-dimensional behavioral health assessment tools that can be used across primary and specialty care settings (Kennedy Forum 2016, A Core Set of Outcome Measures for Behavioral Health Across Service Settings). MUC 16-428 (identification of use of opioids inpts at psychiatric hosp) - M3 applauds the attention to the opioid epidemic through urine screening. M3 recommends continued patient follow-up through routine screening and measurement with a multidimensional mental health and substance use disorder tool. This would identify individuals continuing to use opioids who may have other underlying mental health diagnoses exacerbated by the opioid use. One tool with multiple cloud based screens and measures decreases the clinical workflow burden. The challenge is for NQF to endorse NQF-2620. (Submitted by: M3 Information, 155 Gibbs St #522 Rockville, MD 20850)
  
  

• It appears to me that the exclusions identified for the numerator should be exclusions from the denominator? Perhaps I do not understand what this is intended to measure? (Submitted by: Community Health Systems)
  
  
• The urine drug screen is common practice for inpatient psychiatric admissions, so this does not create a major change in procedure. The PDMP is burdensome if no risk is determined, but it is possible that the PDMP requirement be waived if opiates are not detected on the urine screen. We also question the ease with which PDMP programs are accessible. They are often monitored by state oversight programs and it might not be appropriate to access them for low-risk patients as part of a routine screening. (Submitted by: American Psychiatric Association)
  
  
• NAPHS recognizes the importance of identification of opioid use disorder. MUC16-428 is not a fully developed, specified, or tested measure. We feel it needs significantly more work including field-engagement and endorsement before it is implemented as a quality measure. (Submitted by: National Association of Psychiatric Health Systems)
  
  

Navigating the Discussion Guide

• How do I get back to the section I was just looking at?
  The easiest way is to use the back button on your browser. Other options are using your backspace button (which works for many browsers on laptops), or using the permanent links at the upper right hand corner of the discussion guide. But the back button is the best choice in most situations.
  
  
• Can I print the discussion guide out?
  You can, but we don't recommend it. Besides using a lot of paper (probably a couple hundred pages at least), you'll lose all the links that allow you to move around the document. For instance, if you're scrolling through the agenda and want to see more information about a particular measure, the electronic format will allow you to click a link, read more, and then bo back. If you're on paper, there will be a lot of flipping through paper.
  
  
• If I can't print this out, how can I read it on the plane?
  We will send you a pdf/Adobe Acrobat file a few days before the meeting, which will hopefully be useful when you're reviewing the discussion guide as you travel to Washington, DC.
  
  
• How do I know that I'm looking at the most recent version?
  At the top left corner of the discussion guide is a version number. At the beginning of the in person meetings, the NQF staff will ask everyone to load the most recent discussion guide version and will check that everyone has the same version loaded.
  
  
• What electronic devices can I use to view the discussion guide?
  We tried to make this as universal as possible, so it should work on your laptop (PC, Mac, Linux), your tablet (iPad, Android), or your phone (iPhone, Android). It should also work on many types of browsers (IE, Firefox, Chrome, Safari, Opera, Dolphin,....). Please let us know if you have any problems, and we'll troubleshoot with you (and improve the discussion guide for the next go around).
  
  
• Why do I see weird characters in some places?
  Because we're joining data from many different sources, we do find some technical challenges. This generally shows up as strange characters--extra question marks, accented characters, or otherwise unusual items. We've been able to fix many of these problems, but not all. We ask that you bear with us as we improve this over time!
  
  

Content

• What is included in the discussion guide?
  There are four sections within this document:
  • Agenda, with summaries of each measure under consideration
  • Full information about each measure, including its specifications, preliminary analysis of how this measure can advance the program's goals, and the rationale by HHS for being included in the list
  • Summaries for each federal health program being considered
  • Public comments that have been received to date (Note that the discussion guide may be released before the public comment period is finished, in which case there will just be a placeholder for where comments will go)
  
  
• How are the meeting discussions organized?
  The meeting sessions are organized around consent calendars, which are groups of measures being considered for a particular program or groups of measures for a particular condition or topic area. For each measure being discussed, this document will show you the description, the public comments (if any), the summary of the preliminary analysis, and the result of the preliminary analysis algorithm.

Remote Participation Instructions:

• Direct your web browser to: http://nqf.commpartners.com/.
• Under “Enter a Meeting” type in the meeting number for Day 1: 384974 or for Day 2: 180773
• In the “Display Name” field, type in your first and last names and click “Enter Meeting.”

• Dial (888) 802-7237 for workgroup members or (877) 303-9138 for public participants to access the audio platform.