NQF

Agenda Synopsis

Full Agenda

Measure Index

• Toxic Anterior Segment Syndrome (TASS) Outcome (Public comments received:4; MUC ID: MUC15-1047)
  
  

• Avoidance of Utilization of High Ultrafiltration Rate (= 13 ml/kg/hour) (Public comments received:1; MUC ID: MUC15-758)
  
  
• ESRD Vaccination: Full-Season Influenza Vaccination (Public comments received:4; MUC ID: MUC15-761)
  
  
• Measurement of Phosphorus Concentration (Public comments received:1; MUC ID: MUC15-1136)
  
  
• Proportion of Patients with Hypercalcemia (NQF #1454) (Public comments received:1; MUC ID: MUC15-1165)
  
  
• Standardized Hospitalization Ratio - Modified (Public comments received:2; MUC ID: MUC15-693)
  
  
• Standardized Mortality Ratio - Modified (Public comments received:2; MUC ID: MUC15-575)
  
  
• Standardized Readmission Ratio (SRR) for dialysis facilities (Public comments received:1; MUC ID: MUC15-1167)
  
  

• American College of Surgeons-Centers for Disease Control and Prevention (ACS-CDC) Harmonized Procedure Specific Surgical Site Infection (SSI) Outcome Measure (Public comments received:4; MUC ID: MUC15-534)
  
  
• Patient Safety and Adverse Events Composite (Public comments received:3; MUC ID: MUC15-604)
  
  

• Adult Local Current Smoking Prevalence (Public comments received:3; MUC ID: MUC15-1013)
  
  
• American College of Surgeons-Centers for Disease Control and Prevention (ACS-CDC) Harmonized Procedure Specific Surgical Site Infection (SSI) Outcome Measure (Public comments received:2; MUC ID: MUC15-534)
  
  
• Aortic Aneurysm Procedure Clinical Episode-Based Payment Measure (Public comments received:4; MUC ID: MUC15-835)
  
  
• Cholecystectomy and Common Duct Exploration Clinical Episode-Based Payment Measure (Public comments received:3; MUC ID: MUC15-836)
  
  
• Excess Days in Acute Care after Hospitalization for Pneumonia (Public comments received:2; MUC ID: MUC15-391)
  
  
• Hospital 30-Day Mortality Following Acute Ischemic Stroke Hospitalization Measure (Public comments received:3; MUC ID: MUC15-294)
  
  
• Hospital-level, risk-standardized 30-day episode-of-care payment measure for pneumonia (Public comments received:3; MUC ID: MUC15-378)
  
  
• Hybrid 30-Day Risk-Standardized Acute Ischemic Stroke Mortality Measure with Claims and Clinical Electronic Health Record (EHR) Risk Adjustment Variables (Public comments received:2; MUC ID: MUC15-1135)
  
  
• Hybrid 30-Day Risk-Standardized Acute Ischemic Stroke Mortality Measure with Electronic Health Record (EHR)-Extracted Risk Adjustment Variables (Public comments received:3; MUC ID: MUC15-1033)
  
  
• INR Monitoring for Individuals on Warfarin after Hospital Discharge (Public comments received:2; MUC ID: MUC15-1015)
  
  
• IQI-22: Vaginal Birth After Cesarean (VBAC) Delivery Rate, Uncomplicated (Public comments received:3; MUC ID: MUC15-1083)
  
  
• National Healthcare Safety Network (NHSN) Antimicrobial Use Measure (Public comments received:3; MUC ID: MUC15-531)
  
  
• Patient Safety and Adverse Events Composite (Public comments received:4; MUC ID: MUC15-604)
  
  
• Spinal Fusion Clinical Episode-Based Payment Measure (Public comments received:4; MUC ID: MUC15-837)
  
  
• Transurethral Resection of the Prostate (TURP) for Benign Prostatic Hyperplasia Clinical Episode-Based Payment Measure (Public comments received:2; MUC ID: MUC15-838)
  
  

• Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy (Public comments received:2; MUC ID: MUC15-951)
  
  
• Risk-standardized hospital visits within 7 days after hospital outpatient surgery (Public comments received:6; MUC ID: MUC15-982)
  
  

• American College of Surgeons-Centers for Disease Control and Prevention (ACS-CDC) Harmonized Procedure Specific Surgical Site Infection (SSI) Outcome Measure (Public comments received:2; MUC ID: MUC15-534)
  
  
• Cellulitis Clinical Episode-Based Payment Measure (Public comments received:4; MUC ID: MUC15-1143)
  
  
• Gastrointestinal Intestinal (GI) Hemorrhage Clinical Episode-Based Payment Measure (Public comments received:4; MUC ID: MUC15-1144)
  
  
• Hospital 30-Day, All-Cause, Risk-Standardized Mortality Rate (RSMR) Following Coronary Artery Bypass Graft (CABG) Surgery (Public comments received:3; MUC ID: MUC15-395)
  
  
• Hospital-level, risk-standardized 30-day episode-of-care payment measure for pneumonia (Public comments received:3; MUC ID: MUC15-378)
  
  
• Hospital-level, risk-standardized payment associated with a 30-day episode-of-care for Acute Myocardial Infarction (AMI) (Public comments received:3; MUC ID: MUC15-369)
  
  
• Hospital-level, risk-standardized payment associated with a 30-day episode-of-care for heart failure (HF) (Public comments received:3; MUC ID: MUC15-322)
  
  
• Hospital-level, risk-standardized payment associated with an episode of care for primary elective total hip and/or total knee arthroplasty (THA/TKA) (Public comments received:5; MUC ID: MUC15-295)
  
  
• Kidney/Urinary Tract Infection Clinical Episode-Based Payment Measure (Public comments received:3; MUC ID: MUC15-1145)
  
  
• Patient Safety and Adverse Events Composite (Public comments received:4; MUC ID: MUC15-604)
  
  

• Substance Use Core Measure Set (SUB)-3 Alcohol & Other Drug Use Disorder Treatment Provided or Offered at Discharge and SUB-3a Alcohol & Other Drug Use Disorder Treatment at Discharge (Public comments received:2; MUC ID: MUC15-1065)
  
  
• Thirty-day all-cause unplanned readmission following psychiatric hospitalization in an Inpatient Psychiatric Facility (IPF) (Public comments received:3; MUC ID: MUC15-1082)
  
  

• Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy (Public comments received:3; MUC ID: MUC15-951)
  
  
• American College of Surgeons-Centers for Disease Control and Prevention (ACS-CDC) Harmonized Procedure Specific Surgical Site Infection (SSI) Outcome Measure (Public comments received:2; MUC ID: MUC15-534)
  
  
• National Healthcare Safety Network (NHSN) Facility-wide Inpatient Hospital-onset Clostridium difficile Infection (CDI) Outcome Measure (Public comments received:3; MUC ID: MUC15-533)
  
  
• National Healthcare Safety Network (NHSN) Facility-wide Inpatient Hospital-onset Methicillin-resistant Staphylococcus aureus (MRSA) Bacteremia Outcome Measure (Public comments received:3; MUC ID: MUC15-532)
  
  
• Oncology: Radiation Dose Limits to Normal Tissues (Public comments received:1; MUC ID: MUC15-946)
  
  

Full Measure Information

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This measure is used to assess the number of ophthalmic anterior segment surgery patients diagnosed with TASS within 2 days of surgery.
  
  
• Numerator: All anterior segment surgery patients diagnosed with TASS within 2 days of surgery
  
  
• Denominator: All anterior segment surgery patients
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Administrative clinical data, Paper medical record, Other (physician diagnosis and report for numerator)
  
  
• Measure Type: Outcome
  
  
• Steward: Ambulatory Surgical Center (ASC) Quality Collaboration
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure does not necessarily fill a gap in the program measure set. Moreover, performance on the measure cannot be definitively attributed to the ambulatory surgical center; FDA investigations suggest device manufacturers are responsible for endotoxin contamination that leads to TASS.
  • Impact on quality of care for patients:The measure would add the first outcome measure to Effective Prevention and Treatment, and could improve on the existing cataract surgery measure by basing the results on medical records and physician diagnoses rather than patient self-report.
  
  
  
• Does the measure address a program goal or objective? Yes. Measure addresses ASCQR priority domain of ‘Effective Prevention and Treatment – surgical outcome measures’. TASS is a post-surgical complication.
  
  
• Is this a high-value measure? No. TASS is uncommon. Developers cite two cross-sectional studies reporting rates of 2.1% and 1.8%. However, over 3 million cataract surgeries are performed every year (http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm284239.htm), suggesting total case numbers of ~60,000 annually. While the treatment course of topical steroidal drops and close monitoring leads to ‘excellent’ outcomes [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4345267/ ], TASS can lead to severe complications including irreversible vision loss (Ozcelik ND, Eltutar K, Bilgin B. Toxic anterior segment syndrome after uncomplicated cataract surgery. Eur J Ophthalmol. 2010;20:106–114.) A clear performance gap has not been established. Developers cites ‘unpublished benchmarking data’ as evidence of a performance gap.While the FDA has linked some cases to contaminated ophthalmic devices, in other cases no apparent cause was found. The FDA has attributed some outbreaks of TASS to bacterial edotoxin from medical devices, and issued guidance to medical device manufacturers to limit endotoxin contamination (http://www.fda.gov/downloads/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/UCM393376.pdf). According to an FDA press release, recalls have been issued for several difference opthalmic devices. However, in other cases investigators were unable to determine the cause of the outbreak. (http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm284239.htm)
  
  
• Does this measure fill a gap in the program measure set? No. Two NQF-endorsed outcomes measures in ASC address similar outcomes: ASC-11 Cataracts, and ASC-4, All-Cause Hospital Transfer/Admission. The cataracts measure is most closely related; patients diagnosed with TASS would likely be reflected in the cataracts measure (a primary symptom is blurry vision), which measures the percentage of cataract surgery patients with a post-op improvement in visual function. Similarly, patients re-admitted to the hospital to treat TASS would count as hospital admissions.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested for the appropriate setting, but no reliability or validity testing results were mentioned or submitted.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. Not used in any other federal programs. The FDA’s investigation of TASS is primarily geared towards investigating outbreaks after they occur, and does not appear to use this measure. Two NQF-endorsed outcomes measures in ASC address similar outcomes: ASC-11 Cataracts, and ASC-4, All-Cause Hospital Transfer/Admission. The cataracts measure is most closely related; patients diagnosed with TASS would likely be reflected in the cataracts measure (a primary symptom is blurry vision), which measures the percentage of cataract surgery patients with a post-op improvement in visual function. Similarly, patients admitted to the hospital to treat TASS would count as hospital admissions.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  

Rationale for measure provided by HHS
Toxic anterior segment syndrome (TASS), an acute, noninfectious inflammation of the anterior segment of the eye, is a complication of anterior segment eye surgery that typically develops within 24 hours after surgery. Various contaminants, including those from surgical equipment or supplies, have been implicated as causes of TASS. Although most cases of TASS can be treated, the inflammatory response associated with TASS can cause serious damage to intraocular tissues, resulting in vision loss. Prevention requires careful attention to solutions, medications, and ophthalmic devices and to cleaning and sterilization of surgical equipment because of the numerous potential etiologies. Despite a recent focus on prevention, cases of TASS continue to occur, sometimes in clusters. The incidence of TASS is unknown, but frequencies of 1454 cases in approximately 69,000 surgeries (Bodnar et al, J Cataract Refract Surg. 2012 Nov;38(11):1902-10.) and 909 cases in 50,114 surgeries (Cutler et al, J Cataract Refract Surg. 2010 Jul;36(7):1073-80.) have been reported in cross-sectional studies in the literature. With millions of anterior segment surgeries being performed in the United States each year, measurement and public reporting have the potential to serve as an additional tool to drive further preventive efforts.

Measure Specifications

• NQF Number (if applicable): 2701
  
  
• Description: Percentage of adult in-center hemodialysis patients in the facility whose average ultrafiltration rate (UFR) is = 13 ml/kg/hour.
  
  
• Numerator: Number of patients* from the denominator whose average UFR >13 ml/kg/hour who receive an average of <240 minutes per treatment during the calculation period.** *To address the fact that patients may contribute varying amounts of time to the annual denominator population, results will be reported using a “patient-month” construction. ** The calculation period is defined as the same week that the monthly Kt/V is drawn.
  
  
• Denominator: Number of adult in-center hemodialysis patients in an outpatient dialysis facility undergoing chronic maintenance hemodialysis during the calculation period.
  
  
• Exclusions: 1. Patients <18 years of age (implicit in denominator definition). 2. Home dialysis patients (implicit in denominator definition). 3. Patients in a facility <30 days. 4. Patients with >4 hemodialysis treatments during the calculation period. 5. Patients with <7 hemodialysis treatments in the facility during the reporting month. 6. Patients without a completed CMS Medical Evidence Form (Form CMS-2728) in the reporting month. 7. Kidney transplant recipients with a functioning graft.(The endorsed specifications of the measure are: The following patients are excluded from the denominator population:1. Patients <18 years of age (implicit in denominator definition). 2. Home dialysis patients (implicit in denominator definition).3. Patients in a facility <30 days.4. Patients with >4 hemodialysis treatments during the calculation period.5. Patients with <7 hemodialysis treatments in the facility during the reporting month.6. Patients without a completed CMS Medical Evidence Form (Form CMS-2728) in the reporting month.7. Kidney transplant recipients with a functioning graft.8. Facilities treating <=25 adult in-center hemodialysis patients during the reporting month)
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: CROWNWeb
  
  
• Measure Type: Intermediate Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services, KCQA- Kidney Care Quality Alliance
  
  
• Endorsement Status: Endorsed October 2, 2015
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This NQF-endorsed measure fills a priority gap in the ESRD-QI program, measuring an intermediate outcome closely associated in the literature with severe adverse events, including elevated mortality. The measure has been tested at the appropriate level, and found to be valid and reliable. The measure is not expected to be burdensome to implement, as the necessary data elements exist already as part of the CROWNWeb repository.
  • Impact on quality of care for patients:Implementation of this measure could encourage providers to slow down and extend dialysis sessions, reducing mortality and other adverse events for patients. A wide variation in facility-level performance suggests potential for improved outcomes for many patients.
  
  
  
• Does the measure address a program goal or objective? Yes. Measure concerns Safety, a high-priority domain for the ESRD-QIP program as identified by CMS. Studies show patients with higher ultrafiltration rates have higher mortality, both all-cause and cardiovascular-related.?
  
  
• Is this a high-value measure? Yes. Measures an intermediate outcome that leads to increased mortality. (Flythe JE, Brunelli SM. The risks of high ultrafiltration rate in chronic hemodialysis: Implications for patient care. Semin Dial. 2011;24(3):259-265.) Analysis of performance data across over 4,000 dialysis facilities was submitted. Scores range from 0% to 50%, with a median of 10.88%. A standard deviation of 6.92 and IQR of 8.14 point to wide spread of performance scores.
  
  
• Does this measure fill a gap in the program measure set? Yes. Although the measure set includes a measure of dialysis patient mortality with risk adjustment (NQF #0369), this measure addresses an important intermediate outcome. Additionally, a high UFR is also an intermediate outcome to non-fatal adverse events, such as myocardial remodeling, fibrosis, and a reducation in cardiac function. No other measures in the set track UFR specifically
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Testing information was included as part of the measure’s submission to NQF for endorsement.Tested at the facility level. Reliability testing shows high (~0.65) intra-class correlation, and greater variation between facilities than within facilities. Validity testing includes both face and empirical testing. Face validity was confirmed by the KCQA Steering Committee, a KCQA workgroup, and polling of the KCQA. Empirical validity was conducted by correlating this measure with NQF #0369 and NQF #1463, facility-level measures of mortality and hospital admissions, respectively. This analysis found a low but statistically significant correlation between the measures. No risk adjustment. While one study found an association between gender, race, and 5-year mortality following dialysis sessions, the measure does not include any SDS adjustment. However, no RCTs have been done to firmly establish these differences.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The measure is not in use in other federal programs. However, no other federal programs (or at least none being considered by the MAP Committee) involve dialysis facilities. All necessary data elements are collected through CROWNWeb. The measure is not duplicative of other measures in the set.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed October 2, 2015
  
  

Rationale for measure provided by HHS
The measure focus is evidence-based, demonstrated as follows: • Health outcome: a rationale supports the relationship of the health outcome to processes or structures of care. Applies to patient-reported outcomes (PRO), including health-related quality of life/functional status, symptom/symptom burden, experience with care, health-related behavior. • Intermediate clinical outcome: a systematic assessment and grading of the quantity, quality, and consistency of the body of evidence that the measured intermediate clinical outcome leads to a desired health outcome. • Process: a systematic assessment and grading of the quantity, quality, and consistency of the body of evidence 4 that the measured process leads to a desired health outcome. • Structure: a systematic assessment and grading of the quantity, quality, and consistency of the body of evidence that the measured structure leads to a desired health outcome. • Efficiency: evidence not required for the resource use component.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Renal Measures
  
  
• Review for Importance: The measure meets the Importance criteria(1a. Evidence, 1b. Performance Gap)1a. Evidence: 0-H; 17-M; 2-L; 1-I; 1b. Performance Gap: 3-H; 16-M; 1-L; 0-I

  Rationale:

  • The measure is based on one Kidney Disease Outcomes Quality Initiative (KDOQI) clinical guideline and a systematic review of the evidence. The KDOQI clinical practice guidelines for hemodialysis adequacy: Achievement of optimal “dry” weight (CPG 5.1) gave the evidence a grade of A (high quality of evidence).
  • The developer clarified that the measure requires either having dialyzing patients at an average UFR =13 ml/kg/hour and/or dialyzing patients for an average of >240 minutes per session during the reporting period. Upon review of the evidence submitted, the Committee noted that none of the articles reviewed during the systemic review addressed those specific requirements and different cutoffs are listed for both the timeframe and UFR.
  • While voicing concerns about evidence, the Committee also noted that many of the dialysis measures focused on renal replacement dose have been recommended for movement into reserve status. In contrast, this measure, focused on a discrete intermediate clinical outcome, begins to breakdown in a more granular way some of the issues that are components of what the original Kt/V intended. The concern is there is not much known about this specific aspect of care because the industry has been concentrating on the more global measure. Upon review of performance gap, the Committee indicated data from 4,252 hemodialysis facilities, with over 412,000 patients, shows that there is significant gap with a median of 10.8%.
  • Overall, the Committee agreed there was evidence to support the measure and there was a need for a national performance standard.
  
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: 0-H; 19-M; 0-L; 0-I; 2b. Validity: 2-H; 16-M; 1-L; 0-I

  Rationale:

  • The reliability of the measure was assessed using a repeated measures analysis of variance (ANOVA) test. Using data from 4,252 dialysis facilities, the developer provided data that demonstrated an intra-class correlation coefficient between 0.6 and 0.7, indicating a good level of reliability within facilities over the course of the 12 months They also provided ratios of between-to within- facility correlation ranging 1.7 to 2.3; there is more variation between facilities than within facilities.
  • Clarification was requested on the exclusions. The measure excludes four or more treatments per month so it would count three maximum submissions for compliance. Overall, the Committee concluded the measure was reliable and differentiates between facilities.
  • The validity of the measure was evaluated by correlating facility-specific scores with each facility’s 2013 Standardized Hospitalization Ratio for Admissions measure (SHR, NQF #1463) and Standardized Mortality Ratio* measure (SMR, NQF #0369) scores, using Pearson’s Correlation Coefficient. The correlations were in the expected direction and statistically significant. The measure was also tested for validity at the level of the measure score by systematic assessment of face validity by a technical expert panel advising the measure developers. (*SMR specifications are based on a 4-year rolling period.)
  
  
  
• Review for Feasibility: 2-H; 15-M; 1-L; 1-I(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)

  Rationale:

  • The data source for this measure is CROWNWeb. The measure was tested using data from three KCQA member dialysis organizations, each with the capacity to provide retrospective analyses from a data warehouse/repository. The Committee expressed concerns that CROWNWeb currently only collect one data point and thus would need to be expanded to the three submissions during the week that the monthly Kt/V is drawn in order to monitor this measure. The developer reassured the Committee that they are in conversation with the Centers for Medicare and Medicaid Services (CMS) about adding the two extra data points so batch submitters could batch them together to form the three needed data points and all other facilities would have to manually enter the additional two in the manner they currently manually enter the one data point.
  • Overall, the Committee agreed data is being collected or generated and used by healthcare personnel during provision of care.
  
  
  
• Review for Usability: 2-H; 15-M; 1-L; 1-I(Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement, 4c. Susceptibility to inaccuracies/unintended consequences identified)

  Rationale: While the measure is not currently in use, the Committee agreed it has the potential to be used in public reporting, payment and quality improvement programs.
  
  

• Review for Related and Competing Measures:
  • This measure was identified as potentially related or competing with: NQF #2700 Ultrafiltration rate greater than 13 ml kg hr: Percentage of patients months for patients an ultrafiltration rate greater than 13 ml/kg/hr
  • NQF #2700 was not recommended by the Committee, so the Committee did not discuss the harmonization of these two measures.
  
  
  
• Endorsement Public Comments: Five commenters were generally in support of this measure.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: 19-Y; 0-N
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Percentage of ESRD patients = 6 months of age on October 1 and on chronic dialysis = 30 days in a facility at any point between October 1 and March 31 who either received an influenza vaccination, were offered and declined the vaccination, or were determined to have a medical contraindication.
  
  
• Numerator: Number of patients from the denominator who during the time from August 1 through March 31 (to be calculated and reported separately): 1) Received an influenza vaccination (documented by the dialysis provider, documented off-site vaccination, or patient self-report) 2) Were offered an influenza vaccination and declined 3) Were determined to have a medical contraindication
  
  
• Denominator: All patients alive and aged >/= 6 months on October 1 and on chronic dialysis >/= 30 days in a facility at any point between October 1 and March 31 (in-center or home dialysis)
  
  
• Exclusions: Patients younger than 6 months old Patients on chronic dialysis (as defined by a completed 2728 form or a REMIS/CROWNWeb record) for less than 30 days
  
  
• HHS NQS Priority: Best Practice of Healthy Living
  
  
• HHS Data Source: CROWNWeb
  
  
• 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: Conditional Support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:MUC-761 is a process measure consistent with CDC clinical guidelines and a necessary precursor to mitigate severe negative outcomes, including hospitalization and death. Influenza is particularly deadly and debilitating in the often immune-compromised ESRD population. While the measure has not been submitted for NQF endorsement, it has been fully tested at the appropriate level and setting, and is closely aligned with similar measures used in other CMS hospital quality programs.
  • Impact on quality of care for patients:CDC estimates indicate influenza is associated with approximately 36,000 deaths and 226,000 every year, and particularly affects immune-compromised individuals, including many ESRD patients. The literature suggests 20% or more of ESRD patients are unvaccinated, and the vaccination is associated with improved mortality.This measure is particularly sensitive to the dual-eligible population, who has higher than average rates of ESRD. This measure addresses a gap in care coordination and preventative services.
  
  
  
• Does the measure address a program goal or objective? Yes. ?CMS has listed patient safety as a high-priority domain for future measure consideraiton. ESRD patients are frequently immune-compromised, and vulnerable to infections.
  
  
• Is this a high-value measure? Yes. While MUC-761 measures a process, influenza vaccination is closely tied to important outcomes, as influenza leads to tens of thousands of deaths and hundreds of thousands of hospitalizations annually. This process is particularly important in the often immune-compromised ESRD population. This process matches CDC immunization clinical guidelines on influenza control, including exclusions. Use of the influenza vaccination is correlated with improved mortality in ESRD patients (http://www.ncbi.nlm.nih.gov/pubmed/22694948). A performance gap is established in the literature: immunization rates vary from less than 50% (http://www.ncbi.nlm.nih.gov/pubmed/12631142) to 80% (http://www.ncbi.nlm.nih.gov/pubmed/22694948).
  
  
• Does this measure fill a gap in the program measure set? Yes. This measure would be the first in the set to address the ‘Best Practices of Healthy Living’ NQS priority. No other measures in the set calculate the incidence of or vaccination against communicable diseases, for either patients or healthcare personnel.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested with dialysis facilities.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. Other CMS programs under consideration by MAP include identical measures for their facility types, including IQR and IPFQR. MUC-761 uses CROWNWeb data, and thus is unlikely to impose significant measurement or calculation burden.The ESRD QIP measure set does not include measures that capture the outcome of this process.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Influenza vaccination is universally recommended for all people aged 6 months and older. According to the CDC, seasonal influenza, which occurs between October and March/April of the following year, is associated with approximately 36,000 deaths and 226,000 hospitalizations annually. While overall rates of influenza infection are highest among children, rates of serious illness and mortality are highest among adults aged 65 years or older and children aged two years or younger as well as among immunocompromised patients, which include ESRD patients. The proposed influenza vaccination measure is a facility-level measure that applies to all dialysis patients. At the end of 2012 there were 413,725 patients being dialyzed, of whom 114,083 were new (incident) to dialysis.

Measure Specifications

• NQF Number (if applicable): 255
  
  
• Description: Percentage of all peritoneal dialysis and hemodialysis patient months with serum or plasma phosphorus measured at least once within the month.
  
  
• Numerator: Number of dialysis patient months in the denominator with serum or plasma phosphorus measured at least once within the reporting month.
  
  
• Denominator: Number of patient-months among in-center hemodialysis, home hemodialysis, or peritoneal dialysis patients under the care of the dialysis facility for the entire reporting month
  
  
• Exclusions: Exclusions that are implicit in the denominator definition include all patients who have not been in the facility the entire reporting month. There are no additional exclusions for this measure.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: CROWNWeb
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed on October 2, 2015.
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure, NQF#0255, tracks performance of a precursor process that is consistent with clinical guidelines to mitigate patient morbidity and mortality. The measure has been found to be reliable, valid, and not burdensome to calculate. This updated measure has been broadened to include pediatric patients and permit an alternative measurement mechanism, plasma phosphorous.
  • Impact on quality of care for patients:While the performance gap is small (mean performance is at 87%), the minimum performance is 0%, suggesting some facilities are not following this process at all. Moreover, over 500,000 patients were included in the developer’s analysis – even a difference of just a few percent means higher quality of care for tens of thousands of patients.
  
  
  
• Does the measure address a program goal or objective? Yes. This measure improves patient safety, a high-priority domain identified by CMS. Regulation of phosphorus levels is associated with improved morbidity and mortality, including stabilization of bone density, decreased bone pain, fracture prevention and decreased rates of arteriosclerosis and related conditions (e.g., stroke, heart attack).
  
  
• Is this a high-value measure? Yes. Although this is a process measure, it is a necessary precursor to physician efforts to mitigate significant adverse events tied to bone mineral imbalance, which can include bone pain, fractures, and arteriosclerosis and related conditions. Measuring phosphorous levels is necessary because symptoms of phosphorous deregulation may not present overtly before leading to a severe adverse event.The measure developer supplied an analysis of 6,073 facilities demonstrating a performance gap. Mean performance is at 87%, and the 75th percentile reaches 96%.
  
  
• Does this measure fill a gap in the program measure set? Yes. While there is another measure of bone mineral density (Proportion of Patients with Hypercalcemia, NQF#1454) in the set, clinical guidelines recommend measuring both phosporous and calcium levels (http://www2.kidney.org/professionals/KDOQI/guidelines_bone/Guide1.htm).This measure is an update to the Mineral Metabolism Measure currently in use in ESRD QIP. (based on NQF#0255). The measure specifications have changed to include patients under 18 years old, and permits both serum phosphorous and plasma phosphorous to be used in the measure. This measure was endorsed by NQF on October 2, 2015.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested at the facility level. Found to be both reliable and empirically validated (correlated with measure of mortality).While the measure developer found outcome disparities based on sex, race, ethnicity and age, they did not consider them clinically meaningful differences.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The measure is not in use in other federal programs; however, no other federal programs considered by MAP involve dialysis facilities. This measure is the best measure available for this particular process. All necessary data elements are collected through CROWNWeb, and should not be burdensome to calculate. While the measure set includes a measure of mortality (an outcome to this process measure), other outcomes that include significant adverse events such as bone breakage are not measured.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed on October 2, 2015.
  
  

Rationale for measure provided by HHS
Consistent monitoring of phosphorus levels helps ensure regulation of patient morbidity and mortality, including stabilization of bone density, decreased bone pain, fracture prevention and decreased rates of arteriosclerosis and related conditions (e.g., stroke, heart attack). Routine blood tests will also aid in detection of and monitoring for abnormal states phosphorus balance in this especially vulnerable population. Among the 6,073 facilities that have at least one eligible patient, we generated the following statistics of their performance scores (based on the patient month) using the January – December 2013 CROWNWeb clinical data: mean (SD)=87% (18%); min=0%; max=100%; 25th percentile=86%; 50th percentile=92%; 75th percentile=96%. A description of the data is included in questions 1.1-1.7 under “Scientific Acceptability”. Disparity analyses were performed among the entire eligible adult population (n=518,127) to examine the difference in performance scores by sex, race, ethnicity, and age. In particular, for each facility, the percent of patient-months by demographic group (sex, race, ethnicity, age) was calculated. Then, the facilities were divided into quintiles (Q1-Q5) based on the percentage of patient-months in the particular demographic category (i.e., a facility with percentage of females similar to the national median will be included in quintile 3). The top 20% of facilities in terms of rank, based on the percentages of females, were classified as Q5, while the bottom 20% of facilities were classified as Q1. Average (mean) performance for the measure was calculated for each quintile, and the means were examined for trend across quintiles (Q1-Q5). The Cochran-Armitage test for trend was performed to assess disparities in performance scores. All the results for each group across quintiles were statistically significant (p<0.0001), which imply that there are statistically significant changes in performance scores depending on sex, race, ethnicity, and age. While these differences are statistically significant, we did not determine them to be clinically meaningful differences. The mean performance scores for percent of patient-months with a phosphorus measurement in each quintile, by demographic group, are presented below. Facility Level Quintiles by Population Group (Quintile 1-5): Female(Q1=85.6%; Q2=88.0%; Q3=87.6%; Q4=88.3%; Q5=84.5%; P<0.0001) White (Q1=86.4%; Q2=85.5%; Q3=87.2%; Q4=87.3%; Q5=87.6%; P<0.0001) Black (Q1=86.9%; Q2=87.4%; Q3=87.1%; Q4=86.0%; Q5=86.7%; P<0.0001) Hispanic (Q1=85.2%; Q2=89.1%; Q3=87.6%; Q4=86.1%; Q5=86.8%; P<0.0001) Age>=65 (Q1=83.2%; Q2=88.0%; Q3=87.6%; Q4=87.4%; Q5=87.9%; P<0.0001) (note: age <18 was too small to calculate quintiles). In healthy individuals, the kidney occupies an integral, multi-faceted role in the maintenance of calcium-phosphorus homeostasis. It follows that abnormalities of calcium-phosphorus regulation are exceedingly common in patients with advanced chronic kidney disease, which, indeed, most data indicate that only 25-35% of dialysis patients are able to maintain calcium in the suggested target range of 8.4-9.5 mg/dL (KDOQI 2003). Numerous studies have demonstrated the impact of prolonged calcium-phosphorus dysregulation on patient morbidity and mortality (KDOQI 2003), which can lead to progressive bone weakness, bone pain and increased susceptibility to fractures, and severe arteriosclerosis that can precipitate strokes, heart attacks, and other adverse cardiac events. Unfortunately, overt symptoms can often remain unmanifested in many but the most extreme disordered states of calcium-phosphorus dysregulation, which is why routine blood tests are necessary to detect and monitor abnormal states of calcium and phosphorus balance in this especially vulnerable population. National Kidney Foundation. 2003. "K/DOQI Clinical Practice Guidelines for Bone Metabolism and Disease in Chronic Kidney Disease," American Journal of Kidney Disease, 42 (Suppl 3): S17. Found at: http://www.kidney.org/professionals/kdoqi/guidelines_bone/index.htm

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Renal (Aug 18 draft report available as of 9/17/15)
  
  
• Review for Importance: The measure meets the Importance criteria(1a. Evidence, 1b. Performance Gap)1a. Evidence: 6-H; 15-M; 0-L; 0-I; 1b. Performance Gap: 0-H; 6-M; 16-L; 1-IRationale:• The developer presents the measure focus as the facility´s process of measuring serum or plasma phosphorus each month for End Stage Renal Disease (ESRD) dialysis patients. They provided the following path as the process leads to the improvement of mortality: Measure serum or plasma phosphorus--> Assess value-->Identify problem-->Identify treatment options-->Administer the appropriate treatment-->Patient experiences improvement in mortality.• Developers also reference The Kidney Disease: Improving Global Outcomes (KDIGO) clinical practice guidelines, and cites additional sources of evidence. Three separate Technical Expert Panels (TEPs) were involved in the development and maintenance of the measure. The TEPs found no randomized control trials providing strong evidence to inform healthcare providers as to the efficacy of phosphorus lowering strategies on improvement in clinical outcomes.• The Committee discussed the measure evidence and found that the KDIGO guidelines provided did not match the measure specifications. KDIGO guidelines state for chronic kidney disease (CKD), phosphorous levels should be measured every one to three months and the measure requires a monthly phosphorous. The evidential data provided is largely focused around phosphate levels and not the act of measuring phosphate levels. Despite the discrepancy in the actual process of measuring phosphorous levels, the Committee rated this measure as moderately satisfying the evidence criteria.• Performance gap data provided by the developer noted that consistently monitoring phosphorous levels helps to ensure the regulation of patient morbidity and mortality. Additionally, routine blood tests will assist in the detection and monitoring for abnormal phosphorous balance.• Developers provided information on the performance scores of the more than 6,000 facilities that housed at least a single eligible patient. Using the 2013 CROWNWeb data, the median data were calculated at 92%.• Committee members noted the high percentage of performance at the 50th percentile stating there was not much room for improvement. Questioning whether or not there were factors to be improved upon, members agreed that there was only slight opportunity for improvement and voted to consider the measure for endorsement with reserve status.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: 4-H; 18-M; 0-L; 0-I; 2b. Validity: 3-H; 19-M; 1-L; 0-IRationale:• Some members asked for clarification of whether or not the denominator truly excluded patients who had not been in the facility for the entire month. Developers clarified that a patient must be out of the facility for an entire 30 calendar days during the reporting month to be included in the denominator exclusion.• The assessment of reliability was based on facility-level Pearson correlation coefficients between the current performance month and the previous month for 2013 reporting months (January – December 2013). Pearson correlation coefficients of each pair of the current and preceding months ranted from 0.72 – 0.90 and were statistically significant (p<0.0001). Monthly IURs ranged from 0.95 – 0.97.• There was confusion among committee members regarding the specifications related to transplant patients with functioning allografts. Additionally, inclusion of pediatric patients was a point of confusion since the evidence provided was only from adult patients.• Once the developer clarified that pediatric and adult patients were included in the denominator and in the testing, committee members concluded the measure was reliable and valid.
  
  
• Review for Feasibility: 18-H; 5-M; 0-L; 0-I(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)Rationale:• The data source for this measure is CROWNWeb. If patient data is missing in CROWNWeb, Medicare claims are used. Data is collected or generated and used by healthcare personnel during provision of care. The Committee had no major concerns with feasibility.
  
  
• Review for Usability: 17-H; 6-M; 0-L; 0-I(Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement, 4c. Susceptibility to inaccuracies/unintended consequences identified)Rationale:• The measure is currently in use in the End Stage Renal Disease Quality Improvement Program (ESRD QIP). The current use for quality improvement is internal and specific to the organization via the Renal Physicians Association (RPA) Quality Improvement Registry.• The measure was first publicly reported in the final QIP PY 2014 scores released in December 2013, so performance data over time cannot be assessed at this time. The Committee did not have any major concerns with the use and usability of this measure.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments: Three commenters were generally in support of this measure for reserve status.
  
  
• Endorsement Committee Recommendation: The measure was originally endorsed in 2007, re-endorsed in 2012 and is specified for use at the facility level. The Committee noted that while this is a process measure focused on monthly assessment of patient serum or plasma phosphorus, the evidence provided was not in direct alignment. Specifically, the KDIGO guidelines state for CKD, phosphorous levels should be measured every one to three months and the measure states a monthly phosphorous. The Committee rated this measure as moderately satisfying the evidence criteria. The Committee found the testing data supplied by the developer demonstrated adequate reliability, validity and feasibility of the measure. Committee members agreed that there was only slight opportunity for improvement and voted to recommend the measure for endorsement with reserve status. Standing Committee Recommendation for Endorsement with Potential for Reserve Status: 22-Y; 0-N
  
  

Measure Specifications

• NQF Number (if applicable): 1454
  
  
• Description: Percentage of adult dialysis patients with a 3-month rolling average of total uncorrected calcium (serum or plasma) greater than 10.2 mg/dL (hypercalcemia)
  
  
• Numerator: Number of patient-months in the denominator with 3-month rolling average of total uncorrected serum (or plasma) calcium greater than 10.2 mg/dL
  
  
• Denominator: Number of patient-months among adult (greater than or equal to 18 years old) in-center hemodialysis, home hemodialysis, or peritoneal dialysis patients under the care of the dialysis facility for the entire reporting month who have had ESRD for greater than 90 days.
  
  
• Exclusions: Exclusions that are implicit in the denominator definition include all patients who have not been in the facility the entire reporting month (transient patients), and patients who have had ESRD for <91 days. There are no additional exclusions for this measure.
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Data Source/Registry: CROWNWeb data from January 2013-December 2013.
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed on October 2, 2015.
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:MUC 1165 is an update to a measure previously in the ESRD QIP, is NQF-endorsed, and measures an outcome that is established in the literature as a correlate of cardiovascular disease and death. The measure has been appropriately tested. The update to the measure removed an incentive to non-measurement, and expanded the possible measurement to either serum or plasma, consistent with scientific consensus.
  • Impact on quality of care for patients:Validity testing showed a correlation between outcomes on this measure and worse mortality outcomes; an analysis of testing data estimated 15% of facilities are performing worse than expected, suggesting a performance gap. Implementing this updated measure is likely to encourage facilities performing below expectations to improve their standard of care, potentially improving patient safety for hundreds of thousands of dialysis patients nationwide.
  
  
  
• Does the measure address a program goal or objective? Yes. ?This patient safety measure addresses the high-priority domain for the ESRD QIP program by protecting against the overutilization of oral-only medications. This priority is new, the result of a recent decision to exclude oral-only medications from bundle payment. The measure meets program requirements by measuring bone mineral metabolism, and being NQF-endorsed.
  
  
• Is this a high-value measure? Yes. While this measure is an intermediate-outcome measure, hypercalcemia is associated with cadiovascular disease and mortality in ESRD patients (http://www.ncbi.nlm.nih.gov/pubmed/18514987; http://www.ncbi.nlm.nih.gov/pubmed/17576300). The measure follows recommendations of both a 2010 and 2013 clinical technical expert panel.A performance gap is established in the measure testing, finding that nearly 15% of facilities (876 total) performed worse than expected.
  
  
• Does this measure fill a gap in the program measure set? Yes. N/A – measure is currently in use in the ESRD QI program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Testing performed at the facility level in the ESRD setting. Reliability testing suggests that over half the monthly variation, and 86% of annual variation in the measure can be attributed to inter-facility differences.The measure was universally ratified by a CMS Technical Expert Panel in 2010, and again ratified in 2013. The measure has been endorsed by the National Quality Forum. Poisson regression modeling suggests a correlation between hypercalcemia outcomes and mortality outcomes at the facility level.
  
  
• Is the measure currently in use? Yes. NQF #1454 is currently used in the ESRD QI Program. This version of the measure has a change in the denominator, consistent with the measure as re-submitted to NQF during their periodic review of previously endorsed measures. On October 2, 2015, NQF endorsed the new version of the measure. The measure was changed in two ways. First, the denominator requirement of one calcium measurement in the past 90 days was removed, in order to discourage non-measurement. Second, the measure now permits reporting of either serum or plasma calcium values, consistent with a recent revision to a similar measure of phosphorous values. A literature review submitted as part of the NQF endorsement process found no significant differences between plasma and serum tests for calcium levels.
  
  
• Does a review of its performance history raise any concerns? . No. The measure was endorsed by NQF on October 2, 2015.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. Measures of bone mineral health are particular to the ESRD setting, and are not present in other programs considered by the MAP Hospital Workgroup. The implementation of the measure is unlikely to be burdensome, as the measure is entirely sourced from the electronic CROWNWeb database.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed on October 2, 2015.
  
  

Rationale for measure provided by HHS
In 2011, total Medicare costs for the ESRD program were $34.3 billion, a 5.4% increase from 2010 [14]. Abnormalities in serum levels of calcium and phosphorus, which are markers of mineral and bone disorder, are common among ESRD patients. Numerous studies have demonstrated the association of prolonged calcium and phosphorus dysregulation on patient morbidity and mortality [2,1]. In March 2010, the C- TEP recommended that a quality measure (CPM) for the upper limit of total serum calcium be calculated as the proportion of patients (calculated as patient months) with 3-month rolling average of total serum calcium greater than 10.2 mg/dL. This recommendation is consistent with the value indicated by a TEP held in 2006 and with the 2003 KDOQI guidelines [1]. The TEP in 2013 also reviewed the measures and recommended no changes to the current threshold. Since 10.2 mg/dl is the considered the upper limit of the normal range in the majority of clinical laboratories, this measure is also consistent with the published KDIGO guidelines [2]. Review of the currently available literature and evidence indicates that observational cohort studies show a consistent adverse association of hypercalcemia with cardiovascular events and all-cause mortality [3-7]. Clinical data demonstrate the association of increased serum calcium with vascular [8,9] and valvular calcifications [10]. The basic science also supports a pathological role of high calcium in promoting soft tissue and vascular calcification [11-13]. Although there are no interventional studies demonstrating the benefit of correcting hypercalcemia, there was unanimous agreement among the 2010 C-TEP members that calcium concentrations >10.2 mg/dL place the patient at increased risk of poor outcomes. Current guidelines indicate that clinical decision should be based on trends rather than single laboratory values [2]. Therefore, it was unanimously agreed to use a three-month rolling average for the reporting period. 1c.4. Citations for data demonstrating high priority provided in 1a.3 1) National Kidney Foundation: K/DOQI Clinical Practice Guidelines for Bone Metabolism and Disease in Chronic Kidney Disease. American Journal of Kidney Disease 2003 42:S1-S202 (suppl 3). 2) Kidney Disease: Improving Global Outcomes (KDIGO) CKD-MBD Work Group: KDIGO Clinical Practice Guideline for the Diagnosis, Evaluation, Prevention, and Treatment of Chronic Kidney Disease-Mineral and Bone Disorder (CKD-MBD). Kidney International 2009 76 (Suppl 113): S1-S130. 3) Block GA, Klassen PS, Lazarus JM, et al. Mineral metabolism, mortality, and morbidity in maintenance hemodialysis. Journal of the American Society of Nephrology : JASN 2004 15:2208-18. 4) Young EW, Albert JM, Satayathum S, et al. Predictors and consequences of altered mineral metabolism: the Dialysis Outcomes and Practice Patterns Study. Kidney international 2005 67:1179-87. 5) Kalantar-Zadeh K, Kuwae N, Regidor DL, et al. Survival predictability of time-varying indicators of bone disease in maintenance hemodialysis patients. Kidney international 2006 70:771-80. 6) Kimata N, Albert JM, Akiba T, et al. Association of mineral metabolism factors with all-cause and cardiovascular mortality in hemodialysis patients: the Japan dialysis outcomes and practice patterns study. Hemodialysis international. International Symposium on Home Hemodialysis 2007 11:340-8. 7) Tentori F, Blayney MJ, Albert JM, et al. Mortality risk for dialysis patients with different levels of serum calcium, phosphorus, and PTH: the Dialysis Outcomes and Practice Patterns Study (DOPPS). American journal of kidney diseases : the official journal of the National Kidney Foundation 2008 52:519-30. 8) Chertow G.M., Raggi P., Chasan-Taber S., Bommer J., Holzer H., Burke S.K. Determinants of progressive vascular calcification in haemodialysis patients. Nephrology Dialysis Transplantation 2004 19 (6), pp. 1489-1496. 9) Dhingra R, Sullivan LM, Fox CS, Wang TJ, D´Agostino RB Sr, Gaziano JM, Vasan RS: Relations of serum phosphorus and calcium levels to the incidence of cardiovascular disease in the community. Arch Intern Med 2007 167: 879–885. 10) Wang AY, Lam CW, Wang M, Chan IH, Lui SF, Sanderson JE. Is valvular calcification a part of the missing link between residual kidney function and cardiac hypertrophy in peritoneal dialysis patients? Clinical journal of the American Society of Nephrology 2009 4:1629-36. 11) Ketteler M, Schlieper G, Floege J. Calcification and cardiovascular health: new insights into an old phenomenon. Hypertension 2006 47:1027–1034. 12) Giachelli CM. Vascular calcification mechanisms. Journal of the American Society of Nephrology : JASN 2004 15:2959–2964. 13) Yang H, Curinga G, Giachelli CM. Elevated extracellular calcium levels induce smooth muscle cell matrix mineralization in vitro. Kidney Int. 2004;66(6):2293–2299. 14) U S Renal Data System, USRDS 2013 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2013.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Renal (Aug 18 draft report available as of 9/17/15)
  
  
• Review for Importance: The measure does not meet the Importance criteria(1a. Evidence, 1b. Performance Gap)1a. Evidence: 0-H; 1-M; 22-L; 0-I; Insufficient Evidence with Exception: 19-Y; 4-N; 1b. Performance Gap: 0-H; 0-M; 21-L; 2-I Reconsideration Performance Gap: 0-H; 7-M; 6-L; 5-IRationale:• For this intermediate outcome measure, evidence provided by the developer included two clinical guidelines and an April 2013 Technical Expert Panel (TEP) review. The Kidney Disease: Improving Global Outcomes (KDIGO) graded the evidence 2D, very low evidence, and the Kidney Disease Outcomes Quality Initiative (KDOQI) was expert opinion only. The TEP did not recommend any revisions to the measure.• While the Committee acknowledged that this measure was an important safety measure that filled a gap area in bone and mineral disease, members agreed that evidence demonstrating that calcium concentrations less than 10.2 mg/dL place the patient at increased risk of cardiovascular events and all-cause mortality was largely associative. The Committee allowed the measure to move forward on an evidence exception.• The developer provided January – December 2013 CROWNWeb clinical data on performance scores generated among 5,973 facilities that had at least one eligible patient that indicate the mean gap of performance is two point one percent.• Disparities data were also provided that imply that there are statistically significant changes in performance scores depending on sex, race, ethnicity, and age; however, the Committee found it was not a clinically meaningful difference.• The Committee concluded there was very little room for improvement and the current gap did not warrant a national performance measure.• The Committee considered the measure for endorsement with reserve status due to the fact that there were no other bone and mineral measures; however, determined that losing endorsement would not affect current performance of the measure.• Some committee members suggested lowering the measure threshold to allow for a greater gap in care, however, the developer stated there was no evidence for a lower threshold and two previous TEPs had supported the current threshold of less than 10.2 mg/dL.• The Committee encouraged the developer to consider alternative bone and mineral measures. The developer reassured the Committee that they have convened multiple TEPs in order to develop additional measures in this area but have not been successful thus far to create another strong, evidence supported measure in this area.• At the post-comment call, the Committee decided to reconsider this measure based on the information provided by the developer. While the measure did not pass the gap criterion, the Committee decided they would like to consider this measure for reserve status.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: 0-H; 15-M; 2-L; 0-I; 2b. Validity: 0-H; 17-M; 0-L; 0-IRationale:• The developer used CROWNWeb and Medicare claims data from January 2013 – December 2013 to calculate the inter-unit reliability (IUR) for the 12 month period to assess the reliability of this measure. The IUR is 0.86 with the confidence interval being 0.78 - 0.84. This suggests that 86% of variation in the measure is attributed to between facility variance. The Committee agreed that the testing results suggest this measure is reliable• The developer assessed validity using Poisson regression analysis to identify the predictive strength of facility level performance scores for hypercalcemia on mortality, using the 2013 standardized mortality ratio. The results of the Poisson regression suggest that facilities with a higher percentage of patient-months with hypercalcemia experience a higher standardized mortality rate relative to facilities with a lower percentage of patients with hypercalcemia. The Committee agreed that the testing results suggest the measure is valid.
  
  
• Review for Feasibility: 12-H; 5-M; 0-L; 0-I(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)Rationale:• The data elements required are routinely measured as part of patient care and can be derived from CROWNWeb and electronic health records. The Committee agreed that collection of this data is feasible.
  
  
• Review for Usability: 6-H; 12-M; 0-L; 0-I(Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement, 4c. Susceptibility to inaccuracies/unintended consequences identified)Rationale:The measure is currently in use in the Dialysis Facility Compare program. The Committee did not have any major concerns with the use and usability of this measure.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments: Two commenters agreed with the Committee’s initial recommendation to not endorse this measure citing a poor measure would be more harmful than no measure.

  Developer Response: During the recent DFC performance period, 1538 facilities had 0% of patients with hypercalcemia, 1494 facilities had 1% of patients with hypercalcemia, 889 facilities had 2%, 594 had 3%, and 1360 facilities had 4% or more of their patients with hypercalcemia. The distribution demonstrates the success of many facilities in their ability to achieve extremely low rates of hypercalcemia, as over 3000 facilities have 1% or less patients with hypercalcemia. However, when one looks at the average national performance of 2%, they may interpret that statistic as demonstrating the absence of a performance gap for this safety measure. That interpretation ignores the highly skewed distribution of facility performance for this safety measure as shown in the figure. For this safety measure, the performance gap is clearly demonstrated by comparing the 1360 US dialysis facilities (23% of the total reported facilities) with 4% or greater patients with hypercalcemia to the majority of dialysis facilities that achieve extremely low hypercalcemia rates. We maintain that the measure is important for safety monitoring, as nearly one-fourth of US dialysis facilities are relatively poor at preventing hypercalcemia, an intermediate outcome consistently associated with poorer patient survival and clearly influenced by providers’ bone and mineral disease management practices.
  
  

• Endorsement Committee Recommendation: This measure was originally endorsed in 2011 and is specified at the facility level. The measure is currently used in the CMS Dialysis Facility Compare public reporting program. While the Committee agreed that evidence was largely associative, they allowed the measure to move forward on an evidence exception due to it being considered an important safety measure that fills a gap area in bone and mineral disease. The Committee initially concluded there was very little opportunity for improvement and the 2.1% gap identified by the developer did not warrant a national performance measure. However, based on new data provided by the developer during the post comment call, the Committee agreed to consider the measure for endorsement with reserve status, noting there were no other bone and mineral measures available in the field. After review of the reliability, validity, feasibility, and usability of the measure, the Committee agreed that the measure should be recommended for endorsement with reserve status.

  Standing Committee Recommendation for Endorsement with Potential for Reserve Status: 19-Y; 0-N
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Standardized hospitalization ratio for admissions among ESRD dialysis patients.
  
  
• Numerator: Number of inpatient hospital admissions among eligible patients at the facility during the reporting period.
  
  
• Denominator: Number of hospital admissions that would be expected among eligible patients at the facility during the reporting period, given the patient mix at the facility.
  
  
• Exclusions: UM-KECC’s treatment history file provides a complete history of the status, location, and dialysis treatment modality of an ESRD patient from the date of the first ESRD service until the patient dies or the data collection cutoff date is reached. For each patient, a new record is created each time he/she changes facility or treatment modality. Each record represents a time period associated with a specific modality and dialysis facility. SIMS/CROWNWeb is the primary basis for placing patients at dialysis facilities and dialysis claims are used as an additional source. Information regarding first ESRD service date, death and transplant is obtained from additional sources including the CMS Medical Evidence Form (Form CMS-2728), transplant data from the Organ Procurement and Transplant Network (OPTN), the Death Notification Form (Form CMS-2746) and the Social Security Death Master File. As patients can receive dialysis treatment at more than one facility in a given year, we assign each patient day to a facility (or no facility, in some cases) based on a set of conventions below, which largely align with those for the Standardized Mortality Ratio (SMR). We detail patient inclusion criteria, facility assignment and how to count days at risk, all of which are required for the risk adjustment model. General Inclusion Criteria for Dialysis Patients Though a patient’s follow-up in the database can be incomplete during the first 90 days of ESRD therapy, we only include a patient’s follow-up into the tabulations after that patient has received chronic renal replacement therapy for at least 90 days. Thus, hospitalizations, mortality and survival during the first 90 days of ESRD do not enter into the calculations. This minimum 90-day period also assures that most patients are eligible for Medicare, either as their primary or secondary insurer. It also excludes from analysis patients who die or recover during the first 90 days of ESRD. In order to exclude patients who only received temporary dialysis therapy, we assigned patients to a facility only after they had been on dialysis there for the past 60 days. This 60 day period is used both for patients who started ESRD for the first time and for those who returned to dialysis after a transplant. That is, hospitalizations during the first 60 days of dialysis at a facility do not affect the SHR of that facility. Identifying Facility Treatment Histories for Each Patient For each patient, we identify the dialysis provider at each point in time. Starting with day 91 after onset of ESRD, we attribute patients to facilities according to the following rules. A patient is attributed to a facility once the patient has been treated there for the past 60 days. When a patient transfers from one facility to another, the patient continues to be attributed to the original facility for 60 days and then is attributed to the destination facility. In particular, a patient is attributed to their current facility on day 91 of ESRD if that facility had treated him or her for the past 60 days. If on day 91, the facility had not treated a patient for the past 60 days, we wait until the patient reaches day 60 of continuous treatment at that facility before attributing the patient to that facility. When a patient is not treated in a single facility for a span of 60 days (for instance, if there were two switches within 60 days of each other), we do not attribute that patient to any facility. Patients are removed from facilities three days prior to transplant in order to exclude the transplant hospitalization. Patients who withdrew from dialysis or recovered renal function remain assigned to their treatment facility for 60 days after withdrawal or recovery. If a period of one year passes with neither paid dialysis claims nor SIMS information to indicate that a patient was receiving dialysis treatment, we consider the patient lost to follow-up and do not include that patient in the analysis. If dialysis claims or other evidence of dialysis reappears, the patient is entered into analysis after 60 days of continuous therapy at a single facility. Days at Risk for Medicare Dialysis Patients After patient treatment histories are defined as described above, periods of follow-up in time since ESRD onset are created for each patient. In order to adjust for duration of ESRD appropriately, we define 6 time intervals with cut points at 6 months, 1 year, 2 years, 3 years and 5 years. A new time period begins each time the patient is determined to be at a different facility, or at the start of each calendar year or when crossing any of the above cut points. Since hospitalization data tend not to be as complete as mortality data, we include only patients whose Medicare billing records should include all hospitalizations. To achieve this goal, we require that patients reach a certain level of Medicare-paid dialysis bills to be included in the hospitalization statistics, or that patients have Medicare-paid inpatient claims during the period. Specifically, months within a given dialysis patient-period are used for SHR calculation when they meet the criterion of being within two months after a month with either: (a) $900+ of Medicare-paid dialysis claims OR (b) at least one Medicare-paid inpatient claim. The intention of this criterion is to assure completeness of information on hospitalizations for all patients included in the analysis. The number of days at risk in each of these patient-ESRD-facility-year time periods is used to calculate the expected number of hospital admissions for the patient during that period. The SHR for a facility is the ratio of the total number of observed hospitalizations to the total number of expected hospitalizations during all time periods at the facility. Based on a risk adjustment model for the overall national hospitalization rates, we compute the expected number of hospitalizations that would occur for each month that each patient is attributed to a given facility. The sum of all such expectations over patients and months yields the overall number of hospital admissions that would be expected given the specific patient mix and this forms the denominator of the measure. The denominator of the SHR stems from a proportional rates model (Lawless and Nadeau, 1995; Lin et al., 2000; Kalbfleisch and Prentice, 2002). This is the recurrent event analog of the well-known proportional hazards or Cox model (Cox, 1972; Kalbfleisch and Prentice, 2002). To accommodate large-scale data, we adopt a model with piecewise constant baseline rates (e.g. Cook and Lawless, 2007) and the computational methodology developed in Liu, Schaubel and Kalbfleisch (2012).
  
  
• HHS NQS Priority: Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: This measure is an update to NQF #1463, and has been submitted to NQF for endorsement maintenance with a decision pending in 2016. The update modifies the risk adjustment model.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:MUC-693 measures a critical outcome in a high-priority domain for the ESRD QIP program. ESRD patients average nearly two hospitalizations per year that burden patients and health systems alike. Hospitalizations are measured in other federal programs under consideration by the MAP Hospital Workgroup, including the OQR and ASCQR programs. MUC-693 is aligned with MUC-1167, a measure of readmissions.
  • Impact on quality of care for patients:There are over 600,000 ESRD cases in the U.S. currently, most of whom are receiving treatment at a dialysis facility. These patients average nearly two hospitalizations per year that burden patients and health systems alike. Reducing those hospitalizations would doubtless improve the general health and well-being of the ESRD population, as well as reduce costs for Medicare, which spends roughly 37% of its total outlay for ESRD patients on hospitalizations.
  
  
  
• Does the measure address a program goal or objective? Yes. ?CMS has listed Care Coordination as a high-priority domain for future measure consideration.
  
  
• Is this a high-value measure? Yes. MUC-693 directly measures hospital admissions, a ‘significant societal and financial burden’ with a ‘major negative impact on patients’ well-being and quality of life’ (http://www.usrds.org/2014/view/v2_04.aspx). Hospitalization rates of ESRD patients vary from 1.61-1.73 per year. Performance among facilities is normally distributed, with a standard deviation of 0.31 on a mean performance of 1.0. In effect, over 15% of facilities readmit over 30% more patients that expected given their case mix.
  
  
• Does this measure fill a gap in the program measure set? Yes. While the Readmissions (1167) measure under consideration assesses similar adverse events, the hospitalization measure uses a different denominator to capture a different aspect of dialysis facility hospitalization use. Thus, it is possible to have a facility perform quite differently on the two measures: for example, a facility might be managing patients well overall and minimizing hospitalizations, but see high readmissions, indicating a problem with transitions of care planning.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested at dialysis facilities.
  
  
• Is the measure currently in use? No. The endorsed version of NQF #1463 has been used in Dialysis Facility Compare since January 2013. This measure is an update to NQF #1463, and has been submitted to NQF for endorsement maintenance with a decision pending in 2016. The update enhances the risk adjustment model.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is harmonized with two other measures under consideration for the ESRD QIP: Mortality (MUC-575) and Readmissions (MUC-1167). Very similar hospitalization measures are used in the OQR and ASCQR programs.MUC-693 uses CROWNWeb data, and thus is unlikely to impose a significant measurement or calculation burden.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. This measure is an update to NQF #1463, and has been submitted to NQF for endorsement maintenance with a decision pending in 2016. The update modifies the risk adjustment model.
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
1b.1. Rationale Hospitalization rates are an important indicator of patient morbidity and quality of life. On average, dialysis patients are admitted to the hospital twice a year and spend an average of 11 days in the hospital per year (USRDS, 2014). Hospitalizations account for approximately 37 percent of total Medicare expenditures for ESRD patients. Measures of the frequency of hospitalization have the potential to help efforts to control escalating medical costs, and to play an important role in identifying potential problems and helping facilities provide cost-effective health care. 1c.4. Citations 1) U S Renal Data System, USRDS 2014 Annual Data Report: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2014. 2) Wheeler J, Hirth R, Meyer K, Messana JM. Exploring preventable hospitalizations of dialysis patients. J Am Soc Nephrol 22, 2011. [3] Erickson KF, Winkelmayer WC, Chertow GM, Bhattacharya J. Physician visits and 30-day hospital readmissions in patients receiving hemodialysis. J Am Soc Nephrol 25, 2014 (published online before print). [4] Arora P, Kausz AT, Obrador GT, Ruthazer R, Khan S, Jenuleson CS, Meyer KB, Pereira BJ. Hospital utilization among chronic dialysis patients. J Am Soc Nephrol 11: 740 –746, 2000. [5] Piraino B. Staphylococcus aureus infections in dialysis patients: focus on prevention. ASAIO J 46(6): S13-S17, 2000. [6] Dalrymple LS, Johansen KL, Romano PS, Chertow GM, Mu Y, Ishida JH, Grimes B, Kaysen GA, Nguyen DV. Comparison of hospitalization rates among for-profit and nonprofit dialysis facilities. Clin J Am Soc Nephrol 9, 2014 (published online before print).

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Standardized ratio for death among ESRD dialysis patients. (The endorsed specifications of the measure are: Risk-adjusted standardized hospitalization ratio for admissions for dialysis facility patients.)
  
  
• Numerator: Number of deaths among eligible patients at the facility during the time period.
  
  
• Denominator: Number of deaths that would be expected among eligible dialysis patients at the facility during the time period, given the mortality rate is at the national average and the patient mix at the facility.
  
  
• Exclusions: UM-KECC’s treatment history file provides a complete history of the status, location, and dialysis treatment modality of an ESRD patient from the date of the first ESRD service until the patient dies or the data collection cutoff date is reached. For each patient, a new record is created each time he/she changes facility or treatment modality. Each record represents a time period associated with a specific modality and dialysis facility. SIMS/CROWNWeb is the primary basis for placing patients at dialysis facilities and dialysis claims are used as an additional source. Information regarding first ESRD service date, death and transplant is obtained from additional sources including the CMS Medical Evidence Form (Form CMS-2728), transplant data from the Organ Procurement and Transplant Network (OPTN), the Death Notification Form (Form CMS-2746) and the Social Security Death Master File. The denominator for SMR for a facility is the total number of expected deaths during all patient-records at the facility. The number of days at risk in each of these patient-records is used to calculate the expected number of deaths for that patient-record. The denominator is based on expected mortality calculated from a Cox model (Cox, 1972; SAS Institute Inc., 2004; Kalbfleisch and Prentice, 2002; Collett, 1994). The model used is fit in two stages. The stage 1 model is a Cox model stratified by facility and adjusted for patient age, race, ethnicity, sex, diabetes, duration of ESRD, nursing home status, patient comorbidities at incidence, calendar year and body mass index (BMI) at incidence. This model allows the baseline survival probabilities to vary between strata (facilities), and assumes that the regression coefficients are the same across all strata. Stratification by facility at this stage avoids biases in estimating regression coefficients that can occur if the covariate distributions vary substantially across centers. The results of this analysis are estimates of the regression coefficients in the Cox model and these provide an estimate of the relative risk for each patient. This is based on a linear predictor that arises from the Cox model, and is then used as an offset in the stage 2 model, which is unstratified and includes an adjustment for the race-specific age-adjusted state population death rates. Assignment of Patients to Facilities We detail patient inclusion criteria, facility assignment and how to count days at risk, all of which are required for the risk adjustment model. As patients can receive dialysis treatment at more than one facility in a given year, we assign each patient day to a facility (or no facility, in some cases) based on a set of conventions below. Since a patient’s follow-up in the database can be incomplete during the first 90 days of ESRD therapy, we only include a patient’s follow-up into the tabulations after that patient has received chronic renal replacement therapy for at least 90 days. Thus, hospitalizations, mortality and survival during the first 90 days of ESRD do not enter into the calculations. This minimum 90-day period also assures that most patients are eligible for Medicare, either as their primary or secondary insurer. It also excludes from analysis patients who die or recover during the first 90 days of ESRD. In order to exclude patients who only received temporary dialysis therapy, we assigned patients to a facility only after they had been on dialysis there for the past 60 days. This 60 day period is used both for patients who started ESRD for the first time and for those who returned to dialysis after a transplant. That is, deaths and survival during the first 60 days of dialysis at a facility do not affect the SMR of that facility. Identifying Facility Treatment Histories for Each Patient For each patient, we identify the dialysis provider at each point in time. Starting with day 91 after onset of ESRD, we attribute patients to facilities according to the following rules. A patient is attributed to a facility once the patient has been treated there for the past 60 days. When a patient transfers from one facility to another, the patient continues to be attributed to the original facility for 60 days and then is attributed to the destination facility from day 61. In particular, a patient is attributed to their current facility on day 91 of ESRD if that facility had treated him or her for the past 60 days. If on day 91, the facility had not treated a patient for the past 60 days, we wait until the patient reaches day 60 of continuous treatment at that facility before attributing the patient to that facility. When a patient is not treated in a single facility for a span of 60 days (for instance, if there were two switches within 60 days of each other), we do not attribute that patient to any facility. Patients were removed from a facility’s analysis upon receiving a transplant. Patients who withdrew from dialysis or recovered renal function remain assigned to their treatment facility for 60 days after withdrawal or recovery. If a period of one year passes with neither paid dialysis claims nor SIMS information to indicate that a patient was receiving dialysis treatment, we consider the patient lost to follow-up and do not include that patient in the analysis. If dialysis claims or other evidence of dialysis reappears, the patient is entered into analysis after 60 days of continuous therapy at a single facility. Days at Risk for Each Patient-Record After patient treatment histories are defined as described above, periods of follow-up time (or patient-records) are created for each patient. A patient-record begins each time the patient is determined to be at a different facility or at the start of each calendar year. The number of days at risk starts over at zero for each patient record so that the number of days at risk for any patient-record is always a number between 0 and 365 (or 366 for leap years). Therefore, a patient who is in one facility for all four years gives rise to four patient-records and is analyzed the same way as would be four separate patients in that facility for one year each. When patients are treated at the same facility for two or more separate time periods during a year, the days at risk at the facility is the sum of all time spent at the facility for the year so that a given patient can generate only one patient-record per year at a given facility. For example, consider a who patient spends two periods of 100 days assigned to a facility, but is assigned to a different facility for the 165 days between these two 100-day periods. This patient will give rise to one patient-record of 200 days at risk at the first facility, and a separate patient-record of 165 days at risk at the second facility. Then we use the number of days at risk in each of these patient-records to calculate the expected number of deaths for that patient-record, and sum the total number of expected deaths during all patient-records at the facility as the expected number of death for that facility. Detailed methodology is described in Statistical Risk Model and Variables S.14.
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: CROWNWeb
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: CMS has updated NQF#0369, and has resubmitted the measure for endorsement maintenance.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:MUC 575 would bolster the ESRD QIP measure set by addressing the high-priority need of Patient Safety with a high-value outcome measure of patient mortality. The measure is an updated version of a previously endorsed measure (NQF #0369), and has been submitted for endorsement maintenance with a decision pending in 2016. Adding a mortality measure would align the ESRD QIP program with IQR without adding a measurement burden, as the measure is calculated using CROWNWeb data and claims data, and has been reported on Dialysis Facility Compare since 2001.
  • Impact on quality of care for patients:MUC 575 measures patient mortality, ultimately the highest-value quality measure. A performance gap is clearly established through testing, where 15% of facilities were shown to perform 30% worse than the national average. As the ESRD QIP program measures performance across nearly 6,000 facilities treating nearly a half-million patients, this measure would drive better care for a large group of particularly vulnerable patients.
  
  
  
• Does the measure address a program goal or objective? Yes. ?CMS has identified patient safety as a high-priority domain for future measure consideration, specifically citing mortality as a measurement priority.
  
  
• Is this a high-value measure? Yes. MUC 575 is an outcome measure of mortality rates in ESRD patients. CMS has found that the Standardized Mortality Ratio (SMR) varies between facilities from 0.00 to 3.59, with a mean of 1.02 and standard deviation of 0.3. These statistics indicate some 15% of facilities have mortality rates that are 30% higher than the national average.
  
  
• Does this measure fill a gap in the program measure set? Yes. The measure addresses a high-priority domain identified by CMS; no other measures in the ESRD QIP set measure mortality.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested with dialysis facilities.Although NQF #0369 has low one-year reliability and moderate four-year reliability, it was endorsed by NQF. The updated version of NQF #0369 has similar reliability scores. NQF #0369 is correlated with other measures of quality in the ESRD setting, such as admissions, readmissions, AV Fistula, and high transfusion rates, supporting face validity.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. Other programs under consideration by the MAP Hospital Workgroup employ mortality measures, including the Hospital Value-Based Purchasing and Inpatient Quality Reporting programs. The measure is drawn from a mix of claims and CROWNWeb data, and is unlikely to be burdensome to calculate. NQF endorsement (#0369) has been publicly reported on Dialysis Facility Compare since 2001. CMS has updated NQF#0369, and has resubmitted the measure for endorsement maintenance. The measure has been updated to enhance the risk adjustment model by incorporating comorbidity data and consolidating diabetes indicators. The risk adjustment has been harmonized with MUC 1167 and MUC 693.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. CMS has updated NQF#0369, and has resubmitted the measure for endorsement maintenance.
  
  

Rationale for measure provided by HHS
There is evidence indicating that mortality among black ESRD patients is lower than mortality for white ESRD patients, mortality for Hispanic ESRD patients is lower than mortality for non-Hispanic ESRD patients, and mortality for female ESRD patients is lower than mortality for male ESRD patients (see references below). Without a race adjustment, identical SMRs for one facility with predominantly white patients and one facility with predominantly black patients, for example, would give the false impression that quality of care at the two facilities was equivalent, when in fact adjusted mortality at the facility with more black patients would be lower if performance was identical. The SMR is adjusted for all three of these patient characteristics to avoid masking disparities in care across groups. To examine sociodemographic disparities we included quintiles of socioeconomic status (defined for each patient as the median zipcode code household income). This had little effect on the resulting expected deaths counts from the model. See the section on risk adjustment for further details. References: J Kalbfleisch, R Wolfe, S Bell, R Sun, J Messana, T Shearon, V Ashby, R Padilla, M Zhang, M Turenne, J Pearson, C Dahlerus, Y Li, 2015, “Risk Adjustment and the Assessment of Disparities in Dialysis Mortality Outcomes” accepted for publication by JASN; Powe, NR. Reverse race and ethnic disparities in survival increase with severity of chronic kidney disease: What does this mean? Clin J Am Soc Nephrol 1: 905–906, 2006; Cowie CC, Port FK, Rust KF, Harris MI: Differences in survival between black and white patients with diabetic end-stage renal disease. Diabetes Care 17: 681–687, 1994).

Measure Specifications

• NQF Number (if applicable): 2496
  
  
• Description: The Standardized Readmission Ratio is the ratio of a dialysis facility’s (DF) total Medicare-paid index discharges for its dialysis patients from acute care hospitals (ACHs) that result in an unplanned Medicare-paid ACH readmission within 30 days to the total readmissions expected for the DF, given the discharging ACH, the DF, patient/index hospitalization characteristics, and the US median for DFs. (The endorsed specifications of the measure are: The Standardized Readmission Ratio (SRR) is defined to be the ratio of the number of index discharges from acute care hospitals that resulted in an unplanned readmission to an acute care hospital within 30 days of discharge for Medicare-covered dialysis patients treated at a particular dialysis facility to the number of readmissions that would be expected given the discharging hospitals and the characteristics of the patients as well as the national norm for dialysis facilities. Note that in this document, “hospital” always refers to acute care hospital.)
  
  
• Numerator: Each facility’s observed number of hospital discharges that are followed by an unplanned hospital readmission within 4–30 days of discharge (The endorsed specifications of the measure are: Each facility’s observed number of hospital discharges that are followed by an unplanned hospital readmission within 30 days of discharge)
  
  
• Denominator: The expected number of unplanned readmissions in each facility, which is derived from a model that accounts for patient characteristics and discharging acute care hospitals.
  
  
• Exclusions: Hospital discharges that: Are not live discharges; Result in a patient dying within 30 days with no readmission; Are against medical advice; Include a primary diagnosis for cancer, mental health or rehabilitation; Occur after a patient’s 12th admission in the calendar year; Are from a PPS-exempt cancer hospital; Result in a transfer to another hospital on the same day; Are followed by a readmission within 3 days (inclusive).(The endorsed specifications of the measure are: Hospital discharges that:• Are not live discharges• Result in a patient dying within 30 days with no readmission• Are against medical advice• Include a primary diagnosis for cancer, mental health or rehabilitation• Occur after a patient’s 12th admission in the calendar year• Are from a PPS-exempt cancer hospital• Result in a transfer to another hospital on the same day)
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: The measure was endorsed in December 2014.
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:MUC 1167 is a measure that was previously in the ESRD QIP program, and has been re-submitted to reflect changes to the measure calculation. The updated measure is tested at the ESRD facility level, and testing shows the measure is both valid and reliable. A significant performance gap was established in both measure testing and in national statistics of ESRD patient outcomes.
  • Impact on quality of care for patients:Readmission is a costly adverse event that negatively affects patient quality of life. Over a third of discharges for ESRD patients lead to a readmission, presenting a significant opportunity for improvement. Performance scores are normally distributed with a standard deviation approximately one-third the mean, suggesting many facilities could improve their performance significantly to attain the high standard set by top performing facilities.
  
  
  
• Does the measure address a program goal or objective? Yes. CMS has identified Care Coordination as a high-priority domain for the ESRD program.
  
  
• Is this a high-value measure? Yes. MUC 1167 directly measures unplanned readmissions, an ‘important indicator of both morbidity and quality of life’. (http://www.usrds.org/2014/view/v2_04.aspx). Unplanned readmissions are not uncommon: the overall readmissions figure for ESRD patients following discharge was 35.2% in 2012 (http://www.usrds.org/2014/view/v2_04.aspx). Performance among facilities is normally distributed, with a standard deviation of 0.31 on a mean performance of 1.0. In effect, over 15% of facilities readmit over 30% more patients that expected given their case mix.
  
  
• Does this measure fill a gap in the program measure set? Yes. N/A. This measure is currently in use in the ESRD QI program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested with dialysis facilities. Testing supports validity, showing the measure is moderately correlated with measures of hospitalization and mortality, and negatively correlated with fistula use, among other indicators. A Technical Expert Panel approved the measure as clinically valid. Testing shows a moderate degree of reliability (inter-unit reliability of 0.46-0.61 depending on facility size).
  
  
• Is the measure currently in use? Yes. The measure is finalized for PY2017 of the ESRD QIP, and has been reported on Dialysis Facility Compare since April 2015.
  
  
• Does a review of its performance history raise any concerns? No. No unintended consequences were raised as part of the NQF endorsement review. Performance gap is significant and measure shows no signs of being near ‘topped out’. No data source issues are reported.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is harmonized with two other measures under consideration for the ESRD QIP: Mortality (575) and Hospitalization (693). Very similar readmissions measures are used in the IQR program.While the Hospitalization (693) measure under consideration assesses similar adverse events, the hospitalization measure uses a different denominator to capture a different aspect of dialysis facility hospitalization use. Thus, it is possible to have a facility perform quite differently on the two measures: for example, a facility might be delivering high-quality care that minimizes hospitalizations, but see high readmissions, indicating a problem with transitions of care planning.MUC 1167 uses CROWNWeb data, and thus is unlikely to impose a significant measurement or calculation burden.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. The measure was endorsed in December 2014.
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Unplanned readmission rates are an important indicator of patient morbidity and quality of life. On average, dialysis patients are admitted to the hospital nearly twice a year and hospitalizations account for approximately 38 percent of total Medicare expenditures for dialysis patients (U.S. Renal Data System, 2012). In 2010, more than 30% of dialysis patient discharges from an all-cause hospitalization were followed by an unplanned readmission within 30 days (U.S. Renal Data System, 2012). Measures of the frequency of unplanned readmissions, such as SRR, help efforts to control escalating medical costs, play an important role in providing cost-effective health care, and support coordination of care across inpatient and outpatient settings: discharge planning, transition, and follow-up care. Studies have shown that pre- and post-discharge interventions may reduce admission and unplanned readmission rates. A variety of studies on non-ESRD populations that evaluated post-discharge interventions (Dunn 1994; Bostrom 1996; Dudas 2001; Azevedo 2002; Coleman 2004; Coleman 2006; Balaban 2008; Braun 2009) or a combination of pre- and post-discharge interventions (Naylor 1994; McDonald 2001; Creason 2001; Ahmed 2004; Anderson 2005; Jack 2009; Koehler 2009; Parry 2009) have indicated a reduction in the risk of unplanned readmissions to various degrees. In addition, a recent study in the ESRD population found that certain postdischarge assessments and changes in treatment at the dialysis facility may be associated with a reduced risk of readmission (Chan 2009). Altogether, these studies support the potential for modifying unplanned readmission rates with interventions performed prior to and immediately following patient discharge. Ahmed A, Thornton P, Perry GJ, Allman RM, DeLong JF. Impact of atrial fibrillation on mortality and readmission in older adults hospitalized with heart failure. Eur J Heart Fail. 2004;6(4):421–426. Anderson MA, Clarke MM, Helms LB, Foreman MD. Hospital readmission from home health care before and after prospective payment. J Nurs Scholarsh. 2005;37(1):73–79. Azevedo A, Pimenta J, Dias P, Bettencourt P, Ferreira A, Cerqueira-Gomes M. Effect of a heart failure clinic on survival and hospital readmission in patients discharged from acute hospital care. Eur J Heart Fail. 2002 Jun;4(3):353–359. Balaban RB, Weissman JS, Samuel PA, Woolhandler S. Redefining and redesigning hospital discharge to enhance patient care: a randomized controlled study. J Gen Intern Med. 2008;23(8):1228–1233. Bostrom J, Caldwell J, McGuire K, Everson D. Telephone follow-up after discharge from the hospital: Does it make a difference? Appl Nurs Res. 1996;9:47–52. Braun E, Baidusi A, Alroy G, Azzam ZS. Telephone follow-up improves patients satisfaction following hospital discharge. Eur J Internal Med. 2009;20:221–225. Chan K, Lazarus M, Wingard R, et al. “Association between repeat hospitalization and early intervention in dialysis patients following hospital discharge.” Kidney International (2009) 76:331-41. Coleman E, Parry C, Chalmers S, et al. The care transitions intervention. Arch Internal Med. 2006;166:1822–1828. Creason H. Congestive heart failure telemanagement clinic. Lippencotts Case Management: Managing the Process of Patient Care. 2001 Jul-Aug;6(4):146-56. Dudas V, Bookwalter T, Kerr KM et al. The impact of follow-up telephone calls to patients after hospitalization. American Journal of Medicine. 2001; 111(9B):26S-30S Dunn JM, Elliot TB, Lavy JA et al. Outpatient clinic review after arterial reconstruction: is it necessary? Annals of the Royal College of Surgeons of England. 1994 Sep;76(5):304-6. Jack B, Chetty V, Anthony D, et al. “A reengineered hospital discharge program to decrease rehospitalizaton.” Annals of Internal Medicine (2009) 150:178-88. Koehler BE, Richter KM, Youngblood L et al. Reduction of 30-day postdischarge hospital readmission or emergency department (ED) visit rates in high-risk elderly medical patients through delivery of a targeted care bundle. Journal of Hospital Medicine. 2009 Apr;4(4):211-8. McDonald, MD. The hospitalist movement: wise or wishful thinking? Nurse management. 2001 Mar;32(3):30-1. Naylor M, Brooten D, Jones R et al. Comprehensive discharge planning for the hospitalized elderly. A randomized clinical trial. Annals of Internal Medicine. 1994 Jun 15;120(12):999-1006. Parry C, Min SH, Chugh A et al. Further application of the care transitions intervention: results of a randomized controlled trial conducted in a fee-for-service setting. Home Health Care Services Quarterly. 2009;28(2-3):84-99.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: All-Cause Admissions and Readmissions Measures
  
  
• Review for Importance: The measure meets the Importance criteria(1a. Evidence, 1b. Performance Gap, 1c. High Impact)1a. Evidence: Y-17; N-6; 1b. Performance Gap: H-15; M-8; L-0; I-0; 1c. Impact: H-20; M-3; L-0; I-0Rationale:• There was general agreement that this is a high impact area of measurement and there is opportunity for improvement, with the overall readmissions rate at approximately 30 percent and the readmissions rate for hemodialysis patients at approximately 36 percent.• The Committee agreed that certain post-discharge assessments and changes in treatment at the dialysis facility may be associated with a reduced risk of readmissions.• One committee member was concerned that the cause of the reduced risk of admissions had more to do with interventions by nephrologists, rather than the dialysis unit. Further, the member noted that NQF guidance regarding evidence for outcome measures are not strong enough, suggesting that the quality, quantity, and consistency of the evidence should be evaluated even for outcome measures.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-5; M-17; L-1; I-0 2b. Validity: H-1; M-16; L-7; I-0Rationale:• The Standing Committee discussed a number of threats to validity of the measure, mainly focusing on whether the dialysis unit was the accountable entity for 30-day readmissions back to acute care facilities.o One member argued that there are limited interventions a dialysis unit can implement that would influence this particular measure. This member noted that there are limited structures that allow the medical director or the governing body of the dialysis unit to compel nephrologists to see patients immediately after discharge from an acute care facility.o Other Committee members noted that while the locus of control may not be solely the dialysis facility, this measure and improvement efforts tied to it may be the type of impetus needed to improve care for this population. These members also noted that with patients spending nine to 12 hours in these units during the week, more could be done to improve care for these patients.
  
  
• Review for Feasibility: H-11; M-9; L-4; I-0(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)Rationale:• The required data elements are routinely generated and used during care delivery and all data elements are in defined fields in electronic claims
  
  
• Review for Usability: H-3; M-11; L-10; I-0(Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement)Rationale: Some members were concerned that the threats to validity would cause unintended consequences with the use of this measure in public reporting or accountability applications; however, there was limited evidence of unintended consequences identified.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments: NQF received 10 post-evaluation comments regarding this measure.There was one supportive comment, arguing that this measureaddresses an important high priority for measurement with sufficientroom for improvement in the care processes of dialysis units. Theremaining comments raised concern about the measure specifications,including the numerator specifications, denominator specifications,attribution, temporal logic, risk adjustment, testing, and intendeduse.
  
  Numerator Specifications
  
  • Commenters were concerned that the numerator definition relieson an accurate determination of planned admissions using codesfrom a non-ESRD population. Commenters encouraged validation ofthese codes in the ESRD population through examination ofpatient-level data from the CMS dry run.
  • Commenters raised strong concern that the numerator of acuteadmissions does not consider ESRD-specific patient management –noting that this list of admissions should be tailored toinclude nephrology–related treatment. Commenters requestedclarification on whether PD catheter placement or omentectomy,vascular access creation, or transfusion for a transfusiondependent patient fall is included in the measure.
  Denominator Specifications
  
  • Specifically, a commenter disagreed that the number ofdischarges should not be the determinant of the denominator, butrather the number of readmissions should be based on the totalnumber of patients treated in a facility. Further, the commenterargued that the current measure is vulnerable to being skewed bythe effect of one or two complex patients requiring frequenthospitalization.
  
  Attribution
  
  • Many commenters challenged the notion that dialysis facilitieshave the ability to affect readmissions. Commenters explainedthat dialysis facilities often do not receive any directcommunication from the discharging hospital or facility fortheir patients, and are not supported to have coordinatedpresence in multiple hospitals. One commenter noted that apatient might be readmitted before ever being seen in thedialysis unit. This commenter noted that these readmissions arenot actionable by the dialysis facility and should not beincluded in the measure. Further, commenters noted a lack ofevidence showing that changes in a dialysis unit are the factorsdriving performance improvement.
  • Additionally, a commenter noted that the majority of dialysisfacilities do not have the resources for additional personnel,such as case managers, to improve care coordination betweendialysis facilities and other health care providers. Thiscommenter argued that dialysis facilities have a role inreducing all-cause readmissions; however, these facilities maynot be the locus of control to manage the coordination required.• Further, the commenter discussed that a dialysis unit has nocontrol over a hospital's decision to re-admit a patient. Thehospital physician decides whether or not to admit a patient,and many of these admissions have nothing to do with thenephrological issues being addressed by the dialysis facilityand should also be excluded from the measure.
  • Commenters also requested clarification on the frequency ofadmissions that occur prior to the first post-acute visit to adialysis facility.
  Exclusions
  
  • Commenters requested clarification on how specific patientcohorts are handled in the measure. Additionally, a commenterrequested clarification on how readmissions as a result ofunsuccessful kidney transplants are handled in the 6 monthsfollowing the transplant. Another commenter requestedclarification on the rationale for excluding indexhospitalizations after the patient’s 12th admission in thecalendar year. Further, this commenter requested clarificationon why patients without complete claims histories and those whoare readmitted within the 1-3 days after discharge are notexcluded from the measure.
  Risk Adjustment
  • Commenters noted concern with the validity of the two-stagerandom effects risk-adjustment model. In particular, theyrequested clarification on how the measure is impacted bycommunities where there is only one major hospital and/or onemajor dialysis facility versus communities where there is manyof one or both. The Commenters also noted that the riskadjustment model should reduce the number of variables to thosethat are clinically relevant.
  • Further, another commenter noted that other comorbiditiesshould be included in the risk adjustment model, includingsickle cell trait, angiodysplasia, myelodysplasia, diverticularbleeding, and asthma. Additionally, the commenter suggestedadjusting for nursing home status in the risk adjustment model.Commenters also requested clarification on whether “poisoning bynonmedical substances” includes ongoing/chronic alcohol or drugabuse and not just acute events.
  Reliability and validity testing
  
  • Commenters noted that the testing results demonstratingcorrelations between hospitalization and re-hospitalization donot enhance confidence in the measure. The correlations withaccess and urea reduction ratio (URR) are statisticallysignificant but of very low magnitude, and the correlation withthe standardized mortality ratio (SMR) also has a low magnitude.Another commenter noted that the area under the curve for thefor the receiver operating characteristic (ROC) curve(C-statistic) for the multivariable model of <0.65 is quitepoor and suggests that the model is inadequate.
  • Commenters requested clarification on the minimum sample sizerequired to provide a statistically stable value for themeasure. They expressed concern that many individual dialysisfacilities may be too small with wide confidence intervals,limiting the statistical validity of the results.
  Intended use in the specific program (QIP) and its appropriateness
  • Commenters expressed concern regarding the appropriateness ofthe intended use of this measure for the CMS ESRD QualityIncentive Program (QIP). Commenters argued that the measureshould focus only on admissions that are actionable for dialysisfacilities, making stratification by primary diagnosis forreadmission important.
  
  
  
• Endorsement Committee Recommendation: Y-8; N-12.  
  
  Consensus Standards Approval Committee (CSAC) Vote: November 21,2014: Y-9; N-5; A-3
  Decision: Approved for endorsement  
  
  Board of Directors Vote: Pending  
  
  Appeals
  
  • On January 28, 2015, the 30-day appeals period for theall-cause admission and readmission measures closed. NQFreceived an appeal submitted by the Renal Physicians Association(RPA) and co-signed by the American Nephrology NursesAssociation, American Society of Nephrology, American Society ofPediatric Nephrology, Dialysis Patient Citizens, and Kidney CarePartners.
  • NQF staff reviewed the appeal and determined that the issuesraised were based on NQF process issues, rather thanmeasure-specific issues. The appellant’s main concern was thatthe CSAC did not consider the Committee evaluation and Membervoting results, which is the basis for their challenge of theendorsement decision. The appellants note that the CSAC voted toapprove the measure despite its having reached only 14 percentapproval among NQF member councils and 40 percent approval bythe Standing Committee.
  • CSAC reviewed the appeal on February 10, 2015, and voted touphold endorsement (92% approval).
  • CSAC members acknowledged the appellant’s concerns aboutmeasure 2496 but remained supportive of its endorsement of themeasure. The CSAC noted that the process followed in thereview and endorsement of this measure is consistent with theapproved process for measures on which consensus is notreached. Endorsement decisions require the CSAC to balanceinput received from the project Standing Committee, feedbackby the membership from commenting, voting, and the NQFall-member call. The CSAC considered these transparent inputsand they were adequately considered in the final endorsementrecommendation on this measure.
  • The BOD Executive Committee reviewed the appeal on March 5,2015, and requested that NQF bring together the appellant andthe measure developer to explore opportunities for a shared pathforward. NQF will engage in further consensus building regardingthis measure and the measure will come back to the ExecutiveCommittee when those efforts are complete.
  
  
  

Measure Specifications

• NQF Number (if applicable): 753
  
  
• Description: Organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients at least 18 years of age undergoing inpatient colon procedures and/or abdominal hysterectomies as reported through the ACS-NSQIP or CDC NHSN. The measure yields separate SIRs for each procedure. (The endorsed specifications of the measure are: Prototype measure for the facility adjusted Standardized Infection Ratio (SIR) of deep incisional and organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients aged >= 18 years as reported through the ACS National Surgical Quality Improvement Program (ACS-NSQIP) or CDC National Health and Safety Network (NHSN). Prototype also includes a systematic, retrospective sampling of operative procedures in healthcare facilities. This prototype measure is intended for time-limited use and is proposed as a first step toward a more comprehensive SSI measure or set of SSI measures that include additional surgical procedure categories and expanded SSI risk-adjustment by procedure type. This single prototype measure is applied to two operative procedures, colon surgeries and abdominal hysterectomies, and the measure yields separate SIRs for each procedure.)
  
  
• Numerator: Deep incisional primary (DIP) and organ/space SSIs during the 30-day postoperative period among patients at least 18 years of age undergoing inpatient colon surgeries or abdominal hysterectomies. SSIs will be identified before discharge from the hospital, upon readmission to the same hospital, or during outpatient care or admission to another hospital (post-discharge surveillance). Case accrual will be guided by sampling algorithms as described below.
  
  
• Denominator: Using multivariable logistic regression models for colon surgeries and abdominal hysterectomies, the expected number of SSIs is obtained. These expected numbers are summed by facility and surgical procedure and used as the denominator of this measure
  
  
• Exclusions: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded.(The endorsed specifications of the measure are: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded. In the NHSN, patients without primary closure of the surgical incision are not considered eligible cases and are excluded- the NSQIP will match this practice for this measure, although this is not standard practice within the NSQIP.)
  
  
• 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: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Conditional support, pending NQF annual update
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is an update to the name of the measure from “reliability adjusted SIR” to “Adjusted Ranking Metric (ARM)”, which provides a better estimate of the hospital’s true SIR relative to other facilities.
  • Impact on quality of care for patients:The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
  
• Does the measure address a program goal or objective? Yes. The priority is to make care safer by reducing harm caused in the delivery of care, a high priority domain identified by CMS.?
  
  
• Is this a high-value measure? Yes. Yes, because the continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in this program – the name is being changed from reliability adjusted SIR to the Adjusted Ranking Metric (ARM), which provides a better estimate of the hospital’s true SIR relative to other facilities. Currently, there are three measures in the program measure set implemented and finalized that address the NQS priority of making care safe, two additional ones are proposed. This is the only SSI measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. It is tested at the hospital/acute care facility level, at the facility level of analysis.
  
  
• Is the measure currently in use? Yes. This measure is currently used in this program, but the name of the measure is changing from reliability adjusted SIR to the Adjusted Ranking Metric (ARM), which provides a better estimate of the hospital’s true SIR relative to other facilities.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It is currently in the program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Affects large numbers, Frequently performed procedures, A leading cause of morbidity/mortality, High resource use, Severity of illness, Patient/societal consequences of poor quality. SSIs estimated to account for 20% of all HAIs[1] 290,485 estimated SSIs/yr[2] Estimated 8,205 deaths associated with SSIs each year[1] Estimated 11% of all deaths occurring in intensive care units are associated with SSIs[1] $34,670 medical cost/SSI[2] Total >$10 billion attributable to SSI in U.S. each year[2] Estimated additional 7-10 days of hospitalization for each SSI per patient[1] [1] Klevens RM, Edwards JR, et al. Estimating healthcare-associated infection and deaths in U.S. hospitals, 2002. Public Health Reports 2007; 122:160-166. [2] Scott, RD. The Direct Medical Costs of Healthcare-Associated Infections in U.S. Hospitals and the Benefits of Prevention. http://www.cdc.gov/ncidod/dhqp/pdf/Scott_CostPaper.pdf accessed April 12, 2010.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Patient Safety Measures
  
  
• Review for Importance: The measure addresses a high impact area. Each year, approximately 11 percent of all deaths in ICUs are associated with SSIs, resulting in up to 20,000 deaths and $2 billion in additional costs.2 Moreover, evidence-based interventions have shown significant reductions in SSI rates and improved health outcomes.
  
  
• Review for Scientific Acceptability: See CDP Recommendation]
  
  
• Review for Feasibility: See CDP Recommendation]
  
  
• Review for Usability: See CDP Recommendation]
  
  
• Review for Related and Competing Measures: See CDP Recommendation]
  
  
• Endorsement Committee Recommendation: The Steering Committee discussed the newly-harmonized measure in a supplemental conference call, reviewing the relevant changes, while also receiving clarification from the developers on several issues. Committee members inquired as to why these two particular measures had been chosen, and asked for clarification on the plan for public reporting. The developer explained that the CMS IPPS requirements released on August 1, 2011, call for abdominal hysterectomies and colon surgeries to be reported by the CDC to CMS. The NHSN will serve as the single reporting system for CMS-required reporting. However, facilities may choose which calculations of performance on the measure can be accomplished using either the NHSN or NSQIP data system. The measure developer acknowledged that for hospitals participating in both systems, there could be duplication.The Steering Committee questioned why both organ space and deep incisional infections were included in the measure. The developer described the approach as a long standing precedent and stated that superficial infections are considered trivial events and therefore not included. However, organ space infections that drain through the incisions are classified as deep incisional infections. The combination of organ space and deep incisional infections are considered a clinically coherent grouping. The Committee expressed their appreciation for the developers’ efforts at harmonization, and agreed that the measure continues to meet the four major evaluation criteria. The Steering Committee recommended this measure for endorsement in a unanimous vote.This outcome measure replaces NQF-endorsed measure #0299 (Surgical Site Infection Rate) and addresses the National Priority area of safety.
  
  

Measure Specifications

• NQF Number (if applicable): 531
  
  
• Description: Patient Safety and Adverse Events Composite (Patient Safety Indicator, or PSI90) is a composite measure of 10 individual PSIs, each measuring a different aspect of harm associated with patient safety. Each PSI is reliability-adjusted (smoothed) and indirectly standardized (risk adjusted). The composite is the weighted average of the reliability-adjusted, indirectly standardized, observed-to-expected ratios for component indicators. The final weight for each component is the product of harm weights and volume weights (numerator weights). Harm weights are calculated by multiplying empirical estimates of excess harms associated with the patient safety event by utility weights linked to each of the harms. Excess harms are estimated using statistical models comparing patients with a safety-related event to those without that safety-related event in a CMS Medicare fee-for-service sample that allowed up to one year of follow-up from the discharge date of the hospital stay associated with the index event. Volume weights, the second part of the final weight, are calculated on the basis of the number of safety-related events for the component indicators in the all-payer reference population. The observed to expected ratios (indirect standardization) of the reliability adjusted (smoothed) rates are multiplied by a component weight and the weighted scores are summed to determine the final PSI 90 score. A score of 1 means that the hospital performs as expected, scores greater than one indicate worse performance than expected.
  
  
• Numerator: Below we list the numerator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for pressure ulcer and any secondary ICD-9-CM diagnosis codes for pressure ulcer stage III or IV (or unstageable). PSI06-Iatrogenic Pneumothorax Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for iatrogenic pneumothorax. PSI08-Postoperative Hip Fracture Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for hip fracture. PSI09-Perioperative Hemorrhage and Hematoma Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for perioperative hemorrhage or hematoma and any-listed ICD-9-CM procedure codes for control of perioperative hemorrhage or evacuation of hematoma. PSI10-Postoperative Acute Kidney Injury Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for acute renal failure and any-listed ICD-9- CM procedure codes for dialysis. PSI11-Postoperative Respiratory Failure Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis code for acute respiratory failure; or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for 96 consecutive hours or more that occurs zero or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for less than 96 consecutive hours (or undetermined) that occurs two or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a reintubation that occurs one or more days after the first major operating room procedure code (based on days from admission to procedure). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with a secondary ICD-9-CM diagnosis code for deep vein thrombosis or a secondary ICD-9-CM diagnosis code for pulmonary embolism (omitting cases from the numerator with isolated calf vein DVT). PSI13-Postoperative Sepsis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for sepsis. PSI14-Postoperative Wound Dehiscence Rate-Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any-listed ICD-9-CM procedure codes for reclosure of postoperative disruption of the abdominal wall. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate -Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for accidental puncture or laceration during a procedure and second abdominopelvic operation 1 day or more after the index procedure.
  
  
• Denominator: Below we list the denominator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI06-Iatrogenic Pneumothorax Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI08-Postoperative Hip Fracture Rate- Surgical discharges, ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI09-Perioperative Hemorrhage and Hematoma Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI10-Postoperative Acute Kidney Injury Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI11-Postoperative Respiratory Failure Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI13-Postoperative Sepsis Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI14-Postoperative Wound Dehiscence Rate- Discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for abdominopelvic surgery. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate- Patients ages 18 years and older with any procedure code for an abdominopelvic procedure.
  
  
• Exclusions: Below we list the exclusions for the composite components. There are no additional exclusions for the composite measure as a whole. PSI03 – Pressure Ulcer Rate-Excludes cases with length of stay less than 5 days, with a principal diagnosis of pressure ulcer or secondary diagnosis of pressure ulcer present on admission, cases with evidence of hemiplegia, paraplegia or quadriplegia, spina bifida, anoxic brain damage, debridement or pedicle graft on the same day as the major operating room surgery or as the only major operating room procedure, and cases that were transferred from a different hospital or skilled nursing facility, and cases with MDC (major diagnostic classification) of 9 (skin, subcutaneous and breast) or 14 (pregnancy, childbirth and puerperium). PSI06 – Iatrogenic Pneumothorax Rate - Excludes cases with a principal diagnosis for iatrogenic pneumothorax or secondary diagnosis of iatrogenic pneumothorax on admission, cases with evidence of chest trauma, pleural effusion, thoracic surgery, lung or pleural biopsy, diaphragmatic repair, cardiac procedure, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI08 – Postoperative Hip Fracture Rate-Excludes cases with principal diagnosis of hip fracture or a secondary diagnosis of hip fracture on admission, cases where the only operating room procedure is hip fracture, where the procedure for hip fracture occurs before or on the same day as the first operating room procedure, and cases with a principal diagnosis of seizure, syncope, stroke and occlusion of arteries, coma, cardiac arrest, poisoning, trauma, delirium and other psychoses, anoxic brain injury, metastatic cancer, lymphoid malignancy, bone malignancy, self-inflicted injury, and cases with MDC (major diagnostic classification) of 8 (musculoskeletal system and connective tissue) or 14 (pregnancy, childbirth and puerperium). PSI09 – Perioperative Hemorrhage and Hematoma Rate - Excludes cases with principal diagnosis of perioperative hemorrhage or postoperative hematoma or secondary diagnosis present of perioperative hemorrhage on admission, cases where the only operating room procedure is control of postoperative hemorrhage, drainage of hematoma or miscellaneous hemorrhage- or hematoma-related procedure, any secondary diagnosis of perioperative hemorrhage or postoperative hematoma and any-listed procedure codes for control of perioperative hemorrhage or evacuation of hematoma or miscellaneous hemorrhage- or hematoma- related procedure occurring before the first operating room procedure, cases with diagnosis of coagulation disorder and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI10 – Postoperative Acute Kidney Injury-Excludes cases with a principal diagnosis or secondary diagnosis on admission of acute renal failure, acute myocardial infarction, cardiac arrhythmia, cardiac arrest, shock, hemorrhage, gastrointestinal hemorrhage, or chronic renal failure, cases with dialysis procedure before on the same day as the first operating procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI11 – Postoperative Respiratory Failure Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of acute respiratory failure, cases where the only operating procedure is tracheostomy or a tracheostomy occurs before the first operating procedure, cases with any listed diagnosis of neuromuscular disorder, craniofacial anomalies or degenerative neurological disorder, cases with any listed procedure of laryngeal or pharyngeal, nose, mouth, or pharynx surgery, procedures involving the face, esophageal resection, procedures for lung cancer, and cases with MDC (major diagnostic classification) of 4 (disease of respiratory system), 5 (diseases of the circulatory system), or 14 (pregnancy, childbirth and puerperium). PSI12 – Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of DVT, pulmonary embolism, cases where a procedure for interruption of vena cava occurs before or on the same day as the first operating room procedure, cases with any procedure for extracorporeal membrane oxygenation, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI13 – Postoperative Sepsis Rate – Excludes cases with principal diagnosis or secondary diagnosis on admission of sepsis, infection, cases with evidence of immunocompromised state or cancer, cases with a length of stay less than 4 days, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI14 – Postoperative Wound Dehiscence Rate – Excludes cases with any listed evidence of immunocompromised state, cases where the procedure for abdominal wall reclosure occurs on or before the day of the first abdominopelvic surgery procedure, cases with a length of stay less than 2 days, and cases with MDC(major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI15 – Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate-Excludes cases with a principal diagnosis or secondary diagnosis at admission of accidental puncture or laceration during a procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium).
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Administrative claims Component measures require: ICD-9 diagnosis and procedure codes, MDC, MSDRG, procedure day, age in year, gender, admission type, discharge disposition. All are drawn from administrative data.
  
  
• Measure Type: Composite
  
  
• Steward: Agency for Healthcare Research & Quality
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This updated version of PSI 90 addresses a number of concerns raised by the NQF Safety Standing Committee. Three additional PSIs have been added to the measure. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable. PSIs were better linked to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication. This is intended to allow the measure to more accurately reflect the impact of the events.
  • Impact on quality of care for patients:The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges. The composite measure was constructed to increase the statistical precision by increasing the sample size and to assist consumers, providers, and payers with their decision-making. This updated version would three additional PSIs: PSI09 Postoperative Hemorrhage or Hematoma, PSI10 Physiologic and Metabolic Derangement, and PSI11 Postoperative Respiratory Failure.
  
  
  
• Does the measure address a program goal or objective? Yes. PSI 90 is currently in the HAC program. MAP is being asked to review an updated version of the measure. During the 2014 CDP review of the measure, the Safety Standing Committee raised concerns about the weighting of the various components of the composite, specificially that some of the more heavily weighted components were less clinically significant (i.e., accidental punctures and lacerations) and/or less preventable. To address these concerns several updates were made to the measure: Additional PSI’s were added (from 8 events to 11 events, expanding the type of complications included in this measure)Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable PSIs were better linked to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication. This is intended to allow the measure to more accurately reflect the impact of the events.
  
  
• Is this a high-value measure? Yes. This is an outcome measure addressing patient safety. The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges.
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in the program measure set. MAP is being asked to consider an update to the measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. The measure is currently used in IQR, VBP, and HACRP. The national composite rate is .81.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is currently used in IQR, VBP, and HACRP. This is a composite measure calculated through claims data. This measure would potentially reduce events that cause serious harm to patients.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Each measure used within the PSI 90 composite is an outcome measure that has been shown to be largely preventable through improved structures and processes of care. Each measure has an evidence review form as part of the NQF endorsement process. The literature to support each measure is updated on a schedule basis.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Patient Safety 2015
  
  
• Review for Importance: The measure meets the Importance criteria (1a. Evidence, 1b. Performance Gap) 1a. Evidence: 16-Y; 8-N I; 1b. Performance Gap: 9-H; 9-M; 6-L; 0-I; 1c. Composite- Quality Construct and Rationale: 6-H; 7-M; 11-L; 0-I Rationale: · The Committee agreed that the outcomes in this measure were associated with one or more healthcare actions. However, there was concern that some of the elements of the composite had variable preventability. · The developers reported that the items within the composite are positively correlated. The correlations range in the low 0.08 up to the 30s (not very high). · The developers referenced several processes of care that are associated with lower rates for each of the components in the composite.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria (2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity) 2a. Reliability: 4-H; 10-M; 9-L; 1-I 2b. Validity: 2-H; 11-M; 7-L; 2-I 1c. Composite Construction: 4-H; 12-M; 7-L; 1-I Rationale: · The Committee agreed that the updated version of the measure provided by AHRQ was improved from the 2014 version reviewed by the Committee, specifically noting that the new weighting focusing on harm rather than just the frequency of events, was more clinically relevant than the previous version of the measure. · During reliability testing, the developers examined the true difference rather than random chance and noise. Their results show a reliability scores in the 70s, which is comparable to other endorsed measures · Aggregating a number of individual measures into a single composite can generate an overall performance score that is more reliable than if the individual measure scores were taken in isolation. · Empirical field validity testing was conducted at the performance measure score level for the overall composite by correlating the composite scores with the rates calculated from the 3M Potentially Preventable Readmissions measure. .The Pearson correlation value, was 0.11 with a p-value of <0.0001.
  
  
• Review for Feasibility: 12-H; 8-M; 3-L; 1-I (3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented) Rationale: · The Committee had no concerns about the feasibility of this measure given that it is gathered with administrative claims data.
  
  
• Review for Usability: 12-H; 6-M; 6-L; 0-I (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement) Rationale: · There were concerns about the use of this measure in value-based purchasing, despite the improvements the developer has made, because may not accurately reflect that an actual preventable complication occurred or may focus on preventing measured events that are less clinically important. · This measure is used to monitor performance in national and regional reporting. It was also developed to enable comparative reporting and quality improvement at the provider or the hospital level.
  
  
• Review for Related and Competing Measures: Concerns were raised by the Committee that some of the elements of this measure, notably the central line related blood stream infections and post-operative hip fracture, may be better captured in other NQF approved measures rather than using administrative claims data. In addition, this measure is related to NQF 532, which is the pediatric version of the same measure 0347.
  
  
• Endorsement Public Comments: Summary pending
  
  
• Endorsement Committee Recommendation: 14-Y; 10-N

  Since 58% of the Committee voted to recommend this measure, it did not achieve consensus. It will move forward to the comment period and the Committee will discuss and revote after the public comment.

  This measure was last endorsed in 2009; it is a composite measure of 11 inpatient Patient Safety Indicators. In 2014 the Committee raised concerns about the weighting of the various components of the composite, specificially that some of the more heavily weighted components were less clinically significant (i.e., accidental punctures and lacerations) and/or less preventable. In addition, there were concerns that the events measured are not always reflective of an actual patient safety event that resulted in preventable patient harm. To address the concerns of the 2014 Committee, AHRQ made several updates to the measure to address the Committee’s concerns.

  1. Additional PSIs were included (from 8 events to 11 events, which expanded the type of complications included this measure),
  2. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable, and
  3. The measure was modified to more accurately reflect the impact of the events by better linking the PSIs to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication.

  The Committee agreed that the changes to the measure were highly responsive to the concerns raised during the 2014 Committee discussion. However, new concerns were raised: some post-operative DVT or other events included in the composite may not be preventable; the definition of ICD-9 based central line related blood stream infections may be less precise than other definitions (i.e., NHSN which reports the information differently); and concerns about this measure being included in value-based purchasing programs particularly when it is likely that not all of these events are preventable and that it may distract from efforts to reduce more impactful safety events. In addition, there were concerns that some of the indicators of the measure may not reflect preventable patient safety events because it comes from ICD-9 data of inpatient complications, which sometimes did not directly reflect that an actual preventable complication occurred in the validation of the components of the composite. During the vote, the Committee agreed that the measure meets the four NQF criteria; however, consensus was not reached on a recommendation for endorsement (58% yes, 42% no). The Committee will re-consider the recommendation for endorsement after reviewing the public comments.
  
  

Measure Specifications

• NQF Number (if applicable): 2020
  
  
• Description: Percentage of adult (age 18 and older) U.S. population that currently smoke, defined as adults who reported having smoked at least 100 cigarettes in their lifetime and currently smoke. (The endorsed specifications of the measure are: Percentage of adult (age 18 and older) U.S. population that currently smoke.)
  
  
• Numerator: The numerator is current adult smokers (age 18 and older) in a geographically defined area who live in households. (The endorsed specifications of the measure are: The numerator is current adult smokers (age 18 and older) in the U.S. who live in households.)
  
  
• Denominator: The adult (age 18 and older) population in a geographically defined area who live in households. One adult per household is interviewed.(The endorsed specifications of the measure are: The adult (age 18 and older) population of the U.S. who live in households. One adult per household is interviewed.)
  
  
• Exclusions: Adults 18 years or older are asked to take part in the survey and only one adult is interviewed per household. Adults living in vacation homes not occupied by household members for more than 30 days per year, group homes, institutions, prisons, hospitals and college dorms are excluded.(The endorsed specifications of the measure are: Adults 18 years or older are asked to take part in the survey and only one adult is interviewed per household. Adults living in vacation homes not occupied by household members for more than 30 days per year, group homes, institutions, prisons, hospitals and college dorms are excluded. Military services members and adults who speak a language other than English and Spanish are also excluded.)
  
  
• HHS NQS Priority: Effective Prevention and Treatment, Best Practice of Healthy Living
  
  
• HHS Data Source: BRFSS. Please see: http://www.cdc.gov/brfss/technical_infodata/surveydata/2011.htm
  
  
• Measure Type: Structure
  
  
• Steward: Centers for Disease Control and Prevention, Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:No
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Encourage further development
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This structure measure addresses the high-priority domain “Best Practices of Healthy Living” but it does not fill any of the high-priority gap areas previously identified by CMS. CMS has indicated strong interest in exploring this measure with MAP. The measure is under development for the city and county level of analysis. The applicability of this population measure to the role of hospitals needs further exploration. Furthermore, this measure is focused on smoking and does not align with the tobacco use screening and treatment provided measures currently in the IPFQR program or other tobacco use measures in other programs.
  • Impact on quality of care for patients:This measure is an indicator of population health at the city or county level rather than the quality of care received in the acute inpatient setting. The updated tobacco use and dependence guideline recommends coordinated interventions between the clinician, health care administrator, insurer, and purchaser therefore quality measurement should focus on all entities to ensure tobacco users receive consistent and effective interventions.
  
  
  
• Does the measure address a program goal or objective? Yes. ?This smoking prevalence measure addresses the “Best Practices of Healthy Living” domain.
  
  
• Is this a high-value measure? Yes. The range of current smoking rates range from roughly 10 percent to 30 percent depending on geography. Data on smoking prevalence is also crucial in identifying inequalities between groups and addressing health disparities. A specific example of the importance of tracking smoking status can be found in the American Legacy Foundation’s report, “Saving Lives, Saving Money,” which addresses the financial impact of smoking. In the report, researchers estimated the reduction in state Medicaid expenditures that would result from reducing or eliminating smoking through effective cessation and prevention programs. In order to calculate the lifetime costs of a smoker to a state Medicaid program, data on smoking status was essential.
  
  
• Does this measure fill a gap in the program measure set? No. CMS identified six measurement gap topic/areas as high-priority for future measure consideration and this measure does not address any of the gaps identified.
  
  
• Measure development status: Early Development
  
  
• Is the measure fully tested for the program's setting and level of analysis? No. Not yet tested.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No/Yes. The NQF-endorsed version of the MUC (#2020) is already being collected and reported at the state level by the CDC, therefore, hospitals would not incur the burden and cost of implementation. The MUC and #2020 are not in any other federal programs and do not align with the three NQF-endorsed measures in the Inpatient Psychiatric Facility Quality Reporting Program (IPFQR: tobacco use screening (#1651), tobacco use treatment provided or offered (#1654), and tobacco use treatment provided or offered at discharge (#1656). In addition, this measure does not align with the recommendations in the Treating Tobacco Use and Dependence 2008 Update Clinical Practice Guideline which support the use of counseling and medication treatment for all tobacco products not just cigarettes.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Endorsed; MUC same as endorsed version:No
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Tobacco use and exposure to secondhand smoke caused more than 400,000 in the U.S. in each year between 2000 and 2004, according to the CDC. These deaths represent more than 5 million years of potential life lost (YPLL).1 At the state level, the median annual number of lives lost per state was 5,534, though there was a great deal of variation by state.2 National Cost of Tobacco Use The Centers for Disease Control and Prevention (CDC) estimates that, in the U.S. in each year from 2001 through 2004, an average of $96 billion was spent on health care due to smoking.1 A 2007 study calculates the cost of smoking to the U.S. Medicaid system, concluding that the projected lifetime costs of smoking to Medicaid, for a single cohort—current 24-year-old smokers—is nearly $1 billion. 1. Centers for Disease Control and Prevention (CDC). Smoking attributable mortality, years of potential life lost, and productivity losses--United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2008 Nov 14;57(45):1226-8. 2. Centers for Disease Control and Prevention (CDC). State-specific smoking-attributable mortality and years of potential life lost--United States, 2000-2004. MMWR Morb Mortal Wkly Rep. 2009 Jan 23;58(2):29-33. Erratum in: MMWR Morb Mortal Wkly Rep. 2009 Feb 6;58(4):91. 3. Trogdon J, Pais J. Saving Lives, Saving Money II: Tobacco-Free States Spend Less on Medicaid. A Policy Report of the American Legacy Foundation. 2007. 4. Centers for Disease Control and

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Population Health Endorsement Maintenance: Phase II
  
  
• Review for Importance: The measure meets the Importance criteria.(1a. High Impact: 1b. Performance Gap, 1c. Evidence)1a. Impact: H-9; M-2; L-0; I-0; 1b. Performance Gap: H-5; M-6; L-0; I-0 1c. Evidence: Y-10; N-0; I-1Rationale:• Sufficient evidence about the burden of smoking at state and national levels, and evidence-based interventions to reduce the burden.• Useful community assessment to help determine resource allocation and strategic plans for combatting smoking.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria.(2a. Reliability – precise specifications, testing; 2b. Validity – testing, threats to validity)2a. Reliability: H-8; M-3; L-0; I-0 2b. Validity: H-7; M-4; L-0; I-0Rationale:• Concern about validity because of the exclusion of people serving in the military and those that are institutionalized. Although these are relatively small populations, smoking prevalence is high among these groups.• Some Committee members stated an additional limitation of using NHIS as a data source:o Lower age limit – perhaps consider those younger than 18 years, which data show high prevalence.• Several concerns about the survey questions and apparent and/or potential lack of harmonization with similar smoking survey measures, including BRFSS etc.o “Have you smoked at least 100 cigarettes in your entire life? (Yes, No, Refused, Don’t Know)” does not appear to be aligned with other survey questions, which ask “do you smoke every day, some days, or at all…” The former is listed twice in the measure submission form.• Why are non-combustibles and other tobacco products omitted from the measure?Following the in-person meeting, the steward and developer provided the following responses:• The measure, as currently specified, is based on the National Health Interview Survey (NHIS) measure of current smoking, which tracks the Healthy People 2020 measure for smoking prevalence among adults.• The measure uses the following questions, which are harmonized with BRFSS:o Have you smoked at least 100 cigarettes in your entire life? (Yes, No, Refused, Don’t Know) and,o Do you now smoke every day, some days, or not at all (asked of those who smoked 100 cigarettes in the above question)? (Every day, Some days, Not at all, Refused, Don’t know)The developer agreed to utilize the BRFSS question for smoking prevalence, which can be assessed at the state level. The developer updated the measure submission form accordingly. In response to the Committee’s concern about non-combustible tobacco products, the CDC recognizes the importance of this assessment and adds that some of their surveys “…are moving towards a question like: In the past 30 days have you smoked a cigarette, cigar or pipe (FDA/NIDA proposed question in PATH study) and a separate question on non-combustibles like, In the past 30 days have you used smokeless tobacco such as chewing tobacco, snuff, snus, or dip (FDA/NIDA proposed question in PATH study).” The CDC and the developer are considering the addition of a question on non-combustibles in a future iteration of the measure.
  
  
• Review for Feasibility: H-8; M-3; L-0; I-0(4a. Clinical data generated during care process; 4b. Electronic sources; 4c. Exclusions-no additional data source; 4d. Susceptibility to inaccuracies/unintended consequences identified; 4e. Data collection strategy can be implemented)Rationale:• Data are accessible from existing survey.
  
  
• Review for Usability: H-9; M-2; L-0; I-0(3a. Meaningful/useful for public reporting and quality improvement; 3b. Harmonized; 3c. Distinctive or additive value to exiting measures)Rationale:• Concern about the incentive to drive quality improvement at the national level only, if the measure cannot be drilled down to lower levels of aggregation.• Consider harmonization with other measures. For example, smoking-related measure from NCQA in ongoing Behavioral Health project. Need more to review measure specifications – what questions are used in NCQA’s CAHPS survey measure? Are these aligned with other national surveys? Following the meeting, the developer agreed to use BRFSS’ state-level smoking prevalence measure. The developer revised the measure submission accordingly. In addition, NQF staff reviewed NCQA’s 0027: Medical assistance with smoking and tobacco use cessation. The survey questions used to assess smoking prevalence are generally standardized, except NCQA also assess tobacco use. The survey reads, “Do you now smoke cigarettes or use tobacco every day, some days, or not at all.” CDC asks, “Do you know smoke cigarettes every day, some days, or not at all”.
  
  
• Endorsement Public Comments: July 19-August 17, 2012]Comments include:
  • Concerns about the systematic biases related to validity and accuracy of responses across different populations for patient-reported data.Developer response: This measure assesses members of the population, not patients. Generally, self-reported smoking status is a valid indicator of population-level smoking prevalence, and most national surveys in the United States that assess health behavior rely on self-reported data, such as NHIS and NSDUH. A study by Assaf et al., which examined potential gender differences in self-reported smoking data, compared self-reported smoking behavior to serum thiocyanate and serum cotinine levels. The authors concluded that although there were some differences in self-reporting of smoking status by gender, the results were similar between self-reports and biochemical tests. The authors asserted that the results lent “credibility to the use of self-reports as low-cost accurate approach to obtaining information on smoking behaviors among both men and women in large population-based surveys” (Assaf 2002).
  • Harmonize measure 2020 with measure 0027 Medical assistance with smoking tobacco use cessation (under consideration in the ongoing Behavioral Health project). Developer response: The two metrics assess different aspects of smoking and/or tobacco use. The denominator population for measure 0027 includes health plan members that currently smoke and use tobacco and those that have received tobacco use and smoking cessation advice during a specific time period. Measure 2020 assesses current smoking prevalence (only) among the adult population in the United States. Therefore, harmonization would not be practical or necessary.
  • Include military personnel in the measure’s denominator. Developer response: This would be ideal. While the BRFSS does not include this population in their sample, there is no reason why future iterations of this measure could not accurately assess smoking status in the military as compared to the general population. Many studies examining smoking status in a military population have relied on self-reported data and have used measures similar to the measure used in the BRFSS.
  • Include an assessment of smokeless tobacco. Developer response: This would require a separate measure, with specific validity and reliability testing data. This current smoking prevalence measure is thoroughly tested and has been in use for several years.Steering Committee response: The Committee accepted the developer’s responses and did not change their endorsement consideration. The Committee agreed that military personnel and smokeless tobacco are important assessments to add to the measure in the future.
  
  
  
• Endorsement Committee Recommendation: Steering Committee Recommendation for Endorsement: Y-10; N-0Rationale: The Committee is in favor of developer’s proposed revision to use the BRFSS survey questions.Recommendation: The Steering Committee encourages harmonization with NCQA’s measure #0027 Medical assistance with smoking and tobacco use cessation if possible.

  CSAC Review [October 3, 2012]: Y-11; N-0Decision: Approved for endorsement

  Board Review [October 19, 2012]Decision: Ratified for endorsement
  
  

Measure Specifications

• NQF Number (if applicable): 753
  
  
• Description: Organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients at least 18 years of age undergoing inpatient colon procedures and/or abdominal hysterectomies as reported through the ACS-NSQIP or CDC NHSN. The measure yields separate SIRs for each procedure. (The endorsed specifications of the measure are: Prototype measure for the facility adjusted Standardized Infection Ratio (SIR) of deep incisional and organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients aged >= 18 years as reported through the ACS National Surgical Quality Improvement Program (ACS-NSQIP) or CDC National Health and Safety Network (NHSN). Prototype also includes a systematic, retrospective sampling of operative procedures in healthcare facilities. This prototype measure is intended for time-limited use and is proposed as a first step toward a more comprehensive SSI measure or set of SSI measures that include additional surgical procedure categories and expanded SSI risk-adjustment by procedure type. This single prototype measure is applied to two operative procedures, colon surgeries and abdominal hysterectomies, and the measure yields separate SIRs for each procedure.)
  
  
• Numerator: Deep incisional primary (DIP) and organ/space SSIs during the 30-day postoperative period among patients at least 18 years of age undergoing inpatient colon surgeries or abdominal hysterectomies. SSIs will be identified before discharge from the hospital, upon readmission to the same hospital, or during outpatient care or admission to another hospital (post-discharge surveillance). Case accrual will be guided by sampling algorithms as described below.
  
  
• Denominator: Using multivariable logistic regression models for colon surgeries and abdominal hysterectomies, the expected number of SSIs is obtained. These expected numbers are summed by facility and surgical procedure and used as the denominator of this measure
  
  
• Exclusions: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded.(The endorsed specifications of the measure are: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded. In the NHSN, patients without primary closure of the surgical incision are not considered eligible cases and are excluded- the NSQIP will match this practice for this measure, although this is not standard practice within the NSQIP.)
  
  
• 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: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Conditional support, pending NQF annual update
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is an update to the name of the measure from “reliability adjusted SIR” to “Adjusted Ranking Metric (ARM).”
  • Impact on quality of care for patients:The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
  
• Does the measure address a program goal or objective? Yes. The priority domain is to make care safer by reducing harm caused in the delivery of care.?
  
  
• Is this a high-value measure? Yes. This is an update to a measure currently in the program. The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in this program – the name is being changed from reliability adjusted SIR to the Adjusted Ranking Metric (ARM). Currently, there are three measures in the program measure set implemented and finalized that address the NQS priority of making care safe, two additional ones are proposed. This is the only SSI measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. It is tested at the hospital/acute care facility level, at the facility level of analysis.
  
  
• Is the measure currently in use? Yes. This measure is currently used in this program, but the name of the measure is changing from reliability adjusted SIR to the Adjusted Ranking Metric (ARM).
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It is currently in the program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Affects large numbers, Frequently performed procedures, A leading cause of morbidity/mortality, High resource use, Severity of illness, Patient/societal consequences of poor quality. SSIs estimated to account for 20% of all HAIs[1] 290,485 estimated SSIs/yr[2] Estimated 8,205 deaths associated with SSIs each year[1] Estimated 11% of all deaths occurring in intensive care units are associated with SSIs[1] $34,670 medical cost/SSI[2] Total >$10 billion attributable to SSI in U.S. each year[2] Estimated additional 7-10 days of hospitalization for each SSI per patient[1] [1] Klevens RM, Edwards JR, et al. Estimating healthcare-associated infection and deaths in U.S. hospitals, 2002. Public Health Reports 2007; 122:160-166. [2] Scott, RD. The Direct Medical Costs of Healthcare-Associated Infections in U.S. Hospitals and the Benefits of Prevention. http://www.cdc.gov/ncidod/dhqp/pdf/Scott_CostPaper.pdf accessed April 12, 2010.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Patient Safety Measures
  
  
• Review for Importance: The measure addresses a high impact area. Each year, approximately 11 percent of all deaths in ICUs are associated with SSIs, resulting in up to 20,000 deaths and $2 billion in additional costs.2 Moreover, evidence-based interventions have shown significant reductions in SSI rates and improved health outcomes.
  
  
• Review for Scientific Acceptability: See CDP Recommendation]
  
  
• Review for Feasibility: See CDP Recommendation]
  
  
• Review for Usability: See CDP Recommendation]
  
  
• Review for Related and Competing Measures: See CDP Recommendation]
  
  
• Endorsement Committee Recommendation: The Steering Committee discussed the newly-harmonized measure in a supplemental conference call, reviewing the relevant changes, while also receiving clarification from the developers on several issues. Committee members inquired as to why these two particular measures had been chosen, and asked for clarification on the plan for public reporting. The developer explained that the CMS IPPS requirements released on August 1, 2011, call for abdominal hysterectomies and colon surgeries to be reported by the CDC to CMS. The NHSN will serve as the single reporting system for CMS-required reporting. However, facilities may choose which calculations of performance on the measure can be accomplished using either the NHSN or NSQIP data system. The measure developer acknowledged that for hospitals participating in both systems, there could be duplication.The Steering Committee questioned why both organ space and deep incisional infections were included in the measure. The developer described the approach as a long standing precedent and stated that superficial infections are considered trivial events and therefore not included. However, organ space infections that drain through the incisions are classified as deep incisional infections. The combination of organ space and deep incisional infections are considered a clinically coherent grouping. The Committee expressed their appreciation for the developers’ efforts at harmonization, and agreed that the measure continues to meet the four major evaluation criteria. The Steering Committee recommended this measure for endorsement in a unanimous vote.This outcome measure replaces NQF-endorsed measure #0299 (Surgical Site Infection Rate) and addresses the National Priority area of safety.
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to an aortic aneurysm procedure inpatient (IP) stay and attributes them to the hospital where the index IP stay occurred. It includes abdominal aortic aneurysm and thoracic aortic aneurysm subtypes.
  
  
• Numerator: The numerator of the Aortic Aneurysm Procedure Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to the aortic aneurysm procedures across a hospital’s eligible aortic aneurysm procedure episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure does not address any of the high-priority domains identified by CMS for future measure consideration. Analytic evidence demonstrating that a performance gap exists or that there is a variation in performance among providers for aortic aneurysm procedures was not provided as required for measures that may be considered for potential adoption in the IQR program. Furthermore, a similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program and captures a broader population than the MUC, which is procedure specific.
  • Impact on quality of care for patients:Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
  
• Does the measure address a program goal or objective? No. This measure does not address any of the domains identified by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
• Does this measure fill a gap in the program measure set? No. Analytic evidence was not provided demonstrating that a performance gap exists or that there is a variation in performance among providers for aortic aneurysm procedures.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a Cholecystectomy and Common Duct Exploration IP stay and attributes them to the hospital where the index IP stay occurred.
  
  
• Numerator: The numerator of the Cholecystectomy and Common Duct Exploration Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to cholecystectomy and common duct exploration across a hospital’s eligible Cholecystectomy and Common Duct Exploration episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure does not address any of the high-priority domains identified by CMS for future measure consideration. Analytic evidence demonstrating that a performance gap exists or that there is a variation in performance among providers for cholecystectomy and common duct exploration procedures was not provided as required for measures that may be considered for potential adoption in the IQR program. Furthermore, a similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program and captures a broader population than the MUC, which is procedure specific.
  • Impact on quality of care for patients:Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
  
• Does the measure address a program goal or objective? No. ?This measure does not address any of the domains identified by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
• Does this measure fill a gap in the program measure set? No. Analytic evidence not provided demonstrating that a performance gap exists or that there is a variation in performance among providers for aortic aneurysm procedures.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC which is procedure specific.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This measure assesses the difference (“excess”) between the average number of risk-adjusted days a hospital’s patients spend in an ED, observation, or readmission in the 30 days following a hospitalization for pneumonia (“predicted”) and the number of days in acute care that they would have been expected to spend if discharged from an average hospital.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We use this field to describe the outcome. The outcome of the measure is the average number of days the patient spends in acute care (ED treat-and-release visits, observation stays, and readmissions) during the first 30 days after discharge from the hospital. An ED visit is defined as a visit with revenue center codes ‘0450’, ‘0451’, ‘0452’, ‘0459’, or ‘0981’. Each ED visit is counted as one half-day (0.5 days). An observation stay is defined as a visit with revenue center code ‘0762’ or Healthcare Common Procedure Coding System (HCPCS) code ‘G0378’ (in the outpatient data files) or Current Procedural Terminology (CPT) codes ‘99217’ to ‘99220’ or ‘99234’ to ‘99236’ (in the Physician Carrier data files). Observation stays are recorded in terms of hours and converted for the measure into half-days (rounded up). A readmission is defined as any unplanned acute care hospital inpatient hospitalization within 30 days of the discharge date for the index hospitalization. “Planned” readmissions are those planned by providers for anticipated medical treatment or procedures that must be provided in the inpatient setting. To exclude planned readmissions, we use the planned readmission algorithm previously developed for the CMS 30-day pneumonia readmission measure. Each rehospitalization is counted according to the length of stay, calculated as the discharge date minus the admission date. Admissions that extend beyond the 30-day follow-up period are truncated on day 30. When an ED visit, observation stay, or readmission overlaps with another event, we count only the most severe of the overlapping events
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The denominator includes Medicare FFS beneficiaries aged 65 years and older hospitalized at non-Federal hospitals with a principle discharge diagnosis of pneumonia, aspiration pneumonia, and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. To be included in the cohort the patients must have been continuously enrolled in Medicare FFS Parts A and B for the 12 months prior to the index hospitalization.
  
  
• Exclusions: This measure excludes index admissions for patients who leave the hospital against medical advice. This measure also excludes index admissions for patients without at least 30 days post-discharge enrollment in FFS Medicare.
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination, Best Practice of Healthy Living
  
  
• HHS Data Source: Administrative claims The Medicare data sources used to create this measure were: 1. Medicare Enrollment Database (EDB) (to determine eligibility). This dataset contains Medicare beneficiary demographic, benefit/coverage, enrollment status, and vital status information. 2. Medicare hospital inpatient and outpatient claims, and physician Carrier claims. 3. CCW 100% condition-specific datasets. Specifically, the measure uses the outpatient hospital institutional claims file and physician Carrier file (also known as the Physician/Supplier Part B claims file). This third data source is used to capture the outcome of acute care days of ED visits and observation stays.
  
  
• 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: Conditional support, pending NQF review and endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is an update to a measure previously supported by the MAP with the condition that NQF review and endorse the measure. The cohort has been expanded to include patients with principle discharge diagnosis of aspiration pneumonia and sepsis with an accompanying secondary diagnosis of pneumonia that is present on admission and aligns with NQF #0468 - Hospital 30-day, all-cause, risk-standardized mortality rate (RSMR) following pneumonia hospitalization and NQF #0506 - Hospital 30-day all-cause risk-standardized readmission rate (RSRR) following pneumonia hospitalization.
  • Impact on quality of care for patients:Existing measures publicly report readmission rates and mortality rates following hospitalization for pneumonia. These measures do not include all post-discharge outcomes that matter to patients, such as having to return to the ED or spend time under observation. Moreover, the increasing use of observation care may be replacing some readmissions. Hospitals with high rates of observation stays in the post-discharge period may therefore have low readmission rates that do not fully reflect the quality of care. This measure adds to the existing measurement landscape by including other outcomes (i.e., ED visits, observation stays), by capturing the total amount of time patients spend in acute care, and by accounting for time at risk of an event (i.e. survival time).
  
  
  
• Does the measure address a program goal or objective? Yes. ?This is an update to a measure previously conditionally supported by the MAP and addresses the high-priority domains “Patient and Family Engagment and Best Practices of Health Living”.
  
  
• Is this a high-value measure? Yes. Approximately 20 percent of pneumonia patients were rehospitalized within thirty days, representing the second-highest proportion of all rehospitalizations at 6.3 percent [Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009;360(14):1418-28]. Acute care utilization after discharge (return to the emergency department, observation stay and readmission), for any reason, is disruptive to patients and caregivers, costly to the healthcare system, and puts patients at additional risk of hospital-acquired infections and complications.
  
  
• Does this measure fill a gap in the program measure set? N/A. This is an update to a measure previously recommended by the MAP
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The measure was given conditional support on condition that it be reviewed by NQF and endorsed. The cohort has been expanded to include patients with principle discharge diagnosis of aspiration pneumonia and sepsis with an accompanying secondary diagnosis of pneumonia that is present on admission and aligns with NQF # 0468 - Hospital 30-day, all-cause, risk-standardized mortality rate (RSMR) following pneumonia hospitalization and NQF # 0506 - Hospital 30-day all-cause risk-standardized readmission rate (RSRR) following pneumonia hospitalization.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Pneumonia results in approximately 1.2 million hospital admissions each year and accounts for more than $10 billion annually in hospital expenditures. Approximately 20% of pneumonia patients were rehospitalized within thirty days, representing the second-highest proportion of all rehospitalizations at 6.3% (Jencks et al., 2009). Acute care utilization after discharge (return to the emergency department, observation stay and readmission), for any reason, is disruptive to patients and caregivers, costly to the healthcare system, and puts patients at additional risk of hospital-acquired infections and complications. Although some readmissions are unavoidable, they may also result from poor quality of care or inadequate transitional care. Numerous studies have found an association between quality of inpatient or transitional care and early (typically 30-day) readmission rates for a wide range of conditions including pneumonia (Frankl et al., 1991; Corrigan et al., 1992; Oddone et al., 1996; Ashton et al., 1997; Benbassat et al., 2000; Courtney et al., 2003; Halfon et al., 2006; Dean et al., 2006). Several studies also have reported on the relationship between inpatient admissions and other types of hospital care including ED visits and observation stays. Two recent studies conducted in patients of all ages have shown that 9.5% of patients return to the ED within 30 days of hospital discharge and that about 12% of these patients are discharged from the ED and are not captured by current CMS readmissions measures (Rising et al., 2013; Vashi et al., 2013). Rising rates of observation stays among Medicare beneficiaries have gained the attention of patients, providers, and policymakers (Feng et al., 2012; Rising et al., 2013; Vashi et al., 2013). A report from the Office of the Inspector General (OIG) notes the potential relationship between hospital use of observation stays as an alternative to short-stay inpatient hospitalizations as a response to changing hospital payment incentives (Wright, 2013). Thus, in the context of the publicly reported CMS 30-day readmission measures, the increasing use of ED visits and observation stays has raised concerns that current readmission measures do not capture the full range of unplanned acute care in the post-discharge period. References: Ashton CM, Del Junco DJ, Souchek J, Wray NP, Mansyur CL. The association between the quality of inpatient care and early readmission: a meta-analysis of the evidence. Med Care. Oct 1997;35(10):1044-1059. Benbassat J, Taragin M. Hospital readmissions as a measure of quality of health care: advantages and limitations. Archives of Internal Medicine. Apr 24 2000;160(8):1074-1081. Corrigan JM, Martin JB. Identification of factors associated with hospital readmission and development of a predictive model. Health Serv Res. Apr 1992;27(1):81-101. Courtney EDJ, Ankrett S, McCollum PT. 28-Day emergency surgical re-admission rates as a clinical indicator of performance. Ann R Coll Surg Engl. Mar 2003;85(2):75-78. Dean NC, Bateman KA, Donnelly SM, Silver MP, Snow GL, Hale D. Improved clinical outcomes with utilization of a community-acquired pneumonia guideline. Chest. 2006;130(3):794-799 Feng Z, Wright B, Mor V. Sharp rise in Medicare enrollees being held in hospitals for observation raises concerns about causes and consequences. Health affairs (Project Hope). Jun 2012;31(6):1251-1259. Frankl SE, Breeling JL, Goldman L. Preventability of emergent hospital readmission. Am J Med. Jun 1991;90(6):667-674. Halfon P, Eggli Y, Pr, et al. Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Medical Care. Nov 2006;44(11):972-981. Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009;360(14):1418-28. Oddone EZ, Weinberger M, Horner M, et al. Classifying general medicine readmissions. Are they preventable? Veterans Affairs Cooperative Studies in Health Services Group on Primary Care and Hospital Readmissions. Journal of General Internal Medicine. 1996;11(10):597-607. Rising KL, White LF, Fernandez WG, Boutwell AE. Emergency Department Visits After Hospital Discharge: A Missing Part of the Equation. Annals of Emergency Medicine. Vashi AA, Fox JP, Carr BG, et al. Use of hospital-based acute care among patients recently discharged from the hospital. JAMA : the journal of the American Medical Association. Jan 23 2013;309(4):364-371. Wright S. Hospitals’ Use of Observation Stays and Short Inpatient Stays for Medicare Beneficiaries. Washington, DC: OIG;2013

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This stroke mortality measure will estimate the hospital-level, risk-standardized mortality rate (RSMR) for patients discharged from the hospital with a principal discharge diagnosis of acute ischemic stroke. The outcome is all-cause 30-day mortality, defined as death from any cause within 30 days of the index admission date, including in-hospital death, for stroke patients. The measure uses Medicare fee-for-service (FFS) administrative claims to derive the cohort and outcome, and for risk adjustment. The major revision is to include NIH Stroke Scale as a measure of stroke severity in the risk-adjustment.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure outcome. The measure outcome is death from any cause within 30 days of the admission date of the index admission for patients with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Denominator: The cohort includes inpatient admissions for patients aged 65 years and older who were discharged from short-term acute care hospitals with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Exclusions: The measure excludes admissions for patients: -with inconsistent or unknown vital status or other unreliable data (unreliable or missing data limit the validity of the risk-adjustment model); -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 (because these patients are likely continuing to seek comfort measures only and mortality is not necessarily an adverse outcome or signal of poor quality care for these patients); and -discharged against medical advice (because providers did not have the opportunity to deliver full care and prepare the patient for discharge).
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims. The measure uses Medicare administrative claims data. The Medicare data sources used to create the measure were: 1) Medicare Part A inpatient and Outpatient and Part B outpatient claims from the Standard Analytic File, including inpatient and outpatient claims for the 12 months prior to an index admission. This dataset was used to identify the cohort (Part A inpatient) and to identify comorbidities (Part A inpatient and outpatient and Part B outpatient). 2) Medicare Enrollment Database (EDB): This database contains Medicare beneficiary demographic, benefit/coverage, and vital status information. This dataset was used to obtain information on several inclusions/exclusions indicators such as Medicare status on admission, and to ascertain the outcome (death).
  
  
• 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: Conditional support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This outcome mortality measure adjusts for stroke severity using the NIHSS as recommended by the clinical practice guidelines. The current publicly reported stroke mortality measure does not include stroke severity in the risk adjustment model.
  • Impact on quality of care for patients:There is a need to define the relevant stroke outcomes to measure and the factors that should be accounted for to make comparisons across different facilities valid so that the quality of stroke care can be evaluated and optimized. Stroke severity is the most important prognostic factor for individual patients and appears to be a significant predictor in hospital-level performance therefore inclusion in the risk model is recommended in a Statement for Healthcare Professional from the American Heart Association/American Stroke Association
  
  
  
• Does the measure address a program goal or objective? N/A. ?This measure is currently in the IQR program but it is undergoing substantial change.
  
  
• Is this a high-value measure? Yes. Mortality following stroke is an important adverse outcome that can be measured reliably and objectively. The 30-day stroke mortality rate varies by age from 9 percent in patients 65-74 years of age to 23 percent in those =85 years of age [Casper ML NI, Croft JB, Nilasena DS. Atlas of Stroke Hospitalizations Among Medicare Beneficiaries. 2008]. Post-stroke mortality rates have also been shown to be influenced by critical aspects of care.CMS currently publicly reports a claims-based stroke mortality measure. The results of this measure, as reported in the 2014 update to the Hospital Compare, demonstrate a median hospital RSMR of 15.3 percent, with a range of 8.6 percent to 23.8 percent. This variation across hospitals indicates that there is room for improvement in care for stroke patients that could reduce mortality rates. Additionally, risk-adjusted 30-day mortality rates were shown to decline from 12.1 percent to 11.6 percent in Medicare FFS from 1999 to 2011 [Krumholz HM, Normand S-LT, Wang Y. Trends in Hospitalizations and Outcomes for Acute Cardiovascular Disease and Stroke: 1999-2011. Circulation. August 18, 2014]. This decline suggests that there is opportunity for further improvement in the 30-day mortality outcome over time.
  
  
• Does this measure fill a gap in the program measure set? N/A. This administrative claims based measure is already in the program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure was tested at the facility level in the acute care setting.
  
  
• Is the measure currently in use? Yes. Hospital IQR, 2014 (FY 2015)
  
  
• Does a review of its performance history raise any concerns? Yes. According to the American Heart Association, inadequate risk adjusting stroke outcome measures could result in financial penalties for hospitals, which could result in those hospitals avoiding the sickest stroke patients or electing not to pursue stroke center status. Comprehensive stroke centers could also be less inclined to accept transfers of patients with devastating stroke. These negative incentives could result in exacerbation in disparities for vulnerable populations, and the rapidly developing stroke systems of care would be undermined.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This administrative claims based measure is already in the IQR program. CMS is revising this version of the measure to include stroke severity in the risk-adjustment model [Claims-Based and Hybrid Measures of 30-Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (Version 1.0)].
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Post-stroke mortality rates have been shown to be influenced by critical aspects of care at the hospital such as response to complications, speediness of delivery of care, organization of care, and appropriate imaging [Smith et al., 2006; Reeves et al., 2009; Lingsma et al., 2008; Hong et al., 2008; Fonarow et al., 2014]. This research demonstrates the relationship between hospital organizational factors and performance on the stroke mortality measure, and supports the ability of hospitals to impact these rates.

Measure Specifications

• NQF Number (if applicable): 2579
  
  
• Description: This measure estimates hospital-level, risk-standardized payment for a pneumonia episode of care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of pneumonia, aspiration pneumonia, and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. (The endorsed specifications of the measure are: This measure estimates hospital-level, risk-standardized payment for a pneumonia episode of care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of pneumonia.)
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We are using this field to define the outcome. The outcome for this measure is a hospital-level, risk-standardized payment for Medicare patients for a pneumonia episode-of-care. The payment timeframe starts from the admission date of an index hospitalization through 30 days post-admission. We include payments for the index admission, as well as payments for subsequent inpatient, outpatient, skilled nursing facility, home health, hospice, physician/clinical laboratory/ambulance services, supplier Part B items, and durable medical equipment, prosthetics/orthotics, and supplies. In order to compare payments for Medicare patients related to clinical care, we remove geography and policy adjustment from our payment calculation whenever possible. If the data for a specific care setting do not allow for the removal of these adjustments, we calculate an average payment for each item across all geographic areas and replace the claim payment amount in the data with the average payment amount for that item.
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The measure cohort includes admissions to non-federal, short-stay, acute-care hospitals for Medicare FFS patients age 65 years and older with a principal discharge diagnosis of pneumonia, or aspiration pneumonia, or sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. Patients must also have continuous enrollment in Medicare Part A and Part B benefits for the 12 months prior to the index admission and 30 days post- admission.
  
  
• Exclusions: The measure excludes patients with: 1. Incomplete administrative data in the 30 days following the index admission (if alive) 2. Same or next day discharge and patient did not die or get transferred 3. Transfers into the hospital 4. Inconsistent or unknown mortality status 5. Unreliable data 6. Patients who leave hospital against medical advice (AMA) 7. Patients enrolled in hospice in year prior to admission or day of admission 8. Transfers to Federal hospitals 9. Patients without an index admission DRG or DRG weight 10. Admissions within 30 days of a previous index admission
  
  
• HHS NQS Priority: Communication and Care Coordination, Making Care Affordable
  
  
• HHS Data Source: Administrative claims. Medicare administrative claims data for certain Part A and Part B services in the 12 months prior to and during the index admission are used for risk adjustment. The data also contain price-standardized payments for Medicare patients across multiple care settings, services, and supplies (i.e., inpatient, outpatient, SNF, home health, hospice, physician/clinical laboratory/ambulance services, and durable medical equipment, prosthetics/orthotics, and supplies). The price-standardized payment data element is harmonized across CMS cost and resource use measures
  
  
• Measure Type: Cost/Resource Use
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: CMS is expanding the cohort to match the pneumonia mortality measure. In addition to patients with pneumonia as the principle discharge diagnosis the measure will also include patients with a principle discharge diagnosis of aspiration pneumonia, and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission.
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional support, pending NQF review and endorsement of revised specifications
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This NQF-endorsed cost and resource measure is already in the IQR program and addresses the previously identified gap of affordability/cost measures. CMS is expanding the cohort to match the pneumonia mortality measure which includes patients with a principle diagnosis of aspiration pneumonia and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. CMS is encouraged to submit the updated specifications to NQF when revisions to the measure are complete.
  • Impact on quality of care for patients:A measure of payments for Medicare patients to hospitals that is aligned with current quality of care measures will facilitate profiling hospital value (payments and quality). This measure will reflect differences in the management of care for patients with pneumonia both during hospitalization and immediately post-discharge. Pneumonia is a condition with substantial range in costs of care and for which there are well-established publicly reported quality measures and is therefore an ideal condition for assessing relative value for an episode-of-care that begins with an acute hospitalization. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care.
  
  
  
• Does the measure address a program goal or objective? N/A. ?This cost and resource use measure is currently in the hospital IQR program but is undergoing substanstial changes.
  
  
• Is this a high-value measure? Yes. This measure, which uses standardized payments, reflects differences in the management of care for patients with PNA both during hospitalization and immediately post-discharge. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care. Also, this measure is intended to be paired with other quality measures, such as risk-standardized mortality. As such the goal is to incentivize improvements in quality that will lead to better outcomes at lower costs of care.
  
  
• Does this measure fill a gap in the program measure set? Yes. This measure addresses the previously identified gap of affordability/cost measures. MAP previously noted the need for condition-specific cost information.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure has been tested at the facility level in the acute care setting.
  
  
• Is the measure currently in use? Yes. Hospital IQR (publicly reported July 2015, in payment program FY 2017)
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The price-standardized payment data element is harmonized across CMS cost and resource use measures. This measure uses Medicare administrative claims data and enrollment information. Medicare administrative claims data for certain Part A and Part B services in the 12 months prior to and during the index admission are used for risk adjustment. The data also contain price-standardized payments for Medicare patients across multiple care settings, services, and supplies (i.e., inpatient, outpatient, SNF, home health, hospice, physician/clinical laboratory/ambulance services, and durable medical equipment, prosthetics/orthotics, and supplies).
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. CMS is expanding the cohort to match the pneumonia mortality measure. In addition to patients with pneumonia as the principle discharge diagnosis the measure will also include patients with a principle discharge diagnosis of aspiration pneumonia, and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission.
  
  

Rationale for measure provided by HHS
Medicare spending is estimated to have been $525.0 billion in 2010 with annual growth rates projected to be 6.3% for 2013 through 2020 due to both an increase in the Medicare population as well as Medicare spending on each beneficiary[1]. Further projections anticipate an exhaustion of Medicare‘s Hospital Insurance Trust Fund (Part A) by 2024 [2]. The growth in spending is unsustainable and highlights the need to understand the value of care Medicare buys with every dollar spent. Given the urgency of the state of the Medicare Hospital Insurance Trust Fund and the fact that Medicare pays for 40-50% of hospitalizations nationally [3], hospital costs are a natural venue in which to deconstruct payments for Medicare patients. Yet payments to hospitals are difficult to interpret in isolation. Some high payment hospitals may have better clinical outcomes when compared with low payment hospitals; other high payment hospitals may not. For this reason, the value of hospital care is more clearly assessed when pairing hospital payments with hospital quality. A measure of payments for Medicare patients to hospitals that is aligned with current quality of care measures will facilitate profiling hospital value (payments and quality). This measure will reflect differences in the management of care for patients with pneumonia both during hospitalization and immediately post-discharge. Pneumonia is a condition with substantial range in costs of care and for which there are well-established publicly reported quality measures and is therefore an ideal condition for assessing relative value for an episode-of-care that begins with an acute hospitalization. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care. 1. Ash AS, Byrne-Logan S. How Well Do Models Work? Predicting Health Care Costs. Proceedings of the Section on Statistics in Epidemiology. American Statistical Association. 1998. 2. Medpac. Report to the Congress: Medicare Payment Policy 9/17/12 2012. 3. National Hospital Discharge Survey. http://www.cdc.gov/nchs/nhds.htm. Accessed 08/07/2012.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Endorsing Cost and Resource Use Measures: Phase 3
  
  
• Review for Importance: The measure meets the Importance criteria1a. High Priority: H-17; M-5; L-0; I-0; IE-0; 1b. Opportunity for Improvement: H-19; M-2; L-1; I-0; 1c. Measure Intent: H-18; M-4; L-0; I-0 1. Overall Importance: H-18; M-4; L-0; I-0Rationale:• The Committee stated that the measure is high priority given that pneumonia is one of the leading causes of hospitalization for Medicare patients sixty-five years of age and older, with Medicare paying roughly ten billion dollars in aggregate costs for hospitalized beneficiaries with pneumonia. • The developer presented evidence indicating that there is a threefold variation in cost for the medical treatment of pneumonia patients, which the Committee agreed signified that there is a substantial opportunity for improving the overall costs for pneumonia patients.• The Committee stated that by using this measure in conjunction with a measure capturing the quality of care for pneumonia patients, there is an opportunity to begin to understand the value of the care provided by the hospitals and other providers in treating this condition.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-10; M-11; L-1; I-0 2b. Validity: H-3; M-18; L-1; I-0Rationale:• The Committee stated that the measure specifications were precise and that the measure was well-constructed. This measure captures risk-standardized payments for a thirty-day episode of care for Medicare patients diagnosed admitted to the hospital with a diagnosis of pneumonia through administrative claims data.• The developer provided reliability testing at the level of the performance measure score; testing was performed by calculating the Intraclass Correlation Coefficient (ICC) score by calculating the risk standardized payment using a split-sample of the combined 2008-2009 data from hospitals. The ICC score was 0.825, indicating significant agreement between the two samples, which the Committee found sufficient.• The Committee questioned the validity of specifying the measure for a thirty-day episode triggered by admission for pneumonia, as the treatment of pneumonia may require care coordination post-discharge that may extend past thirty days. The Committee stated that this could affect payments captured during the post-discharge period, artificially inflating or deflating the costs for some patients simply because of the construct of the measure.• The Committee raised concerns regarding the attribution approach and the implications for attribution of costs if a patient were transferred to another hospital. The developer clarified that only 0.4 percent of cohorts are transferred for pneumonia, which represents a small number of beneficiaries. In the case of transfer patients, costs for the patient will be attributed to the initial admitting hospital, as hospitals are increasingly responsible for care delivered up to 30 days after discharge. The Committee found this approach to attribution to be acceptable.• The Committee stated concern that the low r-squared value (.07) for the risk model may indicate that case mix is not being appropriately adjusted for through the risk model. The developer clarified that at lower patient volumes, there is less certainty when estimating cost. The measure uses a continuous outcome which results in a more accurate estimate than would result from a binary outcome. Additionally, the measure uses hierarchical risk modeling that adjusts hospitals with low patient volume towards the mean. The Committee found this explanation to be sufficient.• The Committee questioned whether adjustments for sociodemographic status (SDS) factors should be incorporated into the risk adjustment model. NQF clarified that it is in the early stages of reviewing our policy on risk adjusting for SDS factors. The recommendations for modifying NQF’s current policy on adjusting for SDS factors have not yet been finalized. As such, we ask that Committees continue to evaluate measures according to our current guidelines, that SDS factors are not included in the risk adjustment model, but are used to stratify the measure. If in the future the recommendations for adjusting for SDS factors become NQF policy, measures that may be improved from incorporating these adjustments will be updated and reviewed by the Committee through one of NQF’s measure maintenance processes.
  
  
• Review for Feasibility: H-20; M-2; L-0; I-0(3a. Byproduct of Care Processes; and 3b. Electronic sources; and 3c. Data Collection Strategy)Rationale: The Committee stated that this measure is feasible to implement because the measure is specified using administrative claims data which is created as a byproduct of care delivery and available electronically.
  
  
• Review for Usability: H-10; M-11; L-1; I-0(4a. Accountability/transparency (used in accountability w/in 3 yr, public reporting w/in 6 yr, or if new - credible plan); and 4b. Improvement – progress demonstrated (if new - credible rationale); and 4c. Unintended Consequences - benefits outweigh evidence of unintended negative consequences (to patients/populations); and 4d. Measure Deconstruction – can be deconstructed to facilitate transparency and understanding)Rationale:• The Committee found the measure to be useful for providers, giving them access to detailed data of cost for hospital care for pneumonia.• The Committee questioned the availability of information on costs for providers other than the hospital to which the patient has been attributed, stating that for this measure to be most useful there needs to be documentation of the reimbursement amounts for each provider treating the patient.
  
  
• Review for Related and Competing Measures: No related or competing measures identified.
  
  
• Endorsement Public Comments: August 14, 2014 - September 12, 2014Comments received:• One measure-specific comment was received regarding the appropriateness of the attribution approach for measure #2579. The commenter suggested that the current attribution approach is inappropriate and only reflects an episode-of-care attributed to a hospital as the responsible entity and does not account for the care of multiple providers across the health care delivery system. The commenter suggested this approach would be more appropriate for an integrated health system or an organization accepting bundled payments.• Two comments regarding risk adjustment for sociodemographic status for this measure. Some commenters believed that it would be appropriate to stratify claims by sociodemographic factors and document non-clinical elements that negatively impact patient outcomes when calculating risk adjusted costs.• One measure-specific comment was received regarding validity of exclusions for measure this measure. A commenter proposed the inclusion of ICD-9 code 507.0 in the denominator for aspiration pneumonia, which was estimated to account for 15% of Medicare patients discharged with pneumonia.Developer response:• Yale addressed the concern of integrating the ICD-9 code 507.0 in the denominator for aspiration pneumonia and based on the prevalence of the code, developers will plan to reevaluate including aspiration pneumonia in future versions of the measure.Committee responses:• The Committee acknowledged and many shared the concerns with the attribution approach used in this measure; however, they also stated that hospitals are increasingly responsible for care delivered up to 30 days after discharge. Consequently, hospitals are in the unique position of being able to push coordination of care, and this measure may serve as an impetus for this to occur.• The Committee recognizes the importance of adequately adjusting for sociodemographic status in the appropriate applications. While NQF continues to work on their implementation of the guidance from the SDS Expert Panel, measures currently under review have been recommended with additional guidance to stratify for SDS, as appropriate.• Based on the NQF criteria for validity, the Committee has agreed that this measure has met the criteria for validity and has recommended it for endorsement. A few committee members support the inclusion of ICD-9 code 507.0 within this measure, which will assist with documenting the presence of pneumonia aspiration among admission.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-21; N-1.
  
  NQF Member Voting: October 6, 2014- October 20, 2014
  Representatives of 18 member organizations voted, with 50% approval;consensus was not reached. 
  
  Consensus Standards Approval Committee (CSAC) Vote: November 12,2014; Y-13, N-0
  Endorsed with the same conditions the CMS cardiovascular hospitallevel episode-based measures from phase II. 
  
  Board of Directors Executive Committee Vote: December 22, 2014
  Ratified endorsement with the following conditions:
  
  • One- year Look Back Assessment of Unintended Consequences: NQFstaff will work with Cost and Resource Standing Committee andCMS to determine a plan for assessing potential unintendedconsequences of this measure in use. The evaluation ofunintended consequences will be initiated in approximately oneyear and possible changes to the measures based on this data.
  • Consideration for SDS trial period: The Cost and Resource UseStanding Committee will consider whether the measure should beincluded in the NQF trial period for sociodemographic statusadjustments.
  • Attribution: NQF will consider opportunities to address theattribution issue. 
  Appeals: December 30, 2014 -January 28, 2015
  No appeals submitted.
  
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This hybrid stroke mortality measure will estimate the hospital-level, risk-standardized mortality rate (RSMR) for patients discharged from the hospital with a principal discharge diagnosis of acute ischemic stroke. The outcome is all-cause 30-day mortality, defined as death from any cause within 30 days of the index admission date, including in-hospital death, for stroke patients. The measure is referred to as a hybrid because it will use Medicare fee-for-service (FFS) administrative claims to derive the cohort and outcome, and claims and clinical EHR data for risk adjustment.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure outcome. The measure outcome is death from any cause within 30 days of the admission date of the index admission for patients with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Denominator: The cohort includes inpatient admissions for patients aged 65 years and older who were discharged from short-term acute care hospitals with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Exclusions: The measure excludes admissions for patients: -with inconsistent or unknown vital status or other unreliable data); -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 and -discharged against medical advice
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims (cohort, outcome assessment; risk adjustment), Clinical EHR data: risk adjustment. The measure uses Medicare administrative claims data and clinical data that are extracted from electronic health records (EHRs). Because there is currently no large national dataset that includes patient-level EHR data related to patients with acute ischemic stroke, this measure was developed using Medicare administrative claims and data collected in the American Heart Association (AHA)/American Stroke Association (ASA)’s Get With The Guidelines (GWTG)-Stroke registry for model development and validation. Administrative claims data were obtained from Medicare Inpatient/Outpatient Claims Databases as well as Medicare’s Enrollment Database (EDB), containing Medicare beneficiary demographic (including age, gender, and birth date), benefit/coverage, and vital status information (such as whether the patient was dead or alive, and date of death).
  
  
• 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: Conditional support, pending NQF review and endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This outcome mortality measure adjusts for stroke severity using the NIHSS as recommended by the clinical practice guidelines. The currently publicly reported stroke mortality measure uses administrative claims data only for risk adjustment, and does not include an assessment of stroke severity. *The stage of development for this MUC was updated to "Fully Developed" on December 3, 2015, after the MUC was publicly released.
  • Impact on quality of care for patients:There is a need to define the relevant stroke outcomes to measure and the factors that should be accounted for to make comparisons across different facilities valid so that the quality of stroke care can be evaluated and optimized. Stroke severity is the most important prognostic factor for individual patients and appears to be a significant predictor in hospital-level performance therefore inclusion in the risk model is recommended in a Statement for Healthcare Professional from the American Heart Association/American Stroke Association
  
  
  
• Does the measure address a program goal or objective? N/A. ?This stroke mortality measure is already in the program but it uses administrative claims data only for risk adjustment and does not include an asessment of stroke severity. The proposed measure incorporates clinical data and an assessment of stroke severity into the risk adjustment model.
  
  
• Is this a high-value measure? Yes. Mortality following stroke is an important adverse outcome that can be measured reliably and objectively. The 30-day stroke mortality rate varies by age from 9 percent in patients 65-74 years of age to 23 percent in those =85 years of age [Casper ML NI, Croft JB, Nilasena DS. Atlas of Stroke Hospitalizations Among Medicare Beneficiaries. 2008]. Post-stroke mortality rates have also been shown to be influenced by critical aspects of care.CMS currently publicly reports a claims-based stroke mortality measure. The results of this measure, as reported in the 2014 update to the Hospital Compare, demonstrate a median hospital RSMR of 15.3 percent, with a range of 8.6 percent to 23.8 percent. This variation across hospitals indicates that there is room for improvement in care for stroke patients that could reduce mortality rates. Additionally, risk-adjusted 30-day mortality rates were shown to decline from 12.1 percent to 11.6 percent in Medicare FFS from 1999 to 2011 [Krumholz HM, Normand S-LT, Wang Y. Trends in Hospitalizations and Outcomes for Acute Cardiovascular Disease and Stroke: 1999-2011. Circulation. August 18, 2014]. This decline suggests that there is opportunity for further improvement in the 30-day mortality outcome over time.
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is already in the program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure was tested at the facility level in the acute care setting.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The currently publicly reported stroke mortality measure uses administrative claims data only for risk adjustment, and does not include an assessment of stroke severity. Therefore, this new measure seeks to satisfy stakeholder preferences by incorporating clinical data and an assessment of stroke severity into the risk adjustment models, while improving discrimination of the stroke mortality risk models. This measure incorporates clinical data and an assessment of stroke severity into the risk adjustment model. It uses EHR data for risk adjustment [Claims-Based and Hybrid Measures of 30-Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report (Version 1.0)].
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Post-stroke mortality rates have been shown to be influenced by critical aspects of care at the hospital such as response to complications, speediness of delivery of care, organization of care, and appropriate imaging [Smith et al., 2006; Reeves et al., 2009; Lingsma et al., 2008; Hong et al., 2008; Fonarow et al., 2014]. This research demonstrates the relationship between hospital organizational factors and performance on the stroke mortality measure, and supports the ability of hospitals to impact these rates. The hybrid measure addresses a limitation of the claims-only measure by incorporating clinical data collected at the time of admission to assess the condition of the patient before care has been administered.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This hybrid stroke mortality measure will estimate the hospital-level, risk-standardized mortality rate (RSMR) for patients discharged from the hospital with a principal discharge diagnosis of acute ischemic stroke. The outcome is all-cause 30-day mortality, defined as death from any cause within 30 days of the index admission date, including in-hospital death, for stroke patients. The measure is referred to as a hybrid because it will use Medicare fee-for-service (FFS) administrative claims to derive the cohort and outcome, and clinical data (EHR extracted) for risk adjustment.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure outcome. The measure outcome is death from any cause within 30 days of the admission date of the index admission for patients with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Denominator: The cohort includes inpatient admissions for patients aged 65 years and older who were discharged from short-term acute care hospitals with a principal discharge diagnosis of acute ischemic stroke.
  
  
• Exclusions: The measure excludes admissions for patients: -with inconsistent or unknown vital status or other unreliable data); -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 and -discharged against medical advice
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims ( cohort, outcome assessment; risk adjustment), EHR data: risk adjustment. The measure uses Medicare administrative claims data and clinical data that are extracted from electronic health records (EHRs). Because there is currently no large national dataset that includes patient-level EHR data related to patients with acute ischemic stroke, this measure was developed using Medicare administrative claims (for cohort derivation and outcome assessment) and data collected in the American Heart Association (AHA)/American Stroke Association (ASA)’s Get With The Guidelines (GWTG)-Stroke registry for model development and validation. Administrative claims data were obtained from Medicare Inpatient/Outpatient Claims Databases as well as Medicare’s Enrollment Database (EDB), containing Medicare beneficiary demographic (including age, gender, and birth date), benefit/coverage, and vital status information (such as whether the patient was dead or alive, and date of death).
  
  
• 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: Conditional support, pending NQF review and endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This outcome mortality measure adjusts for stroke severity using the NIHSS as recommended by the clinical practice guidelines. The currently publicly reported stroke mortality measure uses administrative claims data only for risk adjustment, and does not include an assessment of stroke severity. *The stage of development for this MUC was updated to "Fully Developed" on December 3, 2015, after the MUC was publicly released.
  • Impact on quality of care for patients:There is a need to define the relevant stroke outcomes to measure and the factors that should be accounted for to make comparisons across different facilities valid so that the quality of stroke care can be evaluated and optimized. Stroke severity is the most important prognostic factor for individual patients and appears to be a significant predictor in hospital-level performance therefore inclusion in the risk model is recommended in a Statement for Healthcare Professional from the American Heart Association/American Stroke Association.
  
  
  
• Does the measure address a program goal or objective? N/A. ?This stroke mortality measure is already in the program but it uses administrative claims data only for risk adjustment and does not include an asessment of stroke severity. The proposed measure incorporates clinical data and an assessment of stroke severity into the risk adjustment model.
  
  
• Is this a high-value measure? Yes. Mortality following stroke is an important adverse outcome that can be measured reliably and objectively. The 30-day stroke mortality rate varies by age from 9 percent in patients 65-74 years of age to 23 percent in those =85 years of age [Casper ML NI, Croft JB, Nilasena DS. Atlas of Stroke Hospitalizations Among Medicare Beneficiaries. 2008]. Post-stroke mortality rates have also been shown to be influenced by critical aspects of care.CMS currently publicly reports a claims-based stroke mortality measure. The results of this measure, as reported in the 2014 update to the Hospital Compare, demonstrate a median hospital RSMR of 15.3 percent, with a range of 8.6 percent to 23.8 percent. This variation across hospitals indicates that there is room for improvement in care for stroke patients that could reduce mortality rates. Additionally, risk-adjusted 30-day mortality rates were shown to decline from 12.1 percent to 11.6 percent in Medicare FFS from 1999 to 2011 [Krumholz HM, Normand S-LT, Wang Y. Trends in Hospitalizations and Outcomes for Acute Cardiovascular Disease and Stroke: 1999-2011. Circulation. August 18, 2014.]. This decline suggests that there is opportunity for further improvement in the 30-day mortality outcome over time.
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is already in the program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure was tested at the facility level in the acute care setting.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The currently publicly reported stroke mortality measure uses administrative claims data only for risk adjustment, and does not include an assessment of stroke severity. Therefore, this new measure seeks to satisfy stakeholder preferences by incorporating clinical data and an assessment of stroke severity into the risk adjustment models, while improving discrimination of the stroke mortality risk models. This measure incorporates clinical data and an assessment of stroke severity into the risk adjustment model. It uses EHR data for risk adjustment. [Claims-Based and Hybrid Measures of 30-Day Mortality Following Acute Ischemic Stroke Hospitalization Incorporating Risk Adjustment for Stroke Severity Technical Report(Version 1.0)]
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Post-stroke mortality rates have been shown to be influenced by critical aspects of care at the hospital such as response to complications, speediness of delivery of care, organization of care, and appropriate imaging [Smith et al., 2006; Reeves et al., 2009; Lingsma et al., 2008; Hong et al., 2008; Fonarow et al., 2014]. This research demonstrates the relationship between hospital organizational factors and performance on the stroke mortality measure, and supports the ability of hospitals to impact these rates. The hybrid measure addresses a limitation of the claims-only measure by incorporating clinical data collected at the time of admission to assess the condition of the patient before care has been administered.

Measure Specifications

• NQF Number (if applicable): 2732
  
  
• Description: Percentage of adult inpatient hospital discharges to home for which the individual was on warfarin and discharged with a non-therapeutic International Normalized Ratio (INR) who had an INR test within 14 days of hospital discharge
  
  
• Numerator: Individuals in the denominator who had an INR test within 14 days of discharge
  
  
• Denominator: Adult inpatient discharges to home for which the individual had active warfarin therapy within 1 day prior to discharge and the last monitored INR within 7 days of discharge was <=1.5 or >= 4
  
  
• Exclusions: 1) Inpatient discharges for which the individuals received dabigatran, rivaroxaban, or apixaban within one day prior to discharge 2) Inpatient discharges for which the individuals are monitoring INR at home 3) Inpatient discharges for which the individuals expired within 14 days post-discharge 4) Inpatient discharges for which the individuals received hospice care within 14 days post-discharge 5) Inpatient discharges for which the individuals had a hospital inpatient admission within 14 days post-discharge 6) Inpatient discharges for which the individuals were admitted to a skilled nursing facility (SNF) within 14 days post-discharge 7) Inpatient discharges for which the end date of the 14-day follow-up period occurs after the end of the measurement period 8) Inpatient discharges for which the individual is not enrolled in Medicare Part A and Part B at the time of discharge and during the 14-day follow-up period post discharge.
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Hybrid: This measure is specified in part as an electronic clinical quality measure. Some data elements in the denominator and exclusions used to calculate the measure score are taken from the EHR. Portions of the denominator, most exclusions, and the numerator are derived from administrative claims.
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This facility level measure has been submitted to NQF for endorsement and has been reviewed and recommended by the Patient Safety Standing Committee and is currently in the voting phase. This measure addresses two gap areas identified by CMS as high-priority, adverse drug events and care transitions. This measure also compliments the VTE (NQF #0373) and stroke (NQF #0436) measures currently in the IQR program which do not assess INR after discharge. The burden of implementing this hybrid measure should be minimal because the data sources include administrative claims and EHR.
  • Impact on quality of care for patients:Implementing this measure can help to ensure a timely INR after hospital discharge and help prevent readmissions and reduce mortality associated with warfarin-related bleeding and thromboembolic events.
  
  
  
• Does the measure address a program goal or objective? No. This measure meets the “Making Care Safer” NQS Priority but it is not one of the domains identified as high-priority for future measure consideration for the hospital IQR/EHR Incentive program.
  
  
• Is this a high-value measure? Yes. According to an analysis of the Food and Drug Administration’s (FDA) Adverse Drug Event Reporting System found that warfarin ranked seventh overall in drugs identified to cause death, disability, or other serious adverse outcomes, which were defined as “hospitalization, required intervention, or life threatening or other serious outcome” [Moore, T. J., Cohen, M. R., & Furberg, C. D. (2007). Serious adverse drug events reported to the Food and Drug Administration, 1998-2005. Archives of Internal Medicine, 167(16), 1752-1759]. Performance data from seven hospitals demonstrated a performance rate of 23.3 percent to 62.7 percent, with the mean at 49.4 percent. The 90th percentile reported 62.7 percent, indicating there is room for improvement (higher rate = better care).
  
  
• Does this measure fill a gap in the program measure set? Yes. This measure fills two gap areas/topics identified by CMS as high-priority for future measure consideration: Adverse Drug Events and Care Transitions.Patients in the transition period from hospital to home are at particular risk for adverse events from medication errors in general, and for warfarin in particular, as they move from a tightly controlled environment to one with limited supervision and support [Forster, A. J., Murff, H. J., Peterson, J. F., Gandhi, T. K., & Bates, D. W. (2005). Adverse drug events occurring following hospital discharge. Journal of General Internal Medicine, 20(4), 317–323.]. A timely INR test shortly after hospital discharge is expected to lead to the stabilization of the patient’s warfarin regimen and avoidance of non-therapeutic INR levels and, therefore, result in fewer warfarin-related bleeding, thromboembolic events, and lower mortality. The 2012 American College of Chest Physicians guidelines for antithrombotic therapy and prevention of thrombosis recommend INR monitoring within 1-2 weeks for patients with a sub-therapeutic or supra-therapeutic INR [Holbrook, A., Schulman, S., Witt, D. M., Vandvik, P. O., Fish, J., Kovacs, M. J., ... & Guyatt, G. H. (2012). Evidence-based management of anticoagulant therapy: antithrombotic therapy and prevention of thrombosis: American College of Chest Physicians evidence-based clinical practice guidelines. CHEST Journal, 141(2_suppl), e152S-e184S.].
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The VTE and stroke measures currently in the IQR program assess whether a patient is discharged on overlap therapy (if needed) or on antithrombotic therapy but do not assess INR monitoring after discharge. This measure would capture all Medicare fee-for-service (FFS) beneficiaries discharged on warfarin and a non-therapeutic INR regardless of the reason the medication is prescribed (e.g. VTE vs. atrial fibrillation). The burden of implementing this hybrid measure is minimal; the data sources include EHR and administrative claims.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted
  
  

Rationale for measure provided by HHS
An analysis of the Food and Drug Administration’s (FDA) Adverse Drug Event Reporting System found that warfarin ranked seventh overall in drugs identified to cause death, disability, or other serious adverse outcomes (Moore, Cohen, & Furberg, 2007). Evidence suggests that low INR (INR < 2) is associated with an increased risk of stroke and high INR (INR > 3) is associated with increased risk of bleeding (Reynolds, 2004). A study by White et al. (2007) found that patients with poor INR control suffered higher rates of mortality and major bleeding when compared to those with good or moderate INR control. Patients in the transition period from hospital to home are at particular risk for adverse events from medication errors in general, and for warfarin in particular, as they move from a tightly controlled environment to one with limited supervision and support (Forster et al., 2005). A timely INR test shortly after hospital discharge is expected to lead to the stabilization of the patient’s warfarin regimen and avoidance of non-therapeutic INR levels and, therefore, result in fewer warfarin-related bleeding, thromboembolic events, and lower mortality. The 2012 American College of Chest Physicians guidelines for antithrombotic therapy and prevention of thrombosis recommend INR monitoring within 1-2 weeks for patients with a sub-therapeutic or supra-therapeutic INR (Holbrook et al., 2012). Three recent studies have been published on INR monitoring after hospital discharge and/or INR monitoring after an out-of-range value. In a population-based sample of Canadian patients on warfarin (Van Walraven et al., 2007), hospitalization was associated with less time in the therapeutic range, more time with INR <1.5, and more time with INR >=5.0. Qualls et al. (2013) compared patients with heart failure with and without at least one INR test within 45 days of discharge and found that those who had been tested had lower risks of mortality and myocardial infarction one year after discharge. Finally, in a study of patients in VA anticoagulation clinics (Rose et al., 2011), longer follow-up intervals for repeat tests after both INR values above and below the therapeutic range were found to be associated with worse control of anticoagulation among ambulatory patients at the clinic level. Food and Drug Administration. (2011). Warfarin (Coumadin) product labeling. Reference ID 3022954. Retrieved Oct. 16, 2013, from http://www.accessdata.fda.gov/drugsatfda_docs/label/2011/009218s107lbl.pdf Forster, A. J., Murff, H. J., Peterson, J. F., Gandhi, T. K., & Bates, D. W. (2005). Adverse drug events occurring following hospital discharge. Journal of General Internal Medicine, 20(4), 317–323. Holbrook, A., Schulman, S., Witt, D. M., Vandvik, P. O., Fish, J., Kovacs, M. J., ... & Guyatt, G. H. (2012). Evidence-based management of anticoagulant therapy: antithrombotic therapy and prevention of thrombosis: American College of Chest Physicians evidence-based clinical practice guidelines. CHEST Journal, 141(2_suppl), e152S-e184S. Moore, T. J., Cohen, M. R., & Furberg, C. D. (2007). Serious adverse drug events reported to the Food and Drug Administration, 1998-2005. Archives of Internal Medicine, 167(16), 1752-1759. Qualls, L. G., Greiner, M. A., Eapen, Z. J., Fonarow, G. C., Mills, R. M., Klaskala, W., . . . Curtis, L. H. (2013). Postdischarge international normalized ratio testing and long-term clinical outcomes of patients with heart failure receiving warfarin: Findings from the ADHERE registry linked to Medicare claims. Clinical Cardiology, 36(12), 757-765. Reynolds, M. W., Fahrbach, K., Hauch, O., Wygant, G., Estok, R., Cella, C., & Nalysnyk, L. (2004). Warfarin anticoagulation and outcomes in patients with atrial fibrillation: a systematic review and metaanalysis. CHEST Journal, 126(6), 1938-1945. Rose, A. J., Ozonoff, A., Henault, L. E., & Hylek, E. M. (2008). Warfarin for atrial fibrillation in community-based practise. Journal of Thrombosis and Haemostasis, 6(10), 1647-1654. Van Walraven, C., Austin, P. C., Oake, N., Wells, P., Mamdani, M., Forster, A. J. (2007). The effect of hospitalization on oral anticoagulation control: A population-based study. Thrombosis Research 119(6), 705–714. White, H. D., M. Gruber, Feyzi, J., Kaatz, S., Tse, H. F., Husted, S., et al. (2007). Comparison of outcomes among patients randomized to warfarin therapy according to anticoagulant control: results from SPORTIF III and V. Archives of Internal Medicine, 167(3), 239-245.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Patient Safety 2015 (Draft report available as of 9/17/15)
  
  
• Review for Importance: The measure meets the Importance criteria (1a. Evidence, 1b. Performance Gap) 1a. Evidence: 7-H; 11-M; 3-L; 0-I; 1b. Performance Gap: 7-H; 12-M; 2-L; 0-I; Rationale: · The developers provided several studies and a systematic review that support the measure specifications and its importance to measure. · There were concerns about the measures therapeutic range based on the evidence provided by the developers as well as the number of days for follow-up. · The developers show that there is a mean performance rate of about 50 percent, which indicates there is a performance gap.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria (2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity) 2a. Reliability: 3-H; 15-M; 3-L; 0-I 2b. Validity: 3-H; 12-M; 5-L; 0-I Rationale: · Seven hospitals were assessed and five of them had scores that were at the acceptable threshold for reliability. Two of the seven that had smaller sample sizes were below the specified threshold. · Validity testing was done with empirical testing at the data element and performance score measure. · 97.8% of the data elements found in the medical record correctly matched the EHR data extract received from the participating hospitals. The data element with the lowest criterion validity score (<95%) was the “discharge status” at 91.4%. · There were concerns about the patients that are readmitted or died during the follow-up period and how that would be a threat to validity. The developers noted that the onus is no longer on the hospital to do a follow-up for the first encounter once they have been readmitted and there are not enough patients who die to have a significant impact on the measure.
  
  
• Review for Feasibility: 8-H; 11-M; 1-L; 0-I (3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented) Rationale: · Data are drawn from claims and EMR and it seems to be done successfully.
  
  
• Review for Usability: 3-H; 16-M; 1-L; 0-I (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement) Rationale: · The measure is intended to be used in public reporting programs as well as internal and external quality improvement and bench marking. · There were concerns about how the measure could be applied in settings outside of those provided by the developers and level for responsibility of the provider for follow-up.
  
  
• Review for Related and Competing Measures: This measure is related to the following measures: o 0555 : INR Monitoring for Individuals on Warfarin o 0556 : INR for Individuals Taking Warfarin and Interacting Anti-Infective Medications o 0586 : Warfarin_PT/ INR Test · It is harmonized with 0555 and 0556. · Measure 0586 is potentially competing, but the Committee did not discuss this issue since 0586 is not currently under review.
  
  
• Endorsement Public Comments: Not yet available
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: 18-Y; 2-N
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Vaginal births per 1,000 deliveries by patients with previous Cesarean deliveries. Excludes deliveries with complications (abnormal presentation, preterm delivery, fetal death, multiple gestation diagnoses, or breech procedure).
  
  
• Numerator: Number of vaginal deliveries, identified by DRG or MS-DRG code, among cases meeting the inclusion and exclusion rules for the denominator. DRG codes: 372, 373, 374, 375 MS-DRG codes: 767, 768, 774, 775
  
  
• Denominator: All deliveries identified by DRG or MS-DRG code, with any-listed ICD-9-CM diagnosis codes for previous Cesarean delivery. DRG codes: 370, 371, 372, 373, 374, 375 MS-DRG codes: 765, 766, 767, 768, 774, 775
  
  
• Exclusions: Exclude cases: • with any-listed ICD-9-CM diagnosis codes for abnormal presentation, preterm, fetal death, or multiple gestation • with any-listed ICD-9-CM procedure codes for breech • with missing gender (SEX=missing), age (AGE=missing), quarter (DQTR=missing), year (YEAR=missing) or principal diagnosis (DX1=missing) See Inpatient Quality Indicators Appendices: • Appendix A – Abnormal Presentation, Preterm, Fetal Death and Multiple Gestation Diagnosis Codes • Appendix B – Breech Procedure Codes (available here: http://www.qualityindicators.ahrq.gov/Downloads/Modules/IQI/V50/TechSpecs/IQI_Appendices.pdf)
  
  
• HHS NQS Priority: Making Care Safer, Patient and Family Engagement, Communication and Care Coordination
  
  
• HHS Data Source: Administrative clinical data
  
  
• Measure Type: Outcome
  
  
• Steward: Agency for Healthcare Research & Quality
  
  
• Endorsement Status: Never Submitted
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional support, pending NQF review and endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This facility level measure is currently one of AHRQ’s IQIs and reported by multiple states. If implemented this measure will complement the elective delivery measure (NQF #0469) currently in the program.
  • Impact on quality of care for patients:Cesarean deliveries are a common surgical procedure in the United States, accounting for 1 in 3 US births. A planned labor after cesarean/vaginal birth after cesarean (LAC/VBAC) is an appropriate option for most women with a history of prior cesarean birth. Increased access to providers and facilities capable of managing LAC/VBAC are required to reduce the US cesarean rate and associated maternal morbidity while increasing choice for childbearing women and their families (http://www.annfammed.org/content/13/1/80.full).
  
  
  
• Does the measure address a program goal or objective? Yes. ?This measure addresses “Patient and Family Engagment”, one of the domains identifed by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Cesarean section is the most common operating room procedure in U.S. hospitals. Overuse of this procedure is associated with excess morbidity in women and babies [American College of Obstetricians and Gynecologists and Society for Maternal-Fetal Medicine. Safe Prevention of the Primary Cesarean Delivery. March 2014. Available at http://www.acog.org/Resources_And_Publications/Obstetric_Care_Consensus_Series/Safe_Prevention_of_the_Primary_Cesarean_Delivery] For both commercial and Medicaid payers, total maternal-newborn costs are about 50% higher for cesarean compared with vaginal births [Truven Health Analytics. The Cost of Having a Baby in the United States. Ann Arbor: Truven, January 2013. Available at http://transform.childbirthconnection.org/reports/cost ]
  
  
• Does this measure fill a gap in the program measure set? No. This measure does not address any of the gap areas/topics identifed by CMS as high-priority for future measure consideration. NQF #0469, currently in the program, assesses patients with elective vaginal deliveries or elective cesarean sections at >= 37 and < 39 weeks of gestation completed.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? Yes. The MUC is currently used by states as one of AHRQ’s quality indicators.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is already collected and reported by many states as AHRQ’s quality indicators. This measure complements NQF #0469 and provides consumers important information about hospitals that are capable of managing VBACs.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
The evidence supporting VBAC is robust and well-summarized in the ACOG and AAFP guidelines.

Measure Specifications

• NQF Number (if applicable): 2720
  
  
• Description: Assesses antimicrobial use (AU) in hospitals based on medication administration data hospitals collect electronically at the point of care and report via electronic file submissions to NHSN. AU data included in the measure are antibacterial agents administered to adult and pediatric patients in a specified set of hospital ward and intensive care unit locations.
  
  
• Numerator: Days of antimicrobial therapy for antibacterial agents administered to adult and pediatric patients in medical, medical/surgical, and surgical wards and medical, medical/surgical, and surgical intensive care units.
  
  
• Denominator: Days present for each patient care location—adult and pediatric medical, medical/surgical, and surgical wards and adult and pediatric medical, medical/surgical, and surgical intensive care units—is defined as the number of patients who were present for any portion of each day of a calendar month for each location. The day of admission, discharge, and transfer to and from locations are included in days present. All days present are summed for each location and month, and the aggregate sums for each location-month combination comprise the denominator data for the measure
  
  
• Exclusions: Hospital patient care locations other than adult and pediatric medical, medical/surgical, and surgical wards and adult and pediatric medical, medical/surgical, and surgical intensive care units are excluded from this measure.
  
  
• HHS NQS Priority: Making Care Safer, Effective Prevention and Treatment
  
  
• HHS Data Source: National Healthcare Safety Network
  
  
• Measure Type: Process
  
  
• Steward: Centers for Disease Control and Prevention
  
  
• Endorsement Status: Submitted – In the measure submission form it is stated that “The measure is being submitted for public health surveillance for quality measurement and improvement, not for public reporting or payment; the developer wishes to gain greater experience and gather more information before using it for reporting or payment. It is intended for use in the National Healthcare Safety Network.” The Patient Safety committee recommended this measure for endorsement and it is currently in the voting phase.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional support, pending additional use
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure has been submitted to NQF for endorsement. The Patient Safety Standing Committee and comments received during the public comment period expressed concerns about the reliability and validity of the measure due to the small sample size used to conduct the initial analysis. In the submission, the measure developer stated that the measure is intended for use in the National Healthcare Safety Network (NHSN) and wishes to gain greater experience and gather more information before using it for reporting or payment. MAP recognizes the high importance of antimicrobial stewardship and would conditionally support the inclusion of this measure in the IQR program to allow for the opportunity for additional testing to address feasibility issues. However, MAP notes these issues should be addressed before the measure is reported on Hospital Compare.
  • Impact on quality of care for patients:The measure provides summary results that hospital and health system antimicrobial stewardship programs (ASPs) can use as quantitative aids in their efforts to evaluate and improve antibiotic prescribing.
  
  
  
• Does the measure address a program goal or objective? No. This measure does not address any of the domains identified by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Numerous individual studies and systematic reviews provide strong evidence that measurement of antimicrobial use and datadriven interventions by antimicrobial stewardship programs (ASPs) lead to more judicious use of antibiotics, reduced antimicrobial resistance, and other favorable healthcare outcomes (Feazel 2014; Davey 2006; Davey 2013; Kaki 2011).Antimicrobial use measurement enables ASPs to understand prescribing practices, focus efforts on improvement, and determine the impact of their activities (Pollack, 2014). Although standardized metrics have been developed to measure antibiotic use, differences in measurement, limited uptake, and variation among facilities has impeded the ability to compare antibiotic use among hospitals.Feazel LM, Malhotra A, Perencevich EN, Kaboli P, Diekema DJ, Schweizer ML. Effect of antibiotic stewardship programmes on Clostridium difficile incidence: a systematic review and meta-analysis. J Antimicrob Chemother. 2014;69(7):1748-54.http://jac.oxfordjournals.org/content/69/7/1748.full.pdf Davey P, Brown E, Fenelon L, Finch R, Gould I, Holmes A, et al. Systematic review of antimicrobial drug prescribing in hospitals.Emerg Infect Dis. 2006;12(2):211-6. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3373108/ Davey P, Brown E, Charani E, Fenelon L, Gould IM, Holmes A, et al. Interventions to improve antibiotic prescribing practices for hospital inpatients. Cochrane Database Syst Rev. 2013;4:CD003543.http://onlinelibrary.wiley.com/store/10.1002/14651858.CD003543.pub3/asset/CD003543.pdf?v=1&t=hvxzajv5&s=a6f3c724ce051d8acba5866a07e3c5ac8c818e83 Kaki R, Elligsen M, Walker S, Simor A, Palmay L, Daneman N. Impact of antimicrobial stewardship in critical care: a systematic review. J Antimicrob Chemother. 2011;66(6):1223-30. http://jac.oxfordjournals.org/content/66/6/1223.full.pdf Pollack LA, Srinivasan A. Core Elements of Hospital Antibiotic Stewardship Programs from the Centers for Disease Control and Prevention. Clinical Infectious Diseases. 2014;59(suppl 3):S97-S100 .
  
  
• Does this measure fill a gap in the program measure set? No. This measure does not address any of the high-priority measurement gaps identified by CMS.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level. However, the Patient Safety Standing Committee and public comments received expressed concern about the small data sample and suggested additional reliability and validity testing.
  
  
• Is the measure currently in use? Yes. According to the measure developer’s response to comments received during the commenting phase of the Patient Safety project, in 2014, this measure was reported to CDC’s National Healthcare Safety Network (NHSN) by 60 U.S. hospitals including acute care hospitals, critical access hospitals, children’s hospitals, and an oncology hospital for public health/disease surveillance and quality improvement with benchmarking.
  
  
• Does a review of its performance history raise any concerns? Yes. Comments received during the public comment period included concerns that the measure has feasibility issues, noting that standardized EMR guidance would be needed, as well as significant lead time to ensure that facilities have the necessary data mining capabilities. Additional concerns were raised about the selection of some of the drugs used in the measure. Commenters also raised concerns with the difference between utilization and appropriateness, noting that appropriateness incorporates many factors that were not fully accounted for, including geography, seasonal variation, prevalence, and patient mix, all of which could affect predicted use. Commenters noted the need for risk adjustment for cancer and transplant patients and the importance of controlling for differences between types of hospitals and the complexity of their patient population. One comment was particularly concerned with the pediatric population, noting that it is more complex than the adult population, and that the pediatric sample size was extremely small; they suggested further testing. Lastly, a commenter suggested this measure be expanded to include antifungal agents.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is not duplicative of an existing measure and the data is collected from EHRs and submitted to the CDC’s NHSN.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Submitted – In the measure submission form it is stated that “The measure is being submitted for public health surveillance for quality measurement and improvement, not for public reporting or payment; the developer wishes to gain greater experience and gather more information before using it for reporting or payment. It is intended for use in the National Healthcare Safety Network.” The Patient Safety committee recommended this measure for endorsement and it is currently in the voting phase.
  
  

Rationale for measure provided by HHS
Numerous individual studies and systematic reviews provide strong evidence that measurement of antimicrobial use and data-driven interventions by antimicrobial stewardship programs (ASPs) lead to more judicious use of antibiotics, reduced antimicrobial resistance, and other favorable healthcare outcomes (Feazel 2014; Davey 2006; Davey 2013; Kaki 2011). Antimicrobial use measurement enables ASPs to understand prescribing practices, focus efforts on improvement, and determine the impact of their activities (Pollack, 2014). Although standardized metrics have been developed to measure antibiotic use, differences in measurement, limited uptake, and variation among facilities has impeded the ability to compare antibiotic use among hospitals. The measure will serve as a quantitative guide for hospital and health system ASPs, enabling them to benchmark antibiotic use in their facilities and patient care locations against nationally aggregated data. The measure focuses on antibiotic agents that have been shown to be high value targets for antimicrobial stewardship programs activities such as protocols for use or post-prescription reviews to determine need for de-escalation, dose-optimization or oral conversion. Knowledge about antibiotic use patterns of these agents is a primary means to prioritize and evaluate antimicrobial stewardship efforts.

Measure Specifications

• NQF Number (if applicable): 531
  
  
• Description: Patient Safety and Adverse Events Composite (Patient Safety Indicator, or PSI90) is a composite measure of 10 individual PSIs, each measuring a different aspect of harm associated with patient safety. Each PSI is reliability-adjusted (smoothed) and indirectly standardized (risk adjusted). The composite is the weighted average of the reliability-adjusted, indirectly standardized, observed-to-expected ratios for component indicators. The final weight for each component is the product of harm weights and volume weights (numerator weights). Harm weights are calculated by multiplying empirical estimates of excess harms associated with the patient safety event by utility weights linked to each of the harms. Excess harms are estimated using statistical models comparing patients with a safety-related event to those without that safety-related event in a CMS Medicare fee-for-service sample that allowed up to one year of follow-up from the discharge date of the hospital stay associated with the index event. Volume weights, the second part of the final weight, are calculated on the basis of the number of safety-related events for the component indicators in the all-payer reference population. The observed to expected ratios (indirect standardization) of the reliability adjusted (smoothed) rates are multiplied by a component weight and the weighted scores are summed to determine the final PSI 90 score. A score of 1 means that the hospital performs as expected, scores greater than one indicate worse performance than expected.
  
  
• Numerator: Below we list the numerator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for pressure ulcer and any secondary ICD-9-CM diagnosis codes for pressure ulcer stage III or IV (or unstageable). PSI06-Iatrogenic Pneumothorax Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for iatrogenic pneumothorax. PSI08-Postoperative Hip Fracture Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for hip fracture. PSI09-Perioperative Hemorrhage and Hematoma Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for perioperative hemorrhage or hematoma and any-listed ICD-9-CM procedure codes for control of perioperative hemorrhage or evacuation of hematoma. PSI10-Postoperative Acute Kidney Injury Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for acute renal failure and any-listed ICD-9- CM procedure codes for dialysis. PSI11-Postoperative Respiratory Failure Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis code for acute respiratory failure; or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for 96 consecutive hours or more that occurs zero or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for less than 96 consecutive hours (or undetermined) that occurs two or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a reintubation that occurs one or more days after the first major operating room procedure code (based on days from admission to procedure). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with a secondary ICD-9-CM diagnosis code for deep vein thrombosis or a secondary ICD-9-CM diagnosis code for pulmonary embolism (omitting cases from the numerator with isolated calf vein DVT). PSI13-Postoperative Sepsis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for sepsis. PSI14-Postoperative Wound Dehiscence Rate-Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any-listed ICD-9-CM procedure codes for reclosure of postoperative disruption of the abdominal wall. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate -Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for accidental puncture or laceration during a procedure and second abdominopelvic operation 1 day or more after the index procedure.
  
  
• Denominator: Below we list the denominator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI06-Iatrogenic Pneumothorax Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI08-Postoperative Hip Fracture Rate- Surgical discharges, ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI09-Perioperative Hemorrhage and Hematoma Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI10-Postoperative Acute Kidney Injury Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI11-Postoperative Respiratory Failure Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI13-Postoperative Sepsis Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI14-Postoperative Wound Dehiscence Rate- Discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for abdominopelvic surgery. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate- Patients ages 18 years and older with any procedure code for an abdominopelvic procedure.
  
  
• Exclusions: Below we list the exclusions for the composite components. There are no additional exclusions for the composite measure as a whole. PSI03 – Pressure Ulcer Rate-Excludes cases with length of stay less than 5 days, with a principal diagnosis of pressure ulcer or secondary diagnosis of pressure ulcer present on admission, cases with evidence of hemiplegia, paraplegia or quadriplegia, spina bifida, anoxic brain damage, debridement or pedicle graft on the same day as the major operating room surgery or as the only major operating room procedure, and cases that were transferred from a different hospital or skilled nursing facility, and cases with MDC (major diagnostic classification) of 9 (skin, subcutaneous and breast) or 14 (pregnancy, childbirth and puerperium). PSI06 – Iatrogenic Pneumothorax Rate - Excludes cases with a principal diagnosis for iatrogenic pneumothorax or secondary diagnosis of iatrogenic pneumothorax on admission, cases with evidence of chest trauma, pleural effusion, thoracic surgery, lung or pleural biopsy, diaphragmatic repair, cardiac procedure, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI08 – Postoperative Hip Fracture Rate-Excludes cases with principal diagnosis of hip fracture or a secondary diagnosis of hip fracture on admission, cases where the only operating room procedure is hip fracture, where the procedure for hip fracture occurs before or on the same day as the first operating room procedure, and cases with a principal diagnosis of seizure, syncope, stroke and occlusion of arteries, coma, cardiac arrest, poisoning, trauma, delirium and other psychoses, anoxic brain injury, metastatic cancer, lymphoid malignancy, bone malignancy, self-inflicted injury, and cases with MDC (major diagnostic classification) of 8 (musculoskeletal system and connective tissue) or 14 (pregnancy, childbirth and puerperium). PSI09 – Perioperative Hemorrhage and Hematoma Rate - Excludes cases with principal diagnosis of perioperative hemorrhage or postoperative hematoma or secondary diagnosis present of perioperative hemorrhage on admission, cases where the only operating room procedure is control of postoperative hemorrhage, drainage of hematoma or miscellaneous hemorrhage- or hematoma-related procedure, any secondary diagnosis of perioperative hemorrhage or postoperative hematoma and any-listed procedure codes for control of perioperative hemorrhage or evacuation of hematoma or miscellaneous hemorrhage- or hematoma- related procedure occurring before the first operating room procedure, cases with diagnosis of coagulation disorder and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI10 – Postoperative Acute Kidney Injury-Excludes cases with a principal diagnosis or secondary diagnosis on admission of acute renal failure, acute myocardial infarction, cardiac arrhythmia, cardiac arrest, shock, hemorrhage, gastrointestinal hemorrhage, or chronic renal failure, cases with dialysis procedure before on the same day as the first operating procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI11 – Postoperative Respiratory Failure Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of acute respiratory failure, cases where the only operating procedure is tracheostomy or a tracheostomy occurs before the first operating procedure, cases with any listed diagnosis of neuromuscular disorder, craniofacial anomalies or degenerative neurological disorder, cases with any listed procedure of laryngeal or pharyngeal, nose, mouth, or pharynx surgery, procedures involving the face, esophageal resection, procedures for lung cancer, and cases with MDC (major diagnostic classification) of 4 (disease of respiratory system), 5 (diseases of the circulatory system), or 14 (pregnancy, childbirth and puerperium). PSI12 – Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of DVT, pulmonary embolism, cases where a procedure for interruption of vena cava occurs before or on the same day as the first operating room procedure, cases with any procedure for extracorporeal membrane oxygenation, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI13 – Postoperative Sepsis Rate – Excludes cases with principal diagnosis or secondary diagnosis on admission of sepsis, infection, cases with evidence of immunocompromised state or cancer, cases with a length of stay less than 4 days, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI14 – Postoperative Wound Dehiscence Rate – Excludes cases with any listed evidence of immunocompromised state, cases where the procedure for abdominal wall reclosure occurs on or before the day of the first abdominopelvic surgery procedure, cases with a length of stay less than 2 days, and cases with MDC(major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI15 – Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate-Excludes cases with a principal diagnosis or secondary diagnosis at admission of accidental puncture or laceration during a procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium).
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Administrative claims Component measures require: ICD-9 diagnosis and procedure codes, MDC, MSDRG, procedure day, age in year, gender, admission type, discharge disposition. All are drawn from administrative data.
  
  
• Measure Type: Composite
  
  
• Steward: Agency for Healthcare Research & Quality
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes.
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This updated version of PSI 90 addresses a number of concerns raised by the NQF Safety Standing Committee. Three additional PSIs have been added to the measure. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable. PSIs were better linked to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication. This is intended to allow the measure to more accurately reflect the impact of the events.
  • Impact on quality of care for patients:The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges. The composite measure was constructed to increase the statistical precision by increasing the sample size and to assist consumers, providers, and payers with their decision-making. This updated version would three additional PSIs: PSI09 Postoperative Hemorrhage or Hematoma, PSI10 Physiologic and Metabolic Derangement, and PSI11 Postoperative Respiratory Failure.
  
  
  
• Does the measure address a program goal or objective? N/A. This measure is currently in the program and is undergoing substantial changes.
  
  
• Is this a high-value measure? Yes. This is an outcome measure addressing patient safety. The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges.
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently used in several hospital programs and is undergoing substantial changes.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level in the acute care setting.
  
  
• Is the measure currently in use? Yes. The measure is currently in the following hospital programs: Hospital Acquired Condition Reduction Program (FY 2015 – current); Hospital Inpatient Quality Reporting (2012- current); Hospital Value-Based Purchasing (2015-current)
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The data for this outcome measure is based on readily available administrative billing and claims data and U.S. Census data.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed; MUC same as endorsed version:Yes.
  
  

Rationale for measure provided by HHS
Each measure used within the PSI 90 composite is an outcome measure that has been shown to be largely preventable through improved structures and processes of care. Each measure has an evidence review form as part of the NQF endorsement process. The literature to support each measure is updated on a schedule basis.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Patient Safety 2015
  
  
• Review for Importance: The measure meets the Importance criteria (1a. Evidence, 1b. Performance Gap) 1a. Evidence: 16-Y; 8-N I; 1b. Performance Gap: 9-H; 9-M; 6-L; 0-I; 1c. Composite- Quality Construct and Rationale: 6-H; 7-M; 11-L; 0-I Rationale: · The Committee agreed that the outcomes in this measure were associated with one or more healthcare actions. However, there was concern that some of the elements of the composite had variable preventability. · The developers reported that the items within the composite are positively correlated. The correlations range in the low 0.08 up to the 30s (not very high). · The developers referenced several processes of care that are associated with lower rates for each of the components in the composite.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria (2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity) 2a. Reliability: 4-H; 10-M; 9-L; 1-I 2b. Validity: 2-H; 11-M; 7-L; 2-I 1c. Composite Construction: 4-H; 12-M; 7-L; 1-I Rationale: · The Committee agreed that the updated version of the measure provided by AHRQ was improved from the 2014 version reviewed by the Committee, specifically noting that the new weighting focusing on harm rather than just the frequency of events, was more clinically relevant than the previous version of the measure. · During reliability testing, the developers examined the true difference rather than random chance and noise. Their results show a reliability scores in the 70s, which is comparable to other endorsed measures · Aggregating a number of individual measures into a single composite can generate an overall performance score that is more reliable than if the individual measure scores were taken in isolation. · Empirical field validity testing was conducted at the performance measure score level for the overall composite by correlating the composite scores with the rates calculated from the 3M Potentially Preventable Readmissions measure. .The Pearson correlation value, was 0.11 with a p-value of <0.0001.
  
  
• Review for Feasibility: 12-H; 8-M; 3-L; 1-I (3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented) Rationale: · The Committee had no concerns about the feasibility of this measure given that it is gathered with administrative claims data.
  
  
• Review for Usability: 12-H; 6-M; 6-L; 0-I (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement) Rationale: · There were concerns about the use of this measure in value-based purchasing, despite the improvements the developer has made, because may not accurately reflect that an actual preventable complication occurred or may focus on preventing measured events that are less clinically important. · This measure is used to monitor performance in national and regional reporting. It was also developed to enable comparative reporting and quality improvement at the provider or the hospital level.
  
  
• Review for Related and Competing Measures: Concerns were raised by the Committee that some of the elements of this measure, notably the central line related blood stream infections and post-operative hip fracture, may be better captured in other NQF approved measures rather than using administrative claims data. In addition, this measure is related to NQF 532, which is the pediatric version of the same measure 0347.
  
  
• Endorsement Public Comments: Summary pending
  
  
• Endorsement Committee Recommendation: 14-Y; 10-N

  Since 58% of the Committee voted to recommend this measure, it did not achieve consensus. It will move forward to the comment period and the Committee will discuss and revote after the public comment.

  This measure was last endorsed in 2009; it is a composite measure of 11 inpatient Patient Safety Indicators. In 2014 the Committee raised concerns about the weighting of the various components of the composite, specificially that some of the more heavily weighted components were less clinically significant (i.e., accidental punctures and lacerations) and/or less preventable. In addition, there were concerns that the events measured are not always reflective of an actual patient safety event that resulted in preventable patient harm. To address the concerns of the 2014 Committee, AHRQ made several updates to the measure to address the Committee’s concerns.

  1. Additional PSIs were included (from 8 events to 11 events, which expanded the type of complications included this measure),
  2. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable, and
  3. The measure was modified to more accurately reflect the impact of the events by better linking the PSIs to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication.

  The Committee agreed that the changes to the measure were highly responsive to the concerns raised during the 2014 Committee discussion. However, new concerns were raised: some post-operative DVT or other events included in the composite may not be preventable; the definition of ICD-9 based central line related blood stream infections may be less precise than other definitions (i.e., NHSN which reports the information differently); and concerns about this measure being included in value-based purchasing programs particularly when it is likely that not all of these events are preventable and that it may distract from efforts to reduce more impactful safety events. In addition, there were concerns that some of the indicators of the measure may not reflect preventable patient safety events because it comes from ICD-9 data of inpatient complications, which sometimes did not directly reflect that an actual preventable complication occurred in the validation of the components of the composite. During the vote, the Committee agreed that the measure meets the four NQF criteria; however, consensus was not reached on a recommendation for endorsement (58% yes, 42% no). The Committee will re-consider the recommendation for endorsement after reviewing the public comments.
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a Spinal Fusion IP stay and attributes them to the hospital where the index IP stay occurred.
  
  
• Numerator: The numerator of the Spinal Fusion Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to spinal fusions across a hospital’s eligible Spinal Fusion episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure does not address any of the high-priority domains identified by CMS for future measure consideration. Analytic evidence demonstrating that a performance gap exists or that there is a variation in performance among providers for spinal fusion procedures was not provided as required for measures that may be considered for potential adoption in the IQR program. Furthermore, a similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program and captures a broader population than the MUC, which is procedure specific. *The stage of development for this MUC was updated to "Fully Developed" on December 2, 2015, after the MUC was publicly released.
  • Impact on quality of care for patients:Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
  
• Does the measure address a program goal or objective? No. ?This measure does not address any of the domains identified by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406.
  
  
• Does this measure fill a gap in the program measure set? No. Analytic evidence not provided demonstrating that a performance gap exists or that there is a variation in performance among providers for aortic aneurysm procedures.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No. This measure is in early development.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC which is procedure specific.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a TURP IP stay and attributes them to the hospital where the index IP stay occurred.
  
  
• Numerator: The numerator of the TURP Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to the TURPs across a hospital’s eligible TURP episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure does not address any of the high-priority domains identified by CMS for future measure consideration. Analytic evidence demonstrating that a performance gap exists or that there is a variation in performance among providers for transurethral resection of the prostate (TURP) for benign prostatic hyperplasia procedures was not provided as required for measures that may be considered for potential adoption in the IQR program. Furthermore, a similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program and captures a broader population than the MUC, which is procedure specific.
  • Impact on quality of care for patients:Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406).
  
  
  
• Does the measure address a program goal or objective? No. ?This measure does not address any of the domains identified by CMS as high-priority for future measure consideration.
  
  
• Is this a high-value measure? Yes. Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406.
  
  
• Does this measure fill a gap in the program measure set? No. Analytic evidence not provided demonstrating that a performance gap exists or that there is a variation in performance among providers for aortic aneurysm procedures.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. This measure is tested at the facility level.
  
  
• Is the measure currently in use? No. This is a new measure.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC which is procedure specific.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., .Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Measure estimates risk-adjusted rates of inpatient admissions or emergency department (ED) visits for cancer patients >18 years of age with at least one of the following diagnoses—anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, or sepsis—within 30 days of hospital outpatient chemotherapy treatment. Two rates are reported.
  
  
• Numerator: The outcomes for this measure are one or more inpatient admissions or one or more emergency department (ED) visits for one of the following diagnoses—anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, or sepsis—within 30 days among cancer patients receiving a hospital outpatient chemotherapy treatment. Qualifying diagnosis on the admission or ED visit claim must be listed as (1) the primary diagnosis or (2) a secondary diagnosis accompanied by a primary diagnosis of cancer. Outcomes are identified separately for the inpatient and ED categories. A patient can only qualify for an outcome once. Patients who experience both an inpatient admission and an ED visit during the measurement period are counted towards the inpatient admission outcome. Among those with no qualifying inpatient admissions, qualifying ED visits will be counted. Outcome Attribution: The outcome is attributed to the hospital outpatient facility where the patient received chemotherapy treatment during the 30 days prior to the outcome.
  
  
• Denominator: The measure cohort includes Medicare Fee-for-Service (FFS) patients aged 18 years and older as of the start of the measurement period with a diagnosis of any cancer (except leukemia) who received at least one hospital outpatient chemotherapy treatment at the reporting facility during the measurement period.
  
  
• Exclusions: 1) Patients with a diagnosis of leukemia at any time during the measurement period. 2) Patients who were not enrolled in Medicare FFS Parts A and B in the year prior to the first outpatient chemotherapy treatment during the measurement period. 3) Patients who received chemotherapy treatments for whom Medicare FFS Parts A and B enrollment is not maintained for the 30-days following treatment for at least one chemotherapy treatment during the measurement period.
  
  
• HHS NQS Priority: Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Claims
  
  
• 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: Conditional Support, pending NQF endorsement.
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure fits in a high-priority domain and would be the first hospital admissions measure in the OQR set, which would align OQR with other measure sets that include admissions and readmissions measures, including ASCQR and HRRP. This measure would also help expand cancer quality measurement to the Hospital Outpatient setting. The measure has not been submitted for endorsement to NQF. This measure was conditionally supported by the MAP in 2014 for use in the PCHQR program, pending NQF endorsement.
  • Impact on quality of care for patients:According to research by the measure developer, nearly 20% of chemotherapy patients are affected by potentially preventable adverse events that are so severe they require a hospital admission of ED visit. Incentivizing HODs to better manage chemotherapy complications should reduce burden on patients and lower cost for payers.
  
  
  
• Does the measure address a program goal or objective? Yes. The measure addresses Communication/Care Coordination ( part c, ‘measures to reduce unexpected hospital/emergency visits and admissions’), a priority domain identified by CMS.
  
  
• Is this a high-value measure? Yes. Outcome measure: included diagnoses for inpatient admission are significant adverse events (e.g. pneumonia, sepsis) that may be due to outpatient chemotherapy patients having significant unmet needs that contribute to a hospital admission or ED visit. Analysis of the measure suggests approximately 18% of the denominator experiences either a hospital admission or ED visit following outpatient chemotherapy treatment, with a range of performance across hospitals. However, performance information supplied is limited to the mean and upper and lower bounds (100 and 0). Other distribution information (e.g. deciles or quartiles information) would be helpful.
  
  
• Does this measure fill a gap in the program measure set? Yes. No measures in the set track unplanned admissions or ED visits following a procedure, a high-priority domain identified by CMS. Additionally, the Hospital Workgroup has previously noted its desire to see measures addressing quality of care for cancer in the OQR measure set.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested at the Hospital Outpatient Department setting; facility level of analysis.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is harmonized with other, similar measures, by excluding planned visits, and capturing 30 days from the date of the procedure. This measure was conditionally supported by the MAP in 2014 for use in the PCHQR program, pending NQF endorsement. There are no other unplanned hospital admissions measures in the OQR measure set. The measure is entirely derived from Medicare FFS claims data, and unlikely to be burdensome to calculate.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  

Rationale for measure provided by HHS
Cancer patients receiving chemotherapy have much higher rates of admissions and ED use than other patients. A study of 2007 commercial claims data for more than 14 million patients found that cancer patients average one admission per year; 40 percent of those admissions were chemotherapy related (Kolodziej et al. 2011). The authors also found that cancer patients average approximately two ED visits per year, about half of which were chemotherapy related. Common complications of chemotherapy treatment include nausea, emesis, anemia, neutropenic fever, diarrhea, dehydration, and pain (Burton et al. 2007; Crawford et al. 2004; Groopman and Itri 2000; Osoba et al. 1997; Richardson and Dobish 2007; Stein et al. 2010). Chemotherapy-related admissions and ED visits may be due to outpatient chemotherapy patients having unmet needs and gaps in care, which, if addressed, could reduce admissions and ED visits and increase patients’ quality of life (Hassett et al. 2006; Mayer et al. 2011; McKenzie et al. 2011). Although it is extremely unlikely that all admissions and ED visits related to chemotherapy can be avoided by prevention and treatment of side effects and complications, there is evidence and consensus among providers on ways to prevent and treat each of the symptoms included in the numerator of this measure. Measurement of admissions and ED visits for patients receiving outpatient chemotherapy should encourage reporting facilities to take steps to prevent and improve management of side effects and complications from treatment. Poor performance on the measure would reflect high resource use and significant consequences for patient/society due to poor quality; admissions and ED visits are costly to payers and reduce quality of life for patients. Burton, A.W., G.J. Fanciullo, R.D. Beasley, and M.J. Fisch. “Chronic Pain in the Cancer Survivor: A New Frontier”. Pain Medicine, vol. 8, 2007, pp. 189–198. Crawford, J.C., D.C. Dale, and G.H. Lyman. “Chemotherapy-Induced Neutropenia.” Cancer, vol. 15, 2004, pp. 228–237. Groopman, J.E., and L.M. Itri. “Chemotherapy-Induced Anemia in Adults: Incidence and Treatment.” Journal of the National Cancer Institute, vol. 91, 2000, pp. 1616–1634. Hassett, M.J., J. O’Malley, J.R. Pakes, J.P. Newhouse, and C.C. Earle. “Frequency and Cost of Chemotherapy-Related Serious Adverse Effects in a Population Sample of Women with Breast Cancer.” Journal of the National Cancer Institute, vol. 98, no. 16, 2006, pp. 1108–1117. Kolodziej, M., J.R. Hoverman, J.S. Garey, J. Espirito, S. Sheth, A. Ginsburg, M.A. Neubauer, D. Patt, B. Brooks, C. White, M. Sitarik, R. Anderson, and R. Beveridge. “Benchmarks for Value in Cancer Care: An Analysis of a Large Commercial Population.” Journal of Oncology Practice, vol. 7, 2011, pp. 301–306. Mayer, D.K., D. Travers, A. Wyss, A. Leak, A. Waller. “Why Do Patients with Cancer Visit Emergency Departments? Results of a 2008 Population Study in North Carolina.” Journal of Clinical Oncology, vol. 26, no. 19, 2011, pp. 2683–2688. McKenzie, H., L. Hayes, K. White, K. Cox, J. Fethney, M. Boughton, and J. Dunn. “Chemotherapy Outpatients’ Unplanned Presentations to Hospital: A Retrospective Study.” Support Care Cancer, vol. 19, 2011, pp. 963–969. Osoba, D., B. Zee, D. Warr, J. Latreilee, L. Kaizer, and J. Pater. “Effect of Postchemotherapy Nausea and Vomiting on Health-Related Quality of Life.” Support Care Cancer, vol. 5, 1997, pp. 307–313. Richardson, G., and R. Dobish. “Chemotherapy Induced Diarrhea.” Journal of Oncology Pharmacy Practice, vol. 13, no.4, 2007, pp. 181–98. Stein, A., W. Voigt, and K. Jordan. “Chemotherapy-Induced Diarrhea: Pathophysiology, Frequency, and Guideline-Based Management.” Therapeutic Advances Medical Oncology, vol. 2, 2010, pp. 51–63.

Measure Specifications

• NQF Number (if applicable): 2687
  
  
• Description: The measure score is a hospital-level, post-surgical risk-standardized hospital visit (RSHV) ratio, which is a ratio of the predicted to expected number of all-cause, unplanned hospital visits within 7 days of a same-day surgery at a hospital outpatient department (HOPD) among Medicare fee-for-service (FFS) patients aged 65 years and older. (The endorsed specifications of the measure are: Facility-level, post-surgical risk-standardized hospital visit ratio (RSHVR) of the predicted to expected number of all-cause, unplanned hospital visits within 7 days of a same-day surgery at a hospital outpatient department (HOPD) among Medicare fee-for-service (FFS) patients aged 65 years and older.)
  
  
• Numerator: This is a risk-standardized outcome measure, so we use this field to describe the outcome (not the numerator of the measure score). The outcome is all-cause, unplanned hospital visits, defined as 1) an inpatient admission directly after the surgery or 2) an unplanned hospital visit post discharge (emergency department [ED] visit, observation stay, or unplanned inpatient admission) occurring after discharge and within 7 days of the surgical procedure. If more than one unplanned hospital visit occurs, only the first hospital visit within the outcome timeframe is counted in the outcome. (The endorsed specifications of the measure are: The outcome is all-cause, unplanned hospital visits, defined as 1) an inpatient admission directly after the surgery or 2) an unplanned hospital visit (emergency department [ED] visit, observation stay, or unplanned inpatient admission) occurring after discharge and within 7 days of the surgical procedure.)
  
  
• Denominator: Outpatient same-day surgeries performed at HOPDs for Medicare FFS patients aged 65 years and older.(The endorsed specifications of the measure are: Outpatient same-day surgeries performed at HOPDs for Medicare FFS patients aged 65 years and older with the exception of eye surgeries and same day surgeries performed concurrently with high-risk procedures.)
  
  
• Exclusions: The measure excludes: • Surgeries for patients without continuous enrollment in Medicare FFS Parts A and B in the 1 month after the surgery, to ensure all patients have full data for outcome assessment.(The endorsed specifications of the measure are: The measure excludes surgeries for patients without continuous enrollment in Medicare FFS Parts A and B in the 1 month after the surgery. The measure excludes these patients to ensure all patients have full data available for outcome assessment. The exclusion prevents unfair distortion of performance results. The measure excludes surgeries for patients without continuous enrollment in Medicare FFS Parts A and B in the 1 month after the surgery.)
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination
  
  
• HHS Data Source: Claims, Other; Measure also uses CMS enrollment database (EDB) for demographics and FFS enrollment information.
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: As of 9/3/2015
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure addresses a OQR priority domain by adding the first measure of hospital admissions to the OQR measure set. Adding this measure would align OQR with other CMS programs addressing similar settings including ASCQR. This measure has been fully specified and tested, and is endorsed by the National Quality Forum.
  • Impact on quality of care for patients:This measure directly assesses variations in patient outcomes following surgery at a HOPD. Hospital admissions are costly for payers and burdensome to patients, and there is a broad effort across federal programs to reduce excess admissions. The literature finds significant room for improvement in HOPDs: up to 40% of direct admissions after outpatient surgery are preventable.
  
  
  
• Does the measure address a program goal or objective? Yes. The measure addresses Communication/Care Coordination ( part c, ‘measures to reduce unexpected hospital/emergency visits and admissions’), a priority domain identified by CMS.
  
  
• Is this a high-value measure? Yes. Outcome measure. Hospital admissions are costly and deliterious to the patient. 40-60% of hospital admissions following outpatient surgeries are due to adverse effects of the surgery or other serious medical problems (e.g. chest pain). In an analysis of over 200,000 outpatient surgeries, the measure developers found high-performing (>95%) HOPDs had 24% fewer than expected hospital visits, and low-performing (>5%) had at least 34% more hospital visits than expected.Up to 40% of direct admissions after outpatient surgery have been found to be preventable (Awan FN, Zulkifli MS, McCormack O, et al. Factors involved in unplanned admissions from general surgical day-care in a modern protected facility. Irish medical journal. May 2013;106(5):153-154.)
  
  
• Does this measure fill a gap in the program measure set? Yes. No measures in the set track unplanned admissions to a hospital following a procedure, a high-priority domain identified by CMS.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested at Hospital Outpatient Department. Moderate reliability. Only ‘moderate’ reliability was cited as problematic in public comments on the measure during the NQF endorsement process.12 of 13 TEP members agreed that the measure can distinguish better and worse quality facilities, as part of a face validity analysis.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. The Ambulatory Surgical Center Quality Reporting Program includes a similar measure of hospital admissions following discharge from the ASC. The seven-day limit is justified by existing literature and analysis of the measure data, finding that the vast majority of adverse events occur within the first seven days after surgery.This measure is harmonized with other, similar measures, by excluding planned visits, and for being risk-adjusted to evaluate a HOPD’s rate of admissions relative to expectations based on case mix. There are no other hospital admissions measures in the OQR measure set. The measure is entirely derived from Medicare FFS claims data, and unlikely to be burdensome to calculate.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. As of 9/3/2015
  
  

Rationale for measure provided by HHS
Nearly 70% of all surgeries in the US are now performed in the outpatient setting with most performed as same-day surgeries at HOPDs.[1] While most outpatient surgery is safe, there are well-described and potentially preventable adverse events that occur after outpatient surgery, such as uncontrolled pain, urinary retention, infection, bleeding, and venous thromboembolism, which can result in unanticipated hospital visits. Similarly, direct admissions after surgery that are primarily caused by non-clinical patient considerations, such as lack of transport home upon discharge, or hospital logical issues, such as delayed start of surgery, are common causes of unanticipated yet preventable hospital admissions following same-day surgery. Hospital utilization following same-day surgery is an important and accepted patient-centered outcome reported in the literature. National estimates of hospital visit rates following surgery vary from 0.5-9.0% based on the type of surgery, outcome measured (admissions alone or admissions and emergency department [ED] visits), and timeframe for measurement after surgery.[2-9] Furthermore, hospital visit rates vary among HOPDs,[7] suggesting variation in surgical and discharge care quality. However, providers (HOPDs and surgeons) are often unaware of their patients’ hospital visits after surgery since patients often present to the ED or to different hospitals.[10] Therefore, a quality measure of hospital visits following outpatient same-day surgery can improve transparency, inform patients and providers, and foster quality improvement. The literature suggests 1.3-13.6% of outpatient surgeries at HOPDs result in an inpatient admission with the admission rate varying by type of surgery and HOPD case mix.[3,7-9,11-21] Of these admissions, 40-60% are reported to be due to adverse effects of the surgery, anesthesia, or due to other suspected medical problems such as chest pain.[3,7-9,11-21] A smaller proportion of admissions are due to non-clinical reasons such as lack of transport home or logistical issues such as delayed start of surgery.[3,7-9,11-19] When specifically assessed, up to 40% of direct admissions after outpatient surgery have been found to be preventable.[19] Major and minor adverse events, such as uncontrolled pain, urinary retention, infection, bleeding, and venous thromboembolism, are well documented to occur post-discharge and result in unanticipated hospital visits.[12,13,22] Some hospital visits post-discharge are for scheduled follow-up care provided after surgery (e.g., visits for rehabilitation). We remove these ‘planned’ hospital visits from the outcome. We limit the outcome of hospital visits to 7 days since existing literature suggests the vast majority of adverse events after surgery occur within the first 7 days following the surgery.[4,12] We observed in our own data the highest rates of hospital visits occurring within 7 days of surgery. References: 1. Cullen KA, Hall MJ, Golosinskiy A. Ambulatory surgery in the United States, 2006. National health statistics reports. Jan 28 2009(11):1-25. 2. Majholm B, Engbaek J, Bartholdy J, et al. Is day surgery safe? A Danish multicentre study of morbidity after 57,709 day surgery procedures. Acta anaesthesiologica Scandinavica. Mar 2012;56(3):323-331. 3. Linares-Gil MJ, Pelegri-Isanta MD, Pi-Siqués F, Amat-Rafols S, Esteva-Ollé MT, Gomar C. Unanticipated admissions following ambulatory surgery. Ambulatory Surgery. 12// 1997;5(4):183-188. 4. Fleisher LA, Pasternak LR, Herbert R, Anderson GF. Inpatient hospital admission and death after outpatient surgery in elderly patients: importance of patient and system characteristics and location of care. Archives of surgery (Chicago, Ill. : 1960). Jan 2004;139(1):67-72. 5. Coley KC, Williams BA, DaPos SV, Chen C, Smith RB. Retrospective evaluation of unanticipated admissions and readmissions after same day surgery and associated costs. Journal of clinical anesthesia. Aug 2002;14(5):349-353. 6. Hollingsworth JM, Saigal CS, Lai JC, Dunn RL, Strope SA, Hollenbeck BK. Surgical quality among Medicare beneficiaries undergoing outpatient urological surgery. The Journal of urology. Oct 2012;188(4):1274-1278. 7. Bain J, Kelly H, Snadden D, Staines H. Day surgery in Scotland: patient satisfaction and outcomes. Quality in health care : QHC. Jun 1999;8(2):86-91. 8. Fortier J, Chung F, Su J. Unanticipated admission after ambulatory surgery--a prospective study. Canadian journal of anaesthesia = Journal canadien d'anesthesie. Jul 1998;45(7):612-619. 9. Aldwinckle RJ, Montgomery JE. Unplanned admission rates and postdischarge complications in patients over the age of 70 following day case surgery. Anaesthesia. Jan 2004;59(1):57-59. 10. Mezei G, Chung F. Return hospital visits and hospital readmissions after ambulatory surgery. Annals of surgery. Nov 1999;230(5):721-727. 11. Margovsky A. Unplanned admissions in day-case surgery as a clinical indicator for quality assurance. The Australian and New Zealand journal of surgery. Mar 2000;70(3):216-220. 12. Mattila K, Toivonen J, Janhunen L, Rosenberg PH, Hynynen M. Postdischarge symptoms after ambulatory surgery: first-week incidence, intensity, and risk factors. Anesthesia and analgesia. Dec 2005;101(6):1643-1650. 13. Minatti WR, Flavio B, Pablo C, Raúl R, Guillermo P, Miguel S. Postdischarge unplanned admission in ambulatory surgery—a prospective study. Ambulatory Surgery. 1// 2006;12(3):107-112. 14. Morales R, Esteve N, Casas I, Blanco C. Why are ambulatory surgical patients admitted to hospital?: Prospective study. Ambulatory Surgery. 3/15/ 2002;9(4):197-205. 15. Ogg T, Hitchock M, Penn S. Day surgery admissions and complications. Ambulatory Surgery. 1998;6:101-106. 16. Mingus ML, Bodian CA, Bradford CN, Eisenkraft JB. Prolonged surgery increases the likelihood of admission of scheduled ambulatory surgery patients. Journal of clinical anesthesia. Sep 1997;9(6):446-450. 17. Laeeque R, Samad A, Raja AJ. Day care surgery at a university hospital--who is responsible after discharge. JPMA. The Journal of the Pakistan Medical Association. Dec 2001;51(12):422-427. 18. Crew JP, Turner KJ, Millar J, Cranston DW. Is day case surgery in urology associated with high admission rates? Annals of the Royal College of Surgeons of England. Nov 1997;79(6):416-419. 19. Awan FN, Zulkifli MS, McCormack O, et al. Factors involved in unplanned admissions from general surgical day-care in a modern protected facility. Irish medical journal. May 2013;106(5):153-154. 20. Rudkin GE, Bacon AK, Burrow B, et al. Review of efficiencies and patient satisfaction in Australian and New Zealand day surgery units: a pilot study. Anaesthesia and intensive care. Feb 1996;24(1):74-78. 21. Paez A, Redondo E, Linares A, Rios E, Vallejo J, Sanchez-Castilla M. Adverse events and readmissions after day-case urological surgery. International braz j urol : official journal of the Brazilian Society of Urology. May-Jun 2007;33(3):330-338. 22. Twersky R, Fishman D, Homel P. What happens after discharge? Return hospital visits after ambulatory surgery. Anesthesia and analgesia. Feb 1997;84(2):319-324.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Surgery (2014 phase)
  
  
• Review for Importance: The measure meets the Importance criteria (1a. Evidence: 1b. Performance Gap) 1a. Evidence: Y-15; N-3; 1b. Performance Gap: H-5; M-13; L-2; I-0

  Rationale:

  • The developers provided a rationale for the measure, specifically that there are interventions and strategies that may reduce unplanned hospital visits after same-day surgery, including appropriate patient selection, patient education, and nausea and pain management. The developer clarified the difference between an unplanned and planned visit and noted that they recommend reporting the measure as a ratio rather than a rate.
  • The Committee concluded there is minimal evidence that ties specific processes to the outcome but that the rationale is sufficient to support the measure.
  • The developer assessed provider-level variation in performance scores using data from a 20 percent sample of 2010 Medicare fee-for-service claims that represented 4,234 HOPDs and 212,104 surgeries. The measure developers found that the high performing HOPD’s (at or below the 5th percentile) had at least 24 percent fewer than expected surgical hospital visits and those in the 95th percentile had at least 34 percent more hospital visits than what they were expecting given the case and surgical procedure mix.
  • Some Committee members had concerns about being able to determine if there is a performance gap given a small sample size; however, the Committee generally agreed that the evidence is sufficient.
  
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria (2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity) 2a. Reliability: H-2; M-15; L-0; I-0; 2b. Validity: H-3; M-16; L-0; I-0

  Rationale:

  • The data used in testing the reliability of the performance measure score were derived from 2009-2011 Medicare fee-for-service (FFS) claims. These data included a 20 percent sample of same-day surgery claims from Part B (physician) claims, which were then matched to the corresponding hospital claims. The developer conducted a “test-retest” approach by randomly selecting half of the patients from each HOPD into two datasets. They then calculated the risk-standardized hospital visit ratios for each HOPD in each of the datasets, then compared the agreement between the scores for the HOPDs using the Intraclass Correlation Coefficient (ICC) The ICC value was 0.50 (95 percent CI: 0.48-0.53), indicating “moderate” agreement according to the categorization by Landis and Koch.
  • Face validity of the performance measure score was assessed by a Technical Expert Panel comprised of 15 patient representatives, expert clinicians, methodologist, researchers, and providers. Of the 13 experts who responded, 92.3 percent either strongly or moderately agreed that this measure can accurately distinguish better and worse quality facilities.
  • The Committee generally found the reliability and validity information submitted by the developers to be sufficient.
  
  
  
• Review for Feasibility: H-16; M-3; L-0; I-0 (3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)

  Rationale:

  • The data source for this measure is Medicare administrative claims and enrollment data, and therefore all data elements are in defined fields.
  • The Committee was satisfied with the feasibility of this measure.
  
  
  
• Review for Usability: H-6; M-11; L-1; I-0 (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement)

  Rationale: The Committee was generally satisfied with the use and usability of this measure and would like the comments that have been made to be addressed at the next cycle for the measure.
  
  

• Review for Related and Competing Measures:
  • This measure is related to 2539 Facility 7-Day Risk-Standardized Hospital Visit Rate after Outpatient Colonoscopy, 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.
  • The Committee recommended that the need for two similar measures, as well as harmonization and unintended consequences should be assessed during annual updates once the two new measures have been in use for some time so that any potentially needed adjustments could be considered for each measure independently.
  
  
  
• Endorsement Public Comments: April 17, 2015 – May 18, 2015 (Additional 15-day Public and Member Comment: May 22, 2015 to June 5, 2015)

  Comments received:

  • One commenter expressed uncertainty about the feasibility of this measure, citing that a free-standing surgical center would have no mechanism to recall patients. Additionally, hospitals and ambulatory surgical centers that have urgent care facilities would be penalized for providing patient access, per the current measure language.
  • Another commenter noted that CMS Planned Readmission Algorithm 3.0 was used to identify those procedures or conditions that typically result in planned admissions. The commenter noted that this algorithm has been tested for the inpatient care and has not been tested for the ambulatory care setting. The commenter further noted that outpatient surgery procedures that are planned admissions are different and unique to this setting; and questioned that by using this inpatient algorithm, that there has been a compromise in developing a comprehensive list of planned admissions for procedures performed in ambulatory surgery centers.
  • Lastly, two commenters noted that NQF is currently holding a trial period under which measures may be risk-adjusted for patients’ socioeconomic status and other demographic factors (SDS). The commenters suggested that SDS adjustment for measure #2687 (Hospital Visits After Outpatient Surgery) may be appropriate, and questioned why this had not been discussed or considered by the Standing Committee. Commenters also observed that a measure (#2539: Facility 7-Day Risk-Standardized Hospital Visit Rate after Outpatient Colonoscopy) similar to measure #2687 (Hospital Visits after Hospital Outpatient Surgery) was recently endorsed by NQF’s Readmissions Standing Committee, and questioned why the Surgery Standing Committee had not addressed harmonization of these two measures

  NQF response: NQF appreciates your comment and the opportunity to provide clarification. Previous NQF policy prohibited the inclusion of sociodemographic status (SDS) factors in risk-adjustment approaches out of concern that doing so might conceal inequalities in care and result in lower standards of provider performance for certain subpopulations. However, in 2014, NQF convened a multi-stakeholder panel of experts in healthcare performance measurement and disparities to consider if, when, and how performance measures should be adjusted for SDS. After its deliberations, the Expert Panel recommended that NQF should allow inclusion of SDS factors in the risk-adjustment approach for performance measures when conceptual reasons and empirical evidence demonstrate it is appropriate. The NQF Board of Directors reviewed the Expert Panel’s recommendations and decided to temporarily change NQF’s policy and evaluate its impact during the course of a two-year trial period. This trial period went into effect on April 15, 2015, meaning that projects with measure submission deadlines before that date fell under NQF’s previous policy/guidance on SDS adjustment, while projects with measure submission deadlines after that date are subject to the trial policy on SDS adjustment. The2015 Surgery project’s measure submission deadline was January 14, 2015, prior to the start of NQF’s SDS trial period. Therefore, both the developer and the Surgery Standing Committee conformed to the previous policy regarding inclusion of SDS factors in the risk-adjustment approach.

• Thank you for raising these two potential concerns; we would like to clarify, however, that the measure as designed does not assess either ambulatory surgery centers or free standing urgent care facilities. The measure includes outpatient same-day surgeries performed at hospital outpatient departments only; it does not include procedures performed at ambulatory surgery centers. Likewise, the measure does not affect urgent care facilities. They are not measured, and visits to urgent care facilities are not counted in the measure outcome, which only includes hospital emergency department visits, observation stays, or unplanned inpatient admissions.
• We appreciate the question and the opportunity to clarify why it makes sense to use an algorithm developed for hospital readmission measures in this measure, which as you note focuses on same-day surgery rather than admitted patients. The CMS Planned Readmission Algorithm was developed to identify all admissions (rather than readmissions per se) that are planned. That is, it uses condition and procedure codes to distinguish between admissions to address acute illness and injury from admissions of stable patients that are for planned procedures (such as for chemotherapy or a hip replacement). We use the algorithm in this measure because our goal here is the same as it was for the hospital readmission measures – we do not want to include in our measure outcome admissions that are planned, since they are not a signal of care quality. We did review the algorithm carefully to make sure the way we identify the planned admissions makes sense in the context of this surgery measure, and shared the details of the algorithm with our technical expert panel, the public, and NQF reviewers. If you have specific suggestions for ways the algorithm should be adapted for this particular measure, we are happy to consider them.
• We appreciate your concern about the potential effects of SDS on the measure score. We wanted to address your comments on both the process of review and the substance of our conclusions in the NQF application based on the SDS analysis we conducted for the application. Regarding the process, the surgery measure is not technically in NQF’s SDS pilot. “This trial period went into effect on April 15, 2015. This means that projects with measure submission deadlines before that date fell under NQF’s previous policy/guidance on SDS adjustment, while projects with measure submission deadlines after that date are subject to the trial policy on SDS adjustment. Since the 2015 Surgery project’s measure submission deadline was January 14, 2015, both the developer and the Surgery Standing Committee conformed to the [pre-trial] policy regarding inclusion of SDS factors in the risk-adjustment approach (email from Andrew Lyzenga at NQF, June 15, 2015).”
  Regarding the substance of your concern, consistent with the pre-trial NQF guidance on SDS, we evaluated the potential effects of risk adjusting for two SDS indicators – Medicaid-dual eligibility and race. These variable are readily available in the CMS claims data. In addition, use of Medicaid eligibility status as a proxy for SDS is consistent with prior research as well as NQF recommendations (http://www.qualityforum.org/projects/Patient_Outcome_Measures_Phases1-2.aspx). Our results show that adjusting for these factors at the patient level does little to change the measure scores; unadjusted and adjusted HOPD risk-standardized hospital visit (RSHV) ratios are highly correlated (Pearson correlation 0.990 and 0.998 for adjustment for Medicaid-dual eligibility and race, respectively). This suggests that including a patient-level risk adjuster for SDS will make little difference in the measure results after accounting for other factors already adjusted for in the model, such as age, comorbidities, and the complexity of the surgery.
  In addition, to explore whether there might be differences in HOPD RSHV ratios by the proportion of lower SDS patients hospitals care for, we examined the distribution of measure scores by quartiles of both percentage of dual-eligible patients and percentage of African American patients. Although the results show a trend toward higher measure scores in the highest quartile of lower SDS patients, they also show that some hospitals with relatively high proportions of lower SDS patients can and do perform well on the measure. We cannot tell from these analyses what is causing the observed differences across quartiles of proportion of lower SDS patients. One of the potential causes is differences related to quality. For example, some hospitals may be better able than other hospitals to meet the needs of patients with low literacy. Given these findings, on balance we do not recommend adjusting the measure for SDS at this time. Doing so will not appreciably change the measure scores and might contribute to masking disparities in care.
  CMS is participating fully in the NQF trial and is actively working to further consider issues related to adjusting for SDS. In addition, CMS notes that the Office of the Assistant Secretary for Planning and Evaluation (ASPE) is conducting research on the issue of risk adjustment for socioeconomic status as directed by the IMPACT Act and will issue a report to Congress by October 2016. CMS will closely examine the recommendations issued by ASPE and consider how they apply to this and other CMS quality measures.
  CMS did consider the effect of adjusting for SDS and reported the results in the NQF application. As discussed in the application and in response to the question above, we do not recommend adjusting for SDS at this time, so testing the reliability of the measure with SDS adjustment is not necessary at this time. As you note, reliability testing yielded an intraclass correlation coefficient (ICC) of 0.50, which according to conventional interpretation is “moderate.” It should be noted that this ICC value is consistent with those of other CMS claims-based measures. In addition, measure testing was conducted using a 20% sample of Medicare Fee-for-Service data. We expect the reliability score will be higher in the national 100% sample where individual facility volumes would be higher yielding more reliable individual facility results. The 100% sample would be used for public reporting.
  The present measure (NQF # 2687) is already fully harmonized with NQF # 2539 (Facility 7-Day Risk-Standardized Hospital Visit Rate after Outpatient Colonoscopy) on areas of the methodology that are analogous. Specifically, both measures use the same outcome. For both the outpatient surgery measure and the outpatient colonoscopy measure, the outcome is identically specified as all-cause, unplanned hospital visits, defined as 1) an inpatient admission directly after the procedure, or 2) an unplanned hospital visit (emergency department visit, observation stay, or unplanned inpatient admission) occurring after discharge and within 7 days of the outpatient procedure.
  We believe that the measure will yield important information that will help facilities improve patient care. Measure testing demonstrated significant variation in risk-standardized performance across facilities, indicating opportunities for quality improvement. Facilities with a higher than expected number of outcomes will be able to review and improve their processes around preparing the patient for surgery, the surgery itself, and follow-up care. In addition, in implementing the measure, CMS would provide each facility with patient-level data so that facilities could examine the specific causes of higher than expected outcome.
  Reliability testing yielded an intraclass correlation coefficient (ICC) of 0.50, which according to conventional interpretation is “moderate.” It should be noted that this ICC value is consistent with those of other CMS claims-based measures. In addition, measure testing was conducted using a 20% sample of Medicare Fee-for-Service data. We expect the reliability score will be higher in the national 100% sample where individual facility volumes would be higher yielding more reliable individual facility results. The 100% sample would be used for public reporting.

Committee Response:

• The Committee appreciates the opportunity to provide clarification regarding the setting of interest. Given the care setting to which the measure applies, the Committee believes the expressed concerns are mitigated.
• The Committee also appreciates the precision requested by the commenter as well as the clarity provided by the developer. During the in-person meeting the Committee agreed that the specifications of the measure were appropriate.
• Finally, the Committee appreciates the position of NQF, the participation by CMS in the SDS trial as outlined in NQF policy, and CMS commitment regarding recommendations from ASPE research. During the in-person meeting the Committee agreed that the datasets, approach to testing and testing outcome was sufficient to move the measure forward. As part of the annual update to the measure, the Committee anticipates updated information about SDS impact including any changes to the measure to increase SDS sensitivity as well as any changes required to ensure its full alignment with 2539. With respect to harmonization, the Committee agreed that it was appropriate to assess the impact and implementation of the two new measures independently before further consideration about how additional alignment might occur.

Measure Specifications

• NQF Number (if applicable): 753
  
  
• Description: Organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients at least 18 years of age undergoing inpatient colon procedures and/or abdominal hysterectomies as reported through the ACS-NSQIP or CDC NHSN. The measure yields separate SIRs for each procedure. (The endorsed specifications of the measure are: Prototype measure for the facility adjusted Standardized Infection Ratio (SIR) of deep incisional and organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients aged >= 18 years as reported through the ACS National Surgical Quality Improvement Program (ACS-NSQIP) or CDC National Health and Safety Network (NHSN). Prototype also includes a systematic, retrospective sampling of operative procedures in healthcare facilities. This prototype measure is intended for time-limited use and is proposed as a first step toward a more comprehensive SSI measure or set of SSI measures that include additional surgical procedure categories and expanded SSI risk-adjustment by procedure type. This single prototype measure is applied to two operative procedures, colon surgeries and abdominal hysterectomies, and the measure yields separate SIRs for each procedure.)
  
  
• Numerator: Deep incisional primary (DIP) and organ/space SSIs during the 30-day postoperative period among patients at least 18 years of age undergoing inpatient colon surgeries or abdominal hysterectomies. SSIs will be identified before discharge from the hospital, upon readmission to the same hospital, or during outpatient care or admission to another hospital (post-discharge surveillance). Case accrual will be guided by sampling algorithms as described below.
  
  
• Denominator: Using multivariable logistic regression models for colon surgeries and abdominal hysterectomies, the expected number of SSIs is obtained. These expected numbers are summed by facility and surgical procedure and used as the denominator of this measure
  
  
• Exclusions: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded.(The endorsed specifications of the measure are: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded. In the NHSN, patients without primary closure of the surgical incision are not considered eligible cases and are excluded- the NSQIP will match this practice for this measure, although this is not standard practice within the NSQIP.)
  
  
• 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: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Conditional support, pending NQF annual update
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is an update to the name of the measure from “reliability adjusted SIR” to “Adjusted Ranking Metric (ARM).”
  • Impact on quality of care for patients:The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
  
• Does the measure address a program goal or objective? Yes. The priority domain is to make care safer by reducing harm caused in the delivery of care.?
  
  
• Is this a high-value measure? Yes. This is an update to a measure currently in the program. The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in this program – the name is being changed from reliability adjusted SIR to the Adjusted Ranking Metric (ARM). Currently, there are three measures in the program measure set implemented and finalized that address the NQS priority of making care safe, two additional ones are proposed. This is the only SSI measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. It is tested at the hospital/acute care facility level, at the facility level of analysis.
  
  
• Is the measure currently in use? Yes. This measure is currently used in this program, but the name of the measure is changing from reliability adjusted SIR to the Adjusted Ranking Metric (ARM).
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It is currently in the program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Affects large numbers, Frequently performed procedures, A leading cause of morbidity/mortality, High resource use, Severity of illness, Patient/societal consequences of poor quality. SSIs estimated to account for 20% of all HAIs[1] 290,485 estimated SSIs/yr[2] Estimated 8,205 deaths associated with SSIs each year[1] Estimated 11% of all deaths occurring in intensive care units are associated with SSIs[1] $34,670 medical cost/SSI[2] Total >$10 billion attributable to SSI in U.S. each year[2] Estimated additional 7-10 days of hospitalization for each SSI per patient[1] [1] Klevens RM, Edwards JR, et al. Estimating healthcare-associated infection and deaths in U.S. hospitals, 2002. Public Health Reports 2007; 122:160-166. [2] Scott, RD. The Direct Medical Costs of Healthcare-Associated Infections in U.S. Hospitals and the Benefits of Prevention. http://www.cdc.gov/ncidod/dhqp/pdf/Scott_CostPaper.pdf accessed April 12, 2010.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Patient Safety Measures
  
  
• Review for Importance: The measure addresses a high impact area. Each year, approximately 11 percent of all deaths in ICUs are associated with SSIs, resulting in up to 20,000 deaths and $2 billion in additional costs.2 Moreover, evidence-based interventions have shown significant reductions in SSI rates and improved health outcomes.
  
  
• Review for Scientific Acceptability: See CDP Recommendation]
  
  
• Review for Feasibility: See CDP Recommendation]
  
  
• Review for Usability: See CDP Recommendation]
  
  
• Review for Related and Competing Measures: See CDP Recommendation]
  
  
• Endorsement Committee Recommendation: The Steering Committee discussed the newly-harmonized measure in a supplemental conference call, reviewing the relevant changes, while also receiving clarification from the developers on several issues. Committee members inquired as to why these two particular measures had been chosen, and asked for clarification on the plan for public reporting. The developer explained that the CMS IPPS requirements released on August 1, 2011, call for abdominal hysterectomies and colon surgeries to be reported by the CDC to CMS. The NHSN will serve as the single reporting system for CMS-required reporting. However, facilities may choose which calculations of performance on the measure can be accomplished using either the NHSN or NSQIP data system. The measure developer acknowledged that for hospitals participating in both systems, there could be duplication.The Steering Committee questioned why both organ space and deep incisional infections were included in the measure. The developer described the approach as a long standing precedent and stated that superficial infections are considered trivial events and therefore not included. However, organ space infections that drain through the incisions are classified as deep incisional infections. The combination of organ space and deep incisional infections are considered a clinically coherent grouping. The Committee expressed their appreciation for the developers’ efforts at harmonization, and agreed that the measure continues to meet the four major evaluation criteria. The Steering Committee recommended this measure for endorsement in a unanimous vote.This outcome measure replaces NQF-endorsed measure #0299 (Surgical Site Infection Rate) and addresses the National Priority area of safety.
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a cellulitis IP stay and attributes them to the hospital where the index IP stay occurred. It includes subtypes for diabetics, decubitus pressure ulcers, and other cellulitis patients.
  
  
• Numerator: The numerator of the Cellulitis Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to cellulitis across a hospital’s eligible cellulitis episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:While the costs can be high, only a small subset of patients with cellulitis require hospitalization. (Acumen. Methodology for Developing the Six Hospital-based Episode Measures: Supplemental Documentation for the Fiscal Year 2015 Inpatient Prospective Payment System and Long-Term Care Hospital Prospective Payment System Proposed Rule. Available at: http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/index.html?redirect=/hospital-value-based-purchasing) CMS has noted that the variations in cost associated with treating cellulitis are the result of post discharge costs that reflect variations in quality. An episode-based approach could help drive improvement in both cost and quality. (http://content.healthaffairs.org/content/28/5/1406.full.pdf)
  
  
  
• Does the measure address a program goal or objective? Yes. This measure addresses the VBP priority domain of Making Care Affordable. This measure has been finalized for use in the Hospital IQR program in FY 2019. To be added to the VBP program, this measure must be included in IQR and reported on the Hospital Compare website for at least 1 year prior to use in the VBP program.
  
  
• Is this a high-value measure? Yes. This is an efficiency measure addressing a condition with significant variation in performance. Cellulitis is a common but potentially serious skin condition and costs can be significant if hospitalization is required. Costs range from about $5,000 at the 5th percentile to about $24,000 at the 95th percentile. Costs for cellulitis episodes totaled more than $1.4 billion in 2012 with an average cost of $10,000. ?Treatment is usually oral antibiotics however hospitalization may be required for severe infections leading to significant costs.
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No. This measure has been finalized for the IQR FY 2019 measure set.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a GI hemorrhage IP stay and attributes them to the hospital where the index IP stay occurred. It includes subtypes for 1) upper, 2) lower, 3) upper and lower, and 4) undefined bleeds.
  
  
• Numerator: The numerator of the GI Hemorrhage Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to GI hemorrhage across a hospital’s eligible GI Hemorrhage episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:CMS has noted that the variations in cost associated with treating GI hemorrhages are the result of post discharge costs that reflect variations in quality. An episode-based approach could help drive improvement in both cost and quality. (http://content.healthaffairs.org/content/28/5/1406.full.pdf)
  
  
  
• Does the measure address a program goal or objective? Yes. This measure addresses the VBP priority domain of Making Care Affordable. This measure has been finalized for use in the Hospital IQR program in FY 2019. To be added to the VBP program, this measure must be included in IQR and reported on the Hospital Compare website for at least 1 year prior to use in the VBP program.
  
  
• Is this a high-value measure? Yes. The estimated annual hospitalization rate for upper GI bleeding is 165 per 100,000 (Albeldawi M., Qadeer MA, Vargo JJ. Managing acute upper GI bleeding, preventing recurrences. Cleveland Clin J Med. ) This translates to over 300,000 hospitalizations annually, costing over $2.5 billion. (Viviane A, Alan BN. Estimates of costs of hospital stays for variceal and nonvariceal upper gastrointestinal bleeding in the United States. Value Health 2008; 11:1–3.) Costs have been found to be primarily related to inpatient hospitalizations. (Cryer BL1, Wilcox CM, Henk HJ, Zlateva G, Chen L, Zarotsky V. The economics of upper gastrointestinal bleeding in a US managed-care setting: a retrospective, claims-based analysis. J Med Econ. 2010 Mar;13(1):70-7. doi: 10.3111/13696990903526676.) However, GI hemorrhage can be caused by a number of underlying conditions and the costs can vary significantly by type of GI bleeding . (Viviane A, Alan BN. Estimates of costs of hospital stays for variceal and nonvariceal upper gastrointestinal bleeding in the United States. Value Health 2008; 11:1–3.) Additionally there is substantial variation in costs, ranging from $6,500 at the 5th percentile to $23,000 at the 95th percentile. CMS notes that these costs are driven by post discharge costs that reflect variations in quality. (2015 IPPS Final Rule)
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No. This measure has been finalized for the IQR FY 2019 measure set.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable): 2558
  
  
• Description: This measure estimates hospital-level, risk-standardized mortality rates for Medicare fee-for-service (FFS) patients who are 65 years of age or older and discharged from the hospital following a qualifying isolated CABG surgery. (The endorsed specifications of the measure are: The measure estimates a hospital-level, risk-standardized mortality rate (RSMR) for patients 18 years and older discharged from the hospital following a qualifying isolated CABG procedure. Mortality is defined as death from any cause within 30 days of the procedure date of an index CABG admission. The measure was developed using Medicare Fee-for-Service (FFS) patients 65 years and older and was tested in all-payer patients 18 years and older. An index admission is the hospitalization for a qualifying isolated CABG procedure considered for the mortality outcome.)
  
  
• Numerator: The outcome for this measure is 30-day all-cause mortality. Mortality is defined as death for any reason within 30 days of the procedure date from the index admission for patients 65 and older discharged from the hospital after undergoing isolated CABG . (The endorsed specifications of the measure are: The outcome for this measure is 30-day all-cause mortality. Mortality is defined as death for any reason within 30 days of the procedure date from the index admission for patients 18 and older discharged from the hospital after undergoing isolated CABG surgery.)
  
  
• Denominator: This claims-based measure can be used in either of two patient cohorts: (1) patients aged 65 years or older or (2) patients aged 18 years or older. We have tested the measure in both age groups. The cohort includes admissions for patients who receive a qualifying isolated CABG procedure and with a complete claims history for the 12 months prior to admission. If a patient has more than one qualifying isolated CABG admission in a year, one hospitalization is randomly selected for inclusion in the measure.(The endorsed specifications of the measure are: This claims-based measure can be used in either of two patient cohorts: (1) patients aged 65 years or older or (2) patients aged 18 years or older. We have tested the measure in both age groups.The cohort includes admissions for patients who receive a qualifying isolated CABG procedure (see codes below) and with a complete claims history for the 12 months prior to admission. For simplicity of implementation and as testing demonstrated closely correlated patient-level and hospital-level results using models with or without age interaction terms, the only recommended modification to the measure for application to all-payer data sets is replacement of the “Age-65” variable with a fully continuous age variable.If a patient has more than one qualifying isolated CABG admission in a year, one hospitalization is randomly selected for inclusion in the measure.)
  
  
• Exclusions: For all cohorts: 1) Patients who leave hospital against medical advice (AMA) 2) Patients with inconsistent or unknown vital status or other unreliable data 3) Subsequent qualifying CABG procedures during the measurement period are identified by the ICD-9 codes defining CABG listed in denominator details. 4) Non-isolated CABG procedures (CABG Surgeries that occur concomitantly with excluded procedures and procedure groups).(The endorsed specifications of the measure are: Hospitalizations are excluded if they meet any of the following criteria. Hospitalizations for:1) Patients with inconsistent or unknown vital status or other unreliable data.Rationale: We exclude these because the outcome cannot be adequately measured in these patients.2) Patients who leave the hospital against medical advice (AMA)Rationale: We exclude hospitalizations for patients who are discharged AMA because providers did not have the opportunity to deliver full care and prepare the patient for discharge.3) Patients with qualifying CABG procedures subsequent to another qualifying CABG procedure during the measurement periodRationale: CABG procedures are expected to last for several years without the need for revision or repeat revascularization. A repeat CABG procedure during the measurement period very likely represents a complication of the original CABG procedure and is a clinically more complex and higher risk surgery. We, therefore, select the first CABG admission for inclusion in the measure and exclude subsequent CABG admissions from the cohort.)
  
  
• HHS NQS Priority: Making Care Safer, Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Administrative claims. The Medicare data sources used to create the measure were: 1) Medicare Part A inpatient and Outpatient and Part B outpatient claims from the Standard Analytic File, including inpatient and outpatient claims for the 12 months prior to an index admission. 2) Medicare Enrollment Database (EDB): This database contains Medicare beneficiary demographic, benefit/coverage, and vital status information.. The all-payer data source used to test the measure in patients 18 years and over was: 1) 2006 California Patient Discharge Data (PDD), a large, linked database of approximately 3 million adult discharges from more than 450 non-Federal acute care hospitals
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:CABG is a common surgery with notable variation in mortality. Adding this measure to the VBP measure set could provide an incentive to improve patient safety in this area.
  • Impact on quality of care for patients:Coronary Artery Bypass Graft (CABG) Surgery is one of the most commonly performed surgeries in the United States. However, mortality for CABG surgery varies significantly. The measure developer found a mean rate of 3.2% with a range from 1.5%-7.9%. The developer found a median rate of 3.0% (25th and 75th percentiles are 2.6% and 3.6%, respectively). Adding this measure to the VBP program could help to reduce this variation and drive improvement.
  
  
  
• Does the measure address a program goal or objective? Yes. Coronary Artery Bypass Graft (CABG) Surgery is one of the most commonly performed surgeries in the United States. In 2007, there were over 114,000 hospitalizations for CABG surgery and over 137,000 hospitalizations for combined surgeries for CABG and valve procedures among Medicare beneficiaries. This measure would enhance the clinical care domain of the program by addressing mortality for another common condition with significant morbidity and mortality.
  
  
• Is this a high-value measure? Yes. This is an outcome measure. Mortality for CABG surgery varies significantly. The measure developer found a mean rate of 3.2% with a range from 1.5%-7.9%. The developer found a median rate of 3.0% (25th and 75th percentiles are 2.6% and 3.6%, respectively).
  
  
• Does this measure fill a gap in the program measure set? Yes. This measure would address a common surgery with significant variation in mortality. Outcomes for CABG surgery are not currently addressed in the VBP measure set.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No. This measure will be used in IQR starting in FY 2017.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure would maintain the statutory requirement that measures in VBP be drawn from the IQR measure set. This measure is a claims-based measure also used in the IQR program. This measure would address CABG mortality which is not addressed by another measure in the program and is an extremely important outcome to patients.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
It is envisioned that this measure will provide hospitals with procedure-specific information to help improve patient safety and quality of care, thus reducing mortality rates. CABG is a priority area for outcomes measure development because it is a common procedure associated with considerable morbidity, mortality, and health care spending. In 2007, there were 114,028 hospitalizations for CABG surgery and 137,721 hospitalizations for combined surgeries for CABG and valve procedures (“CABG plus valve” surgeries) among Medicare FFS patients in the U.S. [1] CABG surgeries are costly procedures that account for the majority of major cardiac surgeries performed nationally. In fiscal year 2009, isolated CABG surgeries accounted for almost half (47.6%) of all cardiac surgery hospital admissions in Massachusetts. [2] In 2008, the average Medicare payment was $30,546 for CABG without valve and $47,669 for CABG plus valve surgeries. [3] Mortality rates following CABG surgery vary widely across hospitals. Our mean RSMR is 3.2% with a range from 1.5%-7.9%. The median risk-standardized rate is 3.0% (25th and 75th percentiles are 2.6% and 3.6%, respectively). Similarly, published data also demonstrate variation in mortality rates. 1. Drye E, Krumholz H, Vellanky S, Wang Y. Probing New Conditions and Procedures for New Measure Development: Yale New Haven Health Systems Corporation; Center for Outcomes Research and Evaluation.; 2009:1-7. 2. Massachusetts Data Analysis Center. Adult Coronary Artery Bypass Graft Surgery in the Commonwealth of Massachusetts: Hospital and Surgeons Risk-Standardized 30-Day Mortality Rates. In: Health MDoP, ed. Boston2009:77. 3. Pennsylvania Health Care Cost Containment Council. Cardiac Surgery in Pennsylvania 2008-2009. Harrisburg2011:60. 4. American New York State Department of Health. Adult Cardiac Surgery in New York State 2006-20082010:54.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: NQF-Endorsed Measures for Surgical Procedures
  
  
• Review for Importance: The measure meets the Importance criteria(1a. Evidence, 1b. Performance Gap, 1c. High Impact)1a. Evidence: Y- 23; N- 0; 1b. Performance Gap: H- 16; M- 6; L- 0; I-0; 1c. Impact: H- 21; M- 1; L- 0; I-0Rationale:• Evidence provided by the developer displays a direct relationship between the outcome of mortality and processes of care, including timing of procedure in relation to cardiac events and various peri-operative strategies.• The developer provided data from 2009-2011 showing that risk-adjusted mortality rates ranged from 1.5% to 9.3%, demonstrating a gap in performance.• The Committee agreed that an opportunity for improvement remains on this measure.• In 2007, there were 114,028 hospitalizations for CABG surgery and 137,721 hospitalizations for combined surgeries for CABG and valve procedures (“CABG plus valve” surgeries) among Medicare FFS patients in the United States, suggesting that this is a high priority.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H- 12; M- 10; L-1; I-0; 2b. Validity: H- 14; M- 9; L- 0; I-0Rationale:• Reliability testing was conducted at both the performance measure score and data element level. A test-retest approach was performed with the correlation coefficient being 0.32 which the Committee stated was sufficient for reliability.• Validity was conducted at both the data element and measure score level. Face validity was also assessed by a Technical Expert Panel using a six-point scale obtained from the mortality measure as specified, provide an accurate distinction between good and bad quality of care.
  
  
• Review for Feasibility: H- 21; M- 2; L- 0; I-0(3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented)Rationale: The Committee had no concerns regarding measure logic feasibility based on the feasibility assessment using administrative claims.
  
  
• Review for Usability: H- 8; M- 12; L- 3; I-0 (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement)Rationale: The Committee discussed no concerns regarding usability and use. Although this measure is not being currently reported, the developer stated plans for future use.
  
  
• Review for Related and Competing Measures: This measure directly competes with 0119 Risk-Adjusted Operative Mortality for CABG, Percent of patients aged 18 years and older undergoing isolated CABG who die, including both 1) all deaths occurring during the hospitalization in which the CABG was performed, even if after 30 days, and 2) those deaths occurring after discharge from the hospital, but within 30 days of the procedure.
  
  
• Endorsement Public Comments: Commenters generally expressed support for the measure and the Committee's recommendation forendorsement.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y- 22;N-1    
  Consensus Standards Approval Committee (CSAC) Review (October 14,2014): Y-16; N-0; A-0
  Decision: Approved for Endorsement 
  Board of Directors Vote: (October 27, 2014)
  Decision: Ratified for Endorsement   
  Appeals:Three appeals were received on this measure:
  
  • In summary, the appellants requested reconsideration of theendorsement of measures #0119 and #2558, both of which measurerisk-adjusted mortality rates within 30 days of CABG surgery.Many of the appellants questioned whether 30-day mortality initself reflects quality of care, noting that it is only oneindicator among many potential outcomes of interest to patients.Moreover, appellants argued that a 30-day mortality measure mayhave significant unintended consequences, including discouragingappropriate palliative care or appropriate withdrawal ofpost-operative life-supporting treatments despite patient orfamily preferences to limit life-supporting care. Appellantsalso suggested that surgeons may be more likely to decline toperform needed surgery on patients who are at high risk ofcomplications or patients who have placed reasonable limits ontheir post-operative care. In addition, appellants stated thatthese measures are susceptible to ‘gaming’ (e.g., keepingpatients alive until postoperative day 31 to avoid penalties,and then transitioning to palliative care). In general,appellants suggested that these measures are insufficientlysensitive to patient preferences and that they perpetuatenon-patient-centered care.   
    
  • NQF Response: The Surgery Standing Committee chairsappreciated the concerns raised by the appellants, and agreedthat consideration of potential unintended consequences is acritical part of the measure evaluation process. As the Societyof Thoracic Surgeons (STS) and the Centers for Medicare &Medicaid Services/Yale-Center for Outcomes Research andEvaluation (CMS/Yale-CORE) describe in their responses, 30-daymortality measures should be—and are—part of a balanced approachto measurement that takes into account various indicators ofhealthcare quality and multiple outcomes that are important topatients. The Committee co-chairs believe it remains importantto measure postoperative mortality as one facet of quality, andare satisfied that the developers have addressed the appellants’concerns in their responses.
  • Developer Response (Centers for Medicare & MedicaidServices): The developer stated that there are various benefitsachieved by measuring 30-day mortality following CABG surgery,such as providing hospitals with an incentive to reducemortality through improved coordination of peri-operative careand discharge planning. The state of California’s success inreducing CABG mortality rates when using registry-basedmortality measures was cited as an example of the benefits thatcan be achieved through use of such measures.
  • The developer agreed with the appellants that a multi-facetedapproach to measurement is desirable, noting that their CABGmortality measure is harmonized with a measure of readmissionsafter CABG surgery, which helps to ensure that the full spectrumof peri-operative care and care coordination can be assessed.
  • However, while some appellants suggest that patient-reportedoutcomes (PROs) be used to replace or supplement mortalitymeasurement, the developer noted that there are some significantchallenges associated with PROs, including the lack of routineor reliable collection of patient-reported data.
  • In response to the appellants’ concerns about surgeonswithholding comfort care or declining needed surgery forhigh-risk patients, the developers cited studies suggesting thatthere is little evidence that provider behavior is influenced bythe public release of performance data.
  • Consensus Standards Approval Committee (CSAC) Review (January2015): On January 13, 2015 the CSAC convened to discuss theappeals and voted to uphold endorsement for both measures (with100% approval). CSAC members acknowledged the appellants’concerns, but remained supportive of endorsement, noting thatthe measures address an important health outcome and suggestingthat while the concerns expressed by the appellants may havesome validity, the benefits of the measure are highly likely tooutweigh potential unintended consequences. Additionally, CSACmembers expressed satisfaction with the developers’ responses tothe issues raised, including their approach to monitoring forunintended consequences.  
    
  • Board of Directors Executive Committee (February 2015): TheExecutive Committee upheld the CSAC decision and votedunanimously to uphold endorsement of the measure
  
  
  

Measure Specifications

• NQF Number (if applicable): 2579
  
  
• Description: This measure estimates hospital-level, risk-standardized payment for a pneumonia episode of care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of pneumonia, aspiration pneumonia, and sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. (The endorsed specifications of the measure are: This measure estimates hospital-level, risk-standardized payment for a pneumonia episode of care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of pneumonia.)
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We are using this field to define the outcome. The outcome for this measure is a hospital-level, risk-standardized payment for Medicare patients for a pneumonia episode-of-care. The payment timeframe starts from the admission date of an index hospitalization through 30 days post-admission. We include payments for the index admission, as well as payments for subsequent inpatient, outpatient, skilled nursing facility, home health, hospice, physician/clinical laboratory/ambulance services, supplier Part B items, and durable medical equipment, prosthetics/orthotics, and supplies. In order to compare payments for Medicare patients related to clinical care, we remove geography and policy adjustment from our payment calculation whenever possible. If the data for a specific care setting do not allow for the removal of these adjustments, we calculate an average payment for each item across all geographic areas and replace the claim payment amount in the data with the average payment amount for that item.
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The measure cohort includes admissions to non-federal, short-stay, acute-care hospitals for Medicare FFS patients age 65 years and older with a principal discharge diagnosis of pneumonia, or aspiration pneumonia, or sepsis in cases where sepsis is accompanied by secondary diagnosis of pneumonia present on admission. Patients must also have continuous enrollment in Medicare Part A and Part B benefits for the 12 months prior to the index admission and 30 days post- admission.
  
  
• Exclusions: The measure excludes patients with: 1. Incomplete administrative data in the 30 days following the index admission (if alive) 2. Same or next day discharge and patient did not die or get transferred 3. Transfers into the hospital 4. Inconsistent or unknown mortality status 5. Unreliable data 6. Patients who leave hospital against medical advice (AMA) 7. Patients enrolled in hospice in year prior to admission or day of admission 8. Transfers to Federal hospitals 9. Patients without an index admission DRG or DRG weight 10. Admissions within 30 days of a previous index admission
  
  
• HHS NQS Priority: Communication and Care Coordination, Making Care Affordable
  
  
• HHS Data Source: Administrative claims. Medicare administrative claims data for certain Part A and Part B services in the 12 months prior to and during the index admission are used for risk adjustment. The data also contain price-standardized payments for Medicare patients across multiple care settings, services, and supplies (i.e., inpatient, outpatient, SNF, home health, hospice, physician/clinical laboratory/ambulance services, and durable medical equipment, prosthetics/orthotics, and supplies). The price-standardized payment data element is harmonized across CMS cost and resource use measures
  
  
• Measure Type: Cost/Resource Use
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do not support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:Pneumonia is the second leading cause of hospitalization for Americans over 65 years old resulting in 1.2 million hospital admissions with annual expenditures of over $10 billion.Costs of care for an pneumonia episode vary significantly. Implementing this measure could help lower costs related to variations in quality.
  
  
  
• Does the measure address a program goal or objective? Yes. ? This measure addresses the VBP priority domain of Making Care Affordable. Pneumonia is the second leading cause of hospitalization for Americans over 65 years old resulting in 1.2 million hospital admissions with annual expenditures of over $10 billion.
  
  
• Is this a high-value measure? Yes. Yes. This measure addresses a common cause of hospitalizations with demonstrated variations in cost per episode. Unadjusted 30-day episode of care payment ranges from $6,060 to $40, 164 with a mean of $12,631. After adjustments for patient and clinical characteristics the mean is $13,237 and ranges from $8,281 to $27,975.
  
  
• Does this measure fill a gap in the program measure set? Yes. Currently only one measure in the program measure set that addresses the NQS priority of making care affordable (Medicare Spending per Beneficiary). CMS has indicated that measures that effectuate changes in efficiency and reward value over volume are high priority domains for this program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. This measure is currently reported on Hospital Compare.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Medicare spending is estimated to have been $525.0 billion in 2010 with annual growth rates projected to be 6.3% for 2013 through 2020 due to both an increase in the Medicare population as well as Medicare spending on each beneficiary[1]. Further projections anticipate an exhaustion of Medicare‘s Hospital Insurance Trust Fund (Part A) by 2024 [2]. The growth in spending is unsustainable and highlights the need to understand the value of care Medicare buys with every dollar spent. Given the urgency of the state of the Medicare Hospital Insurance Trust Fund and the fact that Medicare pays for 40-50% of hospitalizations nationally [3], hospital costs are a natural venue in which to deconstruct payments for Medicare patients. Yet payments to hospitals are difficult to interpret in isolation. Some high payment hospitals may have better clinical outcomes when compared with low payment hospitals; other high payment hospitals may not. For this reason, the value of hospital care is more clearly assessed when pairing hospital payments with hospital quality. A measure of payments for Medicare patients to hospitals that is aligned with current quality of care measures will facilitate profiling hospital value (payments and quality). This measure will reflect differences in the management of care for patients with pneumonia both during hospitalization and immediately post-discharge. Pneumonia is a condition with substantial range in costs of care and for which there are well-established publicly reported quality measures and is therefore an ideal condition for assessing relative value for an episode-of-care that begins with an acute hospitalization. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care. 1. Ash AS, Byrne-Logan S. How Well Do Models Work? Predicting Health Care Costs. Proceedings of the Section on Statistics in Epidemiology. American Statistical Association. 1998. 2. Medpac. Report to the Congress: Medicare Payment Policy 9/17/12 2012. 3. National Hospital Discharge Survey. http://www.cdc.gov/nchs/nhds.htm. Accessed 08/07/2012.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Endorsing Cost and Resource Use Measures: Phase 3
  
  
• Review for Importance: The measure meets the Importance criteria1a. High Priority: H-17; M-5; L-0; I-0; IE-0; 1b. Opportunity for Improvement: H-19; M-2; L-1; I-0; 1c. Measure Intent: H-18; M-4; L-0; I-0 1. Overall Importance: H-18; M-4; L-0; I-0Rationale:• The Committee stated that the measure is high priority given that pneumonia is one of the leading causes of hospitalization for Medicare patients sixty-five years of age and older, with Medicare paying roughly ten billion dollars in aggregate costs for hospitalized beneficiaries with pneumonia. • The developer presented evidence indicating that there is a threefold variation in cost for the medical treatment of pneumonia patients, which the Committee agreed signified that there is a substantial opportunity for improving the overall costs for pneumonia patients.• The Committee stated that by using this measure in conjunction with a measure capturing the quality of care for pneumonia patients, there is an opportunity to begin to understand the value of the care provided by the hospitals and other providers in treating this condition.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-10; M-11; L-1; I-0 2b. Validity: H-3; M-18; L-1; I-0Rationale:• The Committee stated that the measure specifications were precise and that the measure was well-constructed. This measure captures risk-standardized payments for a thirty-day episode of care for Medicare patients diagnosed admitted to the hospital with a diagnosis of pneumonia through administrative claims data.• The developer provided reliability testing at the level of the performance measure score; testing was performed by calculating the Intraclass Correlation Coefficient (ICC) score by calculating the risk standardized payment using a split-sample of the combined 2008-2009 data from hospitals. The ICC score was 0.825, indicating significant agreement between the two samples, which the Committee found sufficient.• The Committee questioned the validity of specifying the measure for a thirty-day episode triggered by admission for pneumonia, as the treatment of pneumonia may require care coordination post-discharge that may extend past thirty days. The Committee stated that this could affect payments captured during the post-discharge period, artificially inflating or deflating the costs for some patients simply because of the construct of the measure.• The Committee raised concerns regarding the attribution approach and the implications for attribution of costs if a patient were transferred to another hospital. The developer clarified that only 0.4 percent of cohorts are transferred for pneumonia, which represents a small number of beneficiaries. In the case of transfer patients, costs for the patient will be attributed to the initial admitting hospital, as hospitals are increasingly responsible for care delivered up to 30 days after discharge. The Committee found this approach to attribution to be acceptable.• The Committee stated concern that the low r-squared value (.07) for the risk model may indicate that case mix is not being appropriately adjusted for through the risk model. The developer clarified that at lower patient volumes, there is less certainty when estimating cost. The measure uses a continuous outcome which results in a more accurate estimate than would result from a binary outcome. Additionally, the measure uses hierarchical risk modeling that adjusts hospitals with low patient volume towards the mean. The Committee found this explanation to be sufficient.• The Committee questioned whether adjustments for sociodemographic status (SDS) factors should be incorporated into the risk adjustment model. NQF clarified that it is in the early stages of reviewing our policy on risk adjusting for SDS factors. The recommendations for modifying NQF’s current policy on adjusting for SDS factors have not yet been finalized. As such, we ask that Committees continue to evaluate measures according to our current guidelines, that SDS factors are not included in the risk adjustment model, but are used to stratify the measure. If in the future the recommendations for adjusting for SDS factors become NQF policy, measures that may be improved from incorporating these adjustments will be updated and reviewed by the Committee through one of NQF’s measure maintenance processes.
  
  
• Review for Feasibility: H-20; M-2; L-0; I-0(3a. Byproduct of Care Processes; and 3b. Electronic sources; and 3c. Data Collection Strategy)Rationale: The Committee stated that this measure is feasible to implement because the measure is specified using administrative claims data which is created as a byproduct of care delivery and available electronically.
  
  
• Review for Usability: H-10; M-11; L-1; I-0(4a. Accountability/transparency (used in accountability w/in 3 yr, public reporting w/in 6 yr, or if new - credible plan); and 4b. Improvement – progress demonstrated (if new - credible rationale); and 4c. Unintended Consequences - benefits outweigh evidence of unintended negative consequences (to patients/populations); and 4d. Measure Deconstruction – can be deconstructed to facilitate transparency and understanding)Rationale:• The Committee found the measure to be useful for providers, giving them access to detailed data of cost for hospital care for pneumonia.• The Committee questioned the availability of information on costs for providers other than the hospital to which the patient has been attributed, stating that for this measure to be most useful there needs to be documentation of the reimbursement amounts for each provider treating the patient.
  
  
• Review for Related and Competing Measures: No related or competing measures identified.
  
  
• Endorsement Public Comments: August 14, 2014 - September 12, 2014Comments received:• One measure-specific comment was received regarding the appropriateness of the attribution approach for measure #2579. The commenter suggested that the current attribution approach is inappropriate and only reflects an episode-of-care attributed to a hospital as the responsible entity and does not account for the care of multiple providers across the health care delivery system. The commenter suggested this approach would be more appropriate for an integrated health system or an organization accepting bundled payments.• Two comments regarding risk adjustment for sociodemographic status for this measure. Some commenters believed that it would be appropriate to stratify claims by sociodemographic factors and document non-clinical elements that negatively impact patient outcomes when calculating risk adjusted costs.• One measure-specific comment was received regarding validity of exclusions for measure this measure. A commenter proposed the inclusion of ICD-9 code 507.0 in the denominator for aspiration pneumonia, which was estimated to account for 15% of Medicare patients discharged with pneumonia.Developer response:• Yale addressed the concern of integrating the ICD-9 code 507.0 in the denominator for aspiration pneumonia and based on the prevalence of the code, developers will plan to reevaluate including aspiration pneumonia in future versions of the measure.Committee responses:• The Committee acknowledged and many shared the concerns with the attribution approach used in this measure; however, they also stated that hospitals are increasingly responsible for care delivered up to 30 days after discharge. Consequently, hospitals are in the unique position of being able to push coordination of care, and this measure may serve as an impetus for this to occur.• The Committee recognizes the importance of adequately adjusting for sociodemographic status in the appropriate applications. While NQF continues to work on their implementation of the guidance from the SDS Expert Panel, measures currently under review have been recommended with additional guidance to stratify for SDS, as appropriate.• Based on the NQF criteria for validity, the Committee has agreed that this measure has met the criteria for validity and has recommended it for endorsement. A few committee members support the inclusion of ICD-9 code 507.0 within this measure, which will assist with documenting the presence of pneumonia aspiration among admission.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-21; N-1.
  
  NQF Member Voting: October 6, 2014- October 20, 2014
  Representatives of 18 member organizations voted, with 50% approval;consensus was not reached. 
  
  Consensus Standards Approval Committee (CSAC) Vote: November 12,2014; Y-13, N-0
  Endorsed with the same conditions the CMS cardiovascular hospitallevel episode-based measures from phase II. 
  
  Board of Directors Executive Committee Vote: December 22, 2014
  Ratified endorsement with the following conditions:
  
  • One- year Look Back Assessment of Unintended Consequences: NQFstaff will work with Cost and Resource Standing Committee andCMS to determine a plan for assessing potential unintendedconsequences of this measure in use. The evaluation ofunintended consequences will be initiated in approximately oneyear and possible changes to the measures based on this data.
  • Consideration for SDS trial period: The Cost and Resource UseStanding Committee will consider whether the measure should beincluded in the NQF trial period for sociodemographic statusadjustments.
  • Attribution: NQF will consider opportunities to address theattribution issue. 
  Appeals: December 30, 2014 -January 28, 2015
  No appeals submitted.
  
  
  

Measure Specifications

• NQF Number (if applicable): 2431
  
  
• Description: This measure estimates hospital-level, risk-standardized payment for an AMI episode-of-care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of AMI.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We are using this field to define the outcome. The outcome for this measure is a hospital-level, risk-standardized payment for Medicare patients for an AMI episode of care. The payment timeframe starts from the admission date of an index hospitalization through 30 days post-admission. We include payments for the index admission, as well as payments for subsequent inpatient, outpatient, skilled nursing facility, home health, hospice, physician/clinical laboratory/ambulance services, supplier Part B items, and durable medical equipment, prosthetics/orthotics, and supplies. In order to compare payments for Medicare patients related to clinical care, we remove geography and policy adjustment from our payment calculation whenever possible. If the data for a specific care setting do not allow for the removal of these adjustments, we calculate an average payment for each item across all geographic areas and replace the claim payment amount in the data with the average payment amount for that item.
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The measure cohort includes admissions to non-federal, short-stay, acute-care hospitals for Medicare FFS patients aged 65 years and older with a principal discharge diagnosis of AMI. Patients must also have continuous enrollment in Medicare Part A and Part B benefits for the 12 months prior to the index admission and 30 days post- admission.
  
  
• Exclusions: 1. Incomplete administrative data in the 30 days following the index admission if discharged alive 2. Discharged alive on the day of admission or the following day who were not transferred 3. Inconsistent or unknown patient vital status, or other unreliable demographic data (age and gender) 4. Admissions where patients are discharged against medical advice (AMA) 5. Enrolled in the Medicare hospice program any time in the 12 months prior to the index admission, including the first day of the index admission 6. Transferred to federal hospitals 7. Transferred into the hospital 8. Missing index DRG weight and provider received no payment
  
  
• HHS NQS Priority: Making Care Affordable
  
  
• HHS Data Source: Administrative claims. The measure uses Medicare administrative claims data and enrollment information. Medicare administrative claims data for certain Part A and Part B services in the 12 months prior to and during the index admission are used for risk adjustment. The data also contain price-standardized payments for Medicare patients across multiple care settings, services, and supplies (i.e., inpatient, outpatient, SNF, home health, hospice, physician/clinical laboratory/ambulance services, and durable medical equipment, prosthetics/orthotics, and supplies). The price-standardized payment data element is harmonized across CMS cost and resource use measures.
  
  
• Measure Type: Cost/Resource Use
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Do not support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:AMI is a leading cause of hospitalizations for Americans over 65 years old and costs approximately $18 billion annually. Costs of care for an AMI episode vary significantly. Implementing this measure could help lower costs related to variations in quality.
  
  
  
• Does the measure address a program goal or objective? Yes. This measure addresses the VBP priority domain of Making Care Affordable. The NQF Cost and Resource Use Standing Committee noted that AMI is a high-prirotity area for measuring cost and resource use because of the incidence and the cost per episode.
  
  
• Is this a high-value measure? Yes. This measure addresses the cost of care for a common condition. AMI is a leading cause of hospitalizations for Americans over 65 years old and costs approximately $18 billion annually. Unadjusted 30 day episode-of-care payment ranges from $12,282 to $37,482 with a mean of $19,799. After adjusting for case mix, the mean payment is $20,207.
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. This measure is currently reported on Hospital Compare.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure would maintain the statutory requirement that measures in VBP be drawn from the IQR measure set. This measure addresses a condition not currently covered in the VBP program measure set. This measure would enhance the Efficiency domain of the program which currently includes only one measure. While this measure may overlap with the Medicare Spending Per Beneficiary measure currently in the VBP program, MAP has previously indicated its support for the more granular information than provided by the MSPB measure.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
In 2012 total Medicare expenditures were $574.2 billion, representing 3.6% of gross domestic product (GDP). Current estimates suggest that Medicare spending will increase to 5.6% of GDP by 2035 due to both an increase in the Medicare population as well as Medicare spending on each beneficiary [1]. The growth in Medicare spending is unsustainable and highlights the need to create incentives for high value care. A critical first step in moving toward high value care is to define an approach to calculate costs that is transparent to consumers and fair to providers. AMI is a condition with a substantial range in costs of care and for which there are well-established publicly reported quality measures; therefore, it is an ideal condition for assessing relative value for an episode of care that begins with an acute hospitalization. A measure of payments for Medicare patients during an episode of care for AMI aligned with current quality of care measures will facilitate profiling hospital value (payments and quality). This measure, which uses standardized payments, reflects differences in the management of care for patients with AMI both during hospitalization and immediately post-discharge. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care. References: 1. Boards of Trustees of the Federal Hospital Insurance and Federal Supplementary Medical Insurance Trust Funds, 2013 Annual Report, May 31, 2013. 2. Andrews RM, Elixhauser, A. The National Hospital Bill: Growth Trends and 2005 Update on the Most Expensive Conditions by Payer. Agency for Healthcare Research and Quality. 2007.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Endorsing Cost and Resource Use Measures: Phase 2
  
  
• Review for Importance: 1a. High Priority, 1b. Opportunity for Improvement, 1c. Measure Intent)IM.1. High Priority: H-20; M-1; L-0; I-0 IM.2. Opportunity for Improvement: H-10; M-10; L-0; I-1 IM.3. Measure Intent: H-16; M-5; L-0; I-0 Overall Importance: H-16; M-5; L-0; I-0Rationale:• The Committee agreed that Acute Myocardial Infarction (AMI) is a high-priority area for measurement because it is a common condition that drives spending in hospitals.• The Committee questioned the opportunity for improvement because the inner quartile of performance gets very narrow after risk adjustment. The developers responded that this measure is intended to be paired with quality measures and that the opportunity for improvement must be considered with the opportunity to improve the quality of care when factoring in the cost of the care provided.• Additionally, the Committee was concerned with the attribution of post-acute expenses to the admitting hospital. The developers responded that it is critical to capture those costs because the current system is setup to incentivize pushing those payments out into the post-discharge time period. Hospitals can act as catalysts in their communities for improving care and health decision-making. | The Committee raised a question about the episode definition as 30 days from the date of admission and the potential need for alignment with the Medicare Spending per Beneficiary (MSPB) measure that defines a period of 30 days post-discharge. The developers responded that these specifications are aligned with a corresponding AMI mortality measure to be used together to assess value.
  
  
• Review for Scientific Acceptability: 2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-3; M-16; L-2; I-0 2b. Validity: H-0; M-9; L-7; I-4Rationale:• The Committee raised concern about the ability to assess performance of low volume hospitals given the hierarchical modeling approach and the potential implications it could pose for the reliability and validity of the measure. The developers responded that at lower patient volumes, the less certainty you have about your estimates for cost. This measure uses a continuous outcome so the estimate is more accurate than a binary outcome. Additionally, this measure uses hierarchical risk modeling that adjusts hospitals with low patient volume towards the mean. Furthermore, reporting is only done for hospitals that have 25 or more cases.• The Committee further questioned the decision to attribute the entire cost of an episode to the initial hospital in the case of a transfer to another facility. The developers responded that the decision was made not to exclude these cases because transfers account for approximately 8 percent of AMI episodes. This represented too many cases to exclude. Furthermore, the initial hospital begins the episode of care and can have a great influence over the coordination of care.• The Committee raised concerns about whether the supplied reliability testing was done with the amount of data required by the specification of the measure. The measure is specified for a 12-month period and the testing used combined 2008 and 2009 data. The developers responded that the measure will eventually be implemented with three years of data but when the testing was performed, only two years of data was available. The decision to include three years of data was made to include as many hospitals in the measurement as possible. Many hospitals do not have 25 AMI cases in a year and would therefore not meet the threshold for reporting.• In addition to the risk adjustment provided in the overarching issues section, the Committee was concerned that the developer did not do empiric measure-level validity testing for the measure as specified. The developers acknowledged that they relied on prior research on risk adjustment testing for mortality measures and also relied on face validity testing with their technical expert panel.
  
  
• Review for Feasibility: H-18; M-3; L-0; I-0(3a. Byproduct of Care Processes; and 3b. Electronic sources; and 3c. Data Collection Strategy)Rationale:• The Committee had no concerns about the feasibility of the measure.
  
  
• Review for Usability: H-12; M-7; L-2; I-0(4a. Accountability/transparency (used in accountability w/in 3 yr, public reporting w/in 6 yr, or if new - credible plan); and 4b. Improvement – progress demonstrated (if new - credible rationale); and 4c. Unintended Consequences - benefits outweigh evidence of unintended negative consequences (to patients/populations); and 4d. Measure Deconstruction – can be deconstructed to facilitate transparency and understanding)Rationale:• The Committee raised concern about the number of hospitals falling in the “average” range for the measure – 78 percent. 15 percent were rated “high” and 7 percent “low”.• The Committee did appreciate the data breakdown provided to hospitals as a result of the measure.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments: April 21, 2014 – May 21, 2014Several supportive comments for the measure were received, with commenters indicating that the measure addresses an area of high morbidity, mortality, and healthcare costs. Commenters stated that information shared by CMS with hospitals will allow for identification of high/low cost areas and focused improvement. Additionally, commenters raised several issues with the measure, which were discussed during the in-person meeting:
  • Appropriateness of attribution approach
    • Commenters stated that attributing the cost of the entire episode to the admitting hospital may be inappropriate to attribute the cost of the episode to the hospital as much of the care happens in an outpatient setting. Commenters stated that measures should assess processes and outcomes over which the measured entity (e.g., hospital, physician group) can exercise a reasonable level of control, and that these measures may be more appropriate for an organization accepting bundled payments on behalf of all measured entities.
    • The Committee acknowledged this concern; however, the Committee stated that increasingly hospitals are responsible for care delivered up to 30 days after discharge. Consequently, hospitals are in the unique position of being able to push coordination of care, and this measure may serve as an impetus for this to occur.
  • Adequacy of risk adjustment model
    • Several commenters stated that the low r-squared values for the measure (0.05) indicated that the risk model did not account for enough of the variation in measure scores and may not adequately account for patient case mix and severity. Moreover, commenters believe that the low level of reliability demonstrated illustrated another fundamental flaw of both measures—that they fail to adequately account for complicating conditions that patients have prior to an episode of care.
    • The developers explained that at lower patient volumes, there is less certainty when estimating cost. The measure uses a continuous outcome which results in a more accurate estimate than would result from a binary outcome. Additionally, the measure uses hierarchical risk modeling that adjusts hospitals with low patient volume towards the mean. o Approach to addressing transfer patients Several commenters stated concern that the initial admitting hospital would be attributed cost for the episode when transferring patients to a second hospital, as the initial admitting hospital may have little control over the care that happens after the transfer.
    • The Committee acknowledged this concern; however, the Committee stated that increasingly hospitals are responsible for care delivered up to 30 days after discharge.
  • Risk adjustment for socio-demographic factors
    • Several commenters stated that the risk adjustment models for the measures should capture socio-demographic factors, as there is robust evidence that such factors affect health outcomes, including resource use.
    • NQF acknowledged these concerns and clarified that NQF is in the early stages of reviewing our policy on risk adjusting for socio-demographic factors. The report referenced is a draft report that has recently been reviewed during an NQF member and public comment period; the recommendations have not yet been finalized. As such, we ask that Committees continue to evaluate measures according to our current guidelines, that measures not be adjusted for socio-demographic variables. If in the future the recommendations for adjusting for socio-demographic variables become NQF policy, measures needing this adjustment will be updated and reviewed by the Committee through measure maintenance.
    • The Committee acknowledged that the timing of the NQF risk adjustment report is not ideal; however, given the current NQF policy on adjusting for sociodemographic variables, the Committee requested that a recommendation be issued with the measure that when reported, the results should be stratified by sociodemographic variables.
  
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-12; N-9 [Consensus not reached]• After considering all comments and thorough discussion, the Committee requested the opportunity to revote on endorsement for the measure. The results of that vote are below:o Yes- 14; No-7• The measure is recommended for endorsement and pursuant with NQF process will be posted for NQF member voting. 7. NQF Member Voting: June 17, 2014-July 2, 2014• Representatives of 17 member organizations voted.• With 40% of the councils approving the measure, the voting results indicated that consensus was not reached among the membership.• To further understand the rationale for the membership votes, NQF hosted conference calls with council leaders and NQF members to further discuss the issues.o 73 participants from 7 councils with broad distribution across the councils attended the membership call.o Staff compiled the major themes that arose from these consensus-building calls and shared them with the CSAC. 8. Consensus Standards Approval Committee (CSAC) Vote: August 12, 2014, Y-10; N-3• The Consensus Standards Approval Committee (CSAC) pulled this measure on July 10, 2014, to further discuss NQF Member voting results indicating that consensus was not reached. • NQF hosted a call on July 31, 2014 for members to discuss their concerns about the measure.• CSAC reviewed the member voting results and themes from the membership call and endorsed this measure. 9. Board of Directors (BOD) Vote: November 5, 2014• The BOD ratified endorsement with the following conditions:o One- year Look Back Assessment of Unintended Consequences: NQF staff will work with Cost and Resource Standing Committee and CMS to determine a plan for assessing potential unintended consequences of this measure in use. The evaluation of unintended consequences will be initiated in approximately one year and possible changes to the measures based on this data.o Consideration for SDS trial period: The Cost and Resource Use Standing Committee will consider whether the measure should be included in the NQF trial period for sociodemographic status adjustments.o Attribution: NQF will consider opportunities to address the attribution issue. 10. Appeals: November 7, 2014- December 9, 2014• NQF received an appeal for this measure from the American College of Cardiology (ACC). The appeallants noted concerns with attribution, the use of stand-alone cost measures and the adjustment for sociodemographic variables.• CSAC reviewed the appeal on January 13, 2015, and voted to uphold endorsement (92% approval).• The BOD Executive Committee reviewed the appeal on February 4, 2015, and voted to uphold endorsement.
  
  

Measure Specifications

• NQF Number (if applicable): 2436
  
  
• Description: This measure estimates a hospital-level, risk-standardized payment for a heart failure episode-of-care starting with inpatient admission to a short term acute-care facility and extending 30 days post-admission for Medicare fee-for-service (FFS) patients who are 65 years of age or older with a principal discharge diagnosis of heart failure.
  
  
• Numerator: Note: This outcome measure does not have a traditional numerator and denominator. We are using this field to define the outcome. The outcome for this measure is a hospital-level, risk-standardized payment for Medicare patients for a heart failure episode of care. The payment timeframe starts from the admission date of an index hospitalization through 30 days post-admission. We include payments for the index admission, as well as payments for subsequent inpatient, outpatient, skilled nursing facility, home health, hospice, physician/clinical laboratory/ambulance services, supplier Part B items, and durable medical equipment, prosthetics/orthotics, and supplies. In order to compare payments for Medicare patients related to clinical care, we remove geography and policy adjustment from our payment calculation whenever possible. If the data for a specific care setting do not allow for the removal of these adjustments, we calculate an average payment for each item across all geographic areas and replace the claim payment amount in the data with the average payment amount for that item.
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The measure cohort includes admissions to non-federal, short-stay, acute-care hospitals for Medicare FFS patients aged 65 years and older with a principal discharge diagnosis of HF. Patients must also have continuous enrollment in Medicare Part A and Part B benefits for the 12 months prior to the index admission and 30 days post- admission.
  
  
• Exclusions: 1. Incomplete administrative data in the 30 days following the index admission if discharged alive 2. Discharged alive on the day of admission or the following day who were not transferred 3. Inconsistent or unknown patient vital status, or other unreliable demographic data (age and gender) 4. Admissions where patients are discharged against medical advice (AMA) 5. Enrolled in the Medicare hospice program any time in the 12 months prior to the index admission, including the first day of the index admission 6. Transferred to federal hospitals 7. Missing index diagnosis-related group (DRG) weight and provider received no payment 8. Hospitalizations for patients who receive a heart transplant during the episode of care 10. Hospitalizations for patients who receive a Left Ventricular Assist Device (LVAD) during the episode of care
  
  
• HHS NQS Priority: Making Care Affordable
  
  
• HHS Data Source: Administrative claims. The measure uses Medicare administrative claims data and enrollment information. Medicare administrative claims data for certain Part A and Part B services in the 12 months prior to and during the index admission are used for risk adjustment. The data also contain price-standardized payments for Medicare patients across multiple care settings, services, and supplies (i.e., inpatient, outpatient, SNF, home health, hospice, physician/clinical laboratory/ambulance services, and durable medical equipment, prosthetics/orthotics, and supplies). The price-standardized payment data element is harmonized across CMS cost and resource use measures.
  
  
• Measure Type: Cost/Resource Use
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Do not support
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:This measure addresses the cost of care for a common condition. Heart failure is a common condition and one of the leading causes of hospitalization for Americans over 65 years old. Costs related to heart failure total approximately $34 billion annually. Unadjusted 30 day episode of care payments for heart failure have been found to range significantly. Payments range from $6,865 to $26,696 with a mean of $13,081. Use of this measure could drive improvement in variation in costs related to quality of care.
  
  
  
• Does the measure address a program goal or objective? Yes. ? This measure addresses the VBP priority domain of Making Care Affordable. This measure has been finalized for use in the Hospital IQR program in FY 2018. To be added to the VBP program, this measure must be included in IQR and reported on the Hospital Compare website for at least 1 year prior to use in the VBP program.
  
  
• Is this a high-value measure? Yes. Heart failure is a common condition and one of the leading causes of hospitalization for Americans over 65 years old. Costs related to heart failure total approximately $34 billion annually. Unadjusted 30 day episode of care payments for heart failure have been found to range significantly. Payments range from $6,865 to $26,696 with a mean of $13,081.
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. This measure is currently reported on Hospital Compare.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Medicare spending is estimated to have been $525.0 billion in 2010 with annual growth rates projected to be 6.3% for 2013 through 2020 due to both an increase in the Medicare population as well as Medicare spending on each beneficiary [1]. Further projections anticipate an exhaustion of Medicare‘s Hospital Insurance Trust Fund (Part A) by 2024 [2]. The growth in spending is unsustainable and highlights the need to understand the value of care Medicare buys with every dollar spent. Given the urgency of the state of the Medicare Hospital Insurance Trust Fund and the fact that Medicare pays for 40-50% of hospitalizations nationally [3], hospital costs are a natural venue in which to deconstruct payments for Medicare patients. Yet payments to hospitals are difficult to interpret in isolation. Some high payment hospitals may have better clinical outcomes when compared with low payment hospitals; other high payment hospitals may not. For this reason, the value of hospital care is more clearly assessed when pairing hospital payments with hospital quality. A measure of payments for Medicare patients to hospitals that is aligned with current quality of care measures will facilitate profiling hospital value (payments and quality). This measure will reflect differences in the management of care for patients with heart failure both during hospitalization and immediately post-discharge. Heart failure is a condition with substantial range in costs of care and for which there are well-established publicly reported quality measures and is therefore an ideal condition for assessing relative value for an episode-of-care that begins with an acute hospitalization. By focusing on one specific condition, value assessments may provide actionable feedback to hospitals and incentivize targeted improvements in care. 1. Ash AS, Byrne-Logan S. How Well Do Models Work? Predicting Health Care Costs. Proceedings of the Section on Statistics in Epidemiology. American Statistical Association. 1998. 2. Medpac. Report to the Congress: Medicare Payment Policy 9/17/12 2012. 3. National Hospital Discharge Survey. http://www.cdc.gov/nchs/nhds.htm. Accessed 08/07/2012.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Endorsing Cost and Resource Use Measures: Phase 2
  
  
• Review for Importance: IM.1. High Priority; IM.2. Opportunity for Improvement; and IM.3. Measure Intent)IM.1. High Priority: H-14; M-4; L-3; I-0 IM.2. Opportunity for Improvement: H-11; M-9; L-1; I-0 IM.3. Measure Intent: H-11; M-9; L-1; I-0 Overall Importance: H-8; M-13; L-0; I-0Rationale: The Committee agreed that Heart Failure (HF) is a high-priority area for measurement because it is a common condition that drives spending in hospitals and systems.
  
  
• Review for Scientific Acceptability: 2. Scientific Acceptability of Measure Properties(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-7; M-11; L-2; I-1 2b. Validity: H-0; M-9; L-6; I-5Rationale:• The Committee questioned the description of a “typical heart failure” patient considering that many patients have chronic heart failure and a hospitalization occurs for an acute incidence of the disease. The developer responded that they meant non-LVAD, non-transplant, non-major surgical procedure heart failure patients. These conditions dramatically change the payment outcome. They are sicker patients and were excluded from the measure.• The Committee also questioned the methodology for choosing the index admission for patients who might have multiple hospitalizations in the same year for heart failure. The developer responded that the hospitalization is randomly selected and any re-hospitalization within 30 days of that index admission would be considered a re-admission and counted in the total hospitalization cost.• The Committee expressed concern that attributing costs to hospitals was inappropriate for heart failure patients and that the real accountability should be with the ambulatory providers. Furthermore, the 30-day time period for costs does not align with the typical disease progression for a heart failure patient. A longer period, perhaps 12 months, would be more appropriate for the chronic nature of this disease.• The developer defended the attribution to the hospital by stating that heart failure is a leading cause of hospitalization for the elderly and it represented a high-leverage opportunity to measure and evaluate spending. Additionally, the 30-day time period was short enough that the associated spending would be attributable to the hospital admission.• In addition to the risk adjustment discussion provided in the overarching issues section, the Committee was concerned that the developer did not do empiric measure-level validity testing for the measure as specified. The developers acknowledged that they relied on prior research on risk adjustment testing for mortality measures and also relied on face validity testing with their technical expert panel.
  
  
• Review for Feasibility: 3. Feasibility: H-16; M-3; L-0; I-0(3a. Byproduct of Care Processes; and 3b. Electronic sources; and 3c. Data Collection Strategy)Rationale:• The Committee had no concerns about the feasibility of the measure.
  
  
• Review for Usability: 4. Use and Usability: H-4; M-10; L-6; I-1(4a. Accountability/transparency (used in accountability w/in 3 yr, public reporting w/in 6 yr, or if new - credible plan); and 4b. Improvement – progress demonstrated (if new - credible rationale); and 4c. Unintended Consequences - benefits outweigh evidence of unintended negative consequences (to patients/populations); and 4d. Measure Deconstruction – can be deconstructed to facilitate transparency and understanding)Rationale:• The Committee had no concerns about the Use and Usability of the measure.
  
  
• 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: April 21, 2014 – May 21, 2014• Several supportive comments for the measure were received, with commenters indicating that the measure addresses an area of high morbidity, mortality, and healthcare costs. Commenters stated that information shared by CMS with hospitals will allow for identification of high/low cost areas and focused improvement. Additionally, commenters raised several issues with the measure, which were discussed during the in-person meeting:o Appropriateness of attribution approach§ Commenters stated that attributing the cost of the entire episode to the admitting hospital may be inappropriate to attribute the cost of the episode to the hospital as much of the care happens in an outpatient setting. Commenters stated that measures should assess processes and outcomes over which the measured entity (e.g., hospital, physician group) can exercise a reasonable level of control, and that these measures may be more appropriate for an organization accepting bundled payments on behalf of all measured entities.§ The Committee acknowledged this concern; however, the Committee stated that increasingly hospitals are responsible for care delivered up to 30 days after discharge. Consequently, hospitals are in the unique position of being able to push coordination of care, and this measure may serve as an impetus for this to occur.o Adequacy of risk adjustment model§ Several commenters stated that the low r-squared values for the measure (0.03) indicated that the risk model did not account for enough of the variation in measure scores and may not adequately account for patient case mix and severity. Moreover, commenters believe that the low level of reliability demonstrated illustrated another fundamental flaw of both measures—that they fail to adequately account for complicating conditions that patients have prior to an episode of care.§ The developers explained that at lower patient volumes, there is less certainty when estimating cost. The measure uses a continuous outcome which results in a more accurate estimate than would result from a binary outcome. Additionally, the measure uses hierarchical risk modeling that adjusts hospitals with low patient volume towards the mean.o Approach to addressing transfer patients§ Several commenters stated concern that the initial admitting hospital would be attributed cost for the episode when transferring patients to a second hospital, as the initial admitting hospital may have little control over the care that happens after the transfer.§ The Committee acknowledged this concern; however, the Committee stated that increasingly hospitals are responsible for care delivered up to 30 days after discharge.o Risk adjustment for socio-demographic factors§ Several commenters stated that the risk adjustment models for the measures should capture socio-demographic factors, as there is robust evidence that such factors affect health outcomes, including resource use.§ NQF acknowledged these concerns and clarified that NQF is in the early stages of reviewing our policy on risk adjusting for socio-demographic factors. The report referenced is a draft report that has recently been reviewed during an NQF member and public comment period; the recommendations have not yet been finalized. As such, we ask that Committees continue to evaluate measures according to our current guidelines, that measures not be adjusted for socio-demographic variables. If in the future the recommendations for adjusting for socio-demographic variables become NQF policy, measures needing this adjustment will be updated and reviewed by the Committee through measure maintenance.§ The Committee acknowledged that the timing of the NQF risk adjustment report is not ideal; however, given the current NQF policy on adjusting for sociodemographic variables, the Committee requested that a recommendation be issued with the measure that when reported, the results should be stratified by sociodemographic variables.• After considering all comments and thorough discussion, the Committee requested the opportunity to revote on endorsement for the measure. The results of that vote are below:o Yes- 13; No-8• The measure is recommended for endorsement and pursuant with NQF process will be posted for NQF member voting.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-10; N-11 [Consensus not reached] After considering all comments and thorough discussion, the Committee requested the opportunity to revote on endorsement for the measure. The results of that vote are below:o Yes- 13; No-8• The measure is recommended for endorsement and pursuant with NQF process will be posted for NQF member voting. 7. NQF Member Voting: June 17, 2014- July 2, 2014• Representatives of 17 member organizations voted.• With 40% of the councils approving the measure, the voting results indicated that consensus was not reached among the membership.• To further understand the rationale for the membership votes, NQF hosted conference calls with council leaders and NQF members to further discuss the issues.o 73 participants from 7 councils with broad distribution across the councils attended the membership call.o Staff compiled the major themes that arose from these consensus-building calls and shared them with the CSAC. 8. Consensus Standards Approval Committee (CSAC) Vote: August 12, 2014, Y-10; N-3• The Consensus Standards Approval Committee (CSAC) pulled this measure on July 10, 2014, to further discuss NQF Member voting results indicating that consensus was not reached.• NQF hosted a call on July 31, 2014 for members to discuss their concerns about the measure.• CSAC reviewed the member voting results and themes from the membership call and endorsed this measure. 9. Board of Directors Vote: November 5, 2014• The EC ratified endorsement with the following conditions:o One- year Look Back Assessment of Unintended Consequences: NQF staff will work with Cost and Resource Standing Committee and CMS to determine a plan for assessing potential unintended consequences of this measure in use. The evaluation of unintended consequences will be initiated in approximately one year and possible changes to the measures based on this data.o Consideration for SDS trial period: The Cost and Resource Use Standing Committee will consider whether the measure should be included in the NQF trial period for sociodemographic status adjustments. 10. Appeals: November 7, 2014- December 9, 2014• NQF received an appeal for this measure from the American College of Cardiology (ACC). The appeallants noted concerns with attribution, the use of stand-alone cost measures and the adjustment for sociodemographic variables.• CSAC reviewed the appeal on January 13, 2015, and voted to uphold endorsement (92% approval).• The BOD Executive Committee reviewed the appeal on February 4, 2015, and voted to uphold endorsement.
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: This measure estimates hospital-level, risk-standardized payments for a primary elective total THA/TKA episode of care starting with inpatient admission to a short term acute-care facility for Medicare fee-for-service (FFS) patients who are 65 years of age or older.
  
  
• Numerator: This outcome measure does not have a traditional numerator and denominator. We are using this field to define the outcome. The outcome for this measure is a hospital-level, risk-standardized payment for Medicare patients for a primary elective total THA/TKA episode of care. The payment timeframe starts from the admission date of an index hospitalization through 90 days post-admission. We include payments for the index admission, as well as payments for subsequent inpatient, outpatient, skilled nursing facility, home health, hospice, physician/clinical laboratory/ambulance services, supplier Part B items, and durable medical equipment, prosthetics/orthotics, and supplies. In order to compare payments for Medicare patients related to clinical care, we remove geography and policy adjustment from our payment calculation whenever possible. If the data for a specific care setting do not allow for the removal of these adjustments, we calculate an average payment for each item across all geographic areas and replace the claim payment amount in the data with the average payment amount for that item
  
  
• Denominator: This outcome measure does not have a traditional numerator and denominator. We use this field to define the measure cohort. The measure cohort includes admissions to non-federal, short-stay, acute-care hospitals for Medicare FFS patients aged 65 years and older with a qualifying THA/TKA procedure, not transferred in from another facility. Patients must also have continuous enrollment in Medicare Part A and Part B benefits for the 12 months prior to the index admission and 90 days post-admission.
  
  
• Exclusions: 1) Patients without complete administrative data in the 90 days following the index admission, if alive 2) Patients with no payment information during the index admission 3) Patients discharged against medical advice (AMA) 4) Patients transferred to federal hospitals 5) Patients with more than two THA/TKA procedure codes during the admission 6) Patients transferred into the hospital
  
  
• HHS NQS Priority: Making Care Affordable
  
  
• HHS Data Source: Administrative claims. The measure was developed using claims data from seven standard analytic files contained in the Chronic Condition Warehouse (CCW) data. The CCW data are derived from the Medicare claims in the Standard Analytic Files. The CCW data contain data from the Medicare FFS institutional and non-institutional claims, enrollment and eligibility information, and assessment data for up to 100% of the Medicare FFS beneficiary population for particular conditions and procedures. The data are organized by predefined chronic conditions, but can also be used to define individualized patient cohorts, as described below. The annual CCW datasets include claims data from all seven standard files (inpatient, skilled nursing facility, outpatient, home health agency, hospice, carrier, and durable medical equipment) that can be linked across care settings, services, supplies, and years using a unique patient identifier. Specific information available in the CCW data includes diagnosis codes, procedure codes, quantity/units of services used, and payments made by CMS, patients, and other insurers to providers.
  
  
• Measure Type: Cost/Resource Use
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:This measure addresses the cost of care for a common condition. Over 33% of Americans 65 and older suffer from osteoarthritis. Joint replacement surgeries are becoming more commonly utilized as Medicare covered 337,419 THA procedures and 750,569 TKA procedures between 2009 and 2012 and annual Medicare payments for THA and TKA exceed $15 billion annually. There is significant variation in costs for these procedures that are often related to quality of care as complications and readmissions increase the total payment for post-surgical care. The mean 90-day risk-standardized payment among Medicare FFS patients with a qualifying THA/TKA procedure in 2010–2012 was$23,248, and ranged from $16,421 to$35,12. Use of this measure could drive improvement in variation in costs related to quality of care.
  
  
  
• Does the measure address a program goal or objective? Yes. ? This measure addresses the VBP priority domain of Making Care Affordable. This measure has been finalized for use in the Hospital IQR program in FY 2018. To be added to the VBP program, this measure must be included in IQR and reported on the Hospital Compare website for at least 1 year prior to use in the VBP program.
  
  
• Is this a high-value measure? Yes. This measure addresses the cost of care for a common condition. Over 33% of Americans 65 and older suffer from osteoarthritis. Joint replacement surgeries are becoming more commonly utilized as Medicare covered 337,419 THA procedures and 750,569 TKA procedures between 2009 and 2012 and annual Medicare payments for THA and TKA exceed $15 billion annually. There is significant variation in costs for these procedures that are often related to quality of care as complications and readmissions increase the total payment for post-surgical care. The mean 90-day risk-standardized payment among Medicare FFS patients with a qualifying THA/TKA procedure in 2010–2012 was$23,248, and ranged from $16,421 to$35,12.
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No. This measure has been finalized for the IQR FY 2018 measure set.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? No. Never Submitted
  
  

Rationale for measure provided by HHS
Due to their frequency and cost, THA and TKA are priority areas for outcome measure development. More than one third of the US population 65 years and older suffers from osteoarthritis [1]. Between 2009 and 2012, there were 337,419 THA procedures and 750,569 TKA procedures for Medicare fee-for-service patients 65 years and older [2]. Estimates place the annual insurer cost of osteoarthritis in the US at $149 billion, with Medicare direct payments to hospitals for THA/TKA exceeding $15 billion annually [3]. Further, there are conflicting data regarding costs after total joint arthroplasty, with evidence to support both increased [4] and decreased costs [5] following arthroplasty, suggesting there is great variation in the costs of a full episode of care for THA and TKA. The goal of hospital-level resource use measurement is to capture the full spectrum of care in order to incentivize collaboration and shared responsibility for improving patients’ health and reducing the burden of their disease. Variation in the cost of a THA or TKA episode of care is often related to the quality of care, where complications and readmissions increase the total payment for post-surgical care. Given the well-documented variation in readmission and complication rates following THA and TKA, there is expected variation in total episode of care costs for the procedures [6]. Birkmeyer et al. found that the average 30-day cost increased by $2,436 among hospitals with the highest quintile of complication rates, compared to the lowest quintile following THA [7]. The same study also found that rehabilitation costs accounted for 50% of “excess” payments among those undergoing THA. Miller et al. found that a major driver of differences in episode payments for THA was that hospitals within Accountable Care Organizations (ACO) had smaller payments for post-discharge care compared to non-ACO hospitals [8]. Taken together, these studies suggest that much of the variation in total episode costs arises in the post-acute setting. Health systems have taken notice of opportunities to improve value by encouraging collaboration of care between hospitals and post-acute providers. [10]. Transparency regarding the variation of episode of care payments triggered by THA and TKA helps to guide health systems and providers towards improvement in the value of care. 1. Centers for Disease Control and Prevention (CDC). Osteoarthritis. 2011; http://www.cdc.gov/arthritis/basics/osteoarthritis.htm. Accessed August 13, 2013. 2. Suter LG, Grady JN, Lin Z, et al. 2013 Measure Updates and Specifications: Elective Primary Total Hip Arthroplasty (THA) And/Or Total Knee Arthroplasty (TKA) All-Cause Unplanned 30-Day Risk-Standardized Readmission Measure (Version 2.0). March 2013. 3. Miller DC, Gust C, Dimick JB, Birkmeyer N, Skinner J, Birkmeyer JD. Large variations in Medicare payments for surgery highlight savings potential from bundled payment programs. Health affairs (Project Hope). Nov 2011;30(11):2107-2115. 4. Bozic KJ, Stacey B, Berger A, Sadosky A, Oster G. Resource utilization and costs before and after total joint arthroplasty. BMC health services research. 2012;12:73. 5. Hawker GA, Badley EM, Croxford R, et al. A population-based nested case-control study of the costs of hip and knee replacement surgery. Med Care. 2009;47(7):732-741. 6. Suter LG, et al., Medicare Hospital Quality Chartbook 2013: Performance Report on Outcome Measures, 2013. 7. Birkmeyer JD, Gust C, Dimick JB, Birkmeyer NJ, Skinner JS. Hospital quality and the cost of inpatient surgery in the United States. Annals of surgery. 2012;255(1):1-5. 8. Miller DC, Ye Z, Gust C, Birkmeyer JD. Anticipating the effects of accountable care organizations for inpatient surgery. JAMA surgery. Jun 2013;148(6):549-554. 9. CMS. Bundled Payments for Care Improvement (BPCI) Initiative: General Information. http:/ / innovation.cms.gov/initiatives/bundled?payments/ [accessed Jan 7, 2014] 10. Miller DC, Ye Z, Gust C, Birkmeyer JD. Anticipating the effects of accountable care organizations for inpatient surgery. JAMA surgery. Jun 2013;148(6):549-554.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure constructs a clinically coherent group of services to inform providers about resource use and effectiveness. It sums Parts A and B payments related to a kidney/urinary tract infection IP stay and attributes them to the hospital where the index IP stay occurred.
  
  
• Numerator: The numerator of the Kidney/Urinary Tract Infection Clinical Episode-Based Payment Measure is the risk-adjusted sum of a provider’s spending and the preadmission and post-discharge medical services that are clinically related to kidney/urinary tract infection across a hospital’s eligible Kidney/Urinary Tract Infection episodes during the period of performance. A clinical episode begins 3 days prior to the initial (i.e., index) admission and extends 30 days following the index hospital stay discharge date.
  
  
• Denominator: A count of the provider’s condition-specific episodes during the period of performance.
  
  
• Exclusions: Episode Exclusions: 1. Beneficiaries who do not have continuous enrollment in Medicare Parts A and B from 90 days prior to IP admission through the end of the episode with Medicare as the primary payer. 2. Beneficiaries who enroll in Medicare Advantage during the period that starts 90 days prior to IP admission through the end of the episode.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Efficiency
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would add another measure to the Efficiency domain of the program. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. However, this measure would overlap with the current Medicare Spending Per Beneficiary Measure and MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  • Impact on quality of care for patients:CMS has noted that the variations in cost associated with treating kidney/urinary tract infections are the result of post discharge costs that reflect variations in quality. An episode-based approach could help drive improvement in both cost and quality. (http://content.healthaffairs.org/content/28/5/1406.full.pdf)
  
  
  
• Does the measure address a program goal or objective? Yes. This measure addresses the VBP priority domain of Making Care Affordable. This measure has been finalized for use in the Hospital IQR program in FY 2019. To be added to the VBP program, this measure must be included in IQR and reported on the Hospital Compare website for at least 1 year prior to use in the VBP program.
  
  
• Is this a high-value measure? Yes. Urinary tract infections (UTIs) are mainly treated on an outpatient basis but the cost of care can be high if hospitalization and follow-up is required. UTIs are the second most common type of infection however; vast the majority of these infections are treated in an outpatient setting, not in a hospital. UTIs are responsible for approximately eight million visits to health care providers annually and about 200,000 of those results in hospitalization. There is substantial variation in episode costs ranging from approximately $4,800 at the 5th percentile to approximately $27,000 at the 95th.
  
  
• Does this measure fill a gap in the program measure set? No. A measure currently in the program, NQF #2151 Medicare Spending per Beneficiary addresses the NQF priority of making care affordable and the CMS high priority domains of effectuating changes in effectuating changes in efficiency and rewarding value over volume.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No. This measure has been finalized for the IQR FY 2019 measure set.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? No. A similar measure, NQF #2151 Medicare Spending Per Beneficiary (MSPB), is already in the program. NQF #2151 captures a broader population than the MUC, which is procedure specific.MAP has previously advocated keeping a parsimonious set of measures for the VBP program to avoid rewarding or penalizing a provider mulitple times for the same case.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  

Rationale for measure provided by HHS
Episode-based performance measurement allows meaningful comparisons between providers based on resource use for certain clinical conditions or procedures, as noted in the NQF report for the “Episode Grouper Evaluation Criteria” project (available at http://www.qualityforum.org/Publications/2014/09/Evaluating_Episode_Groupers__A_Report_from_the_National_Quality_Forum.aspx) and in various peer-reviewed articles (e.g., Hussey, P. S., Sorbero, M. E., Mehrotra, A., Liu, H., & Damberg, S. L. (2009). Episode-Based Performance Measurement and Payment: Making It a Reality. Health Affairs, 28(5), 1406-1417. doi:10.1377/hlthaff.28.5.1406). While reliability analyses have been conducted on similar performance measures, we plan to conduct our own reliability analysis for this specific measure and propose a minimum number of cases for reporting. The analysis will likely mirror the 2012 MSPB reliability analysis: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/hospital-value-based-purchasing/Downloads/MSPBReliabilityAnalysis-Jul-18-12.pdf

Measure Specifications

• NQF Number (if applicable): 531
  
  
• Description: Patient Safety and Adverse Events Composite (Patient Safety Indicator, or PSI90) is a composite measure of 10 individual PSIs, each measuring a different aspect of harm associated with patient safety. Each PSI is reliability-adjusted (smoothed) and indirectly standardized (risk adjusted). The composite is the weighted average of the reliability-adjusted, indirectly standardized, observed-to-expected ratios for component indicators. The final weight for each component is the product of harm weights and volume weights (numerator weights). Harm weights are calculated by multiplying empirical estimates of excess harms associated with the patient safety event by utility weights linked to each of the harms. Excess harms are estimated using statistical models comparing patients with a safety-related event to those without that safety-related event in a CMS Medicare fee-for-service sample that allowed up to one year of follow-up from the discharge date of the hospital stay associated with the index event. Volume weights, the second part of the final weight, are calculated on the basis of the number of safety-related events for the component indicators in the all-payer reference population. The observed to expected ratios (indirect standardization) of the reliability adjusted (smoothed) rates are multiplied by a component weight and the weighted scores are summed to determine the final PSI 90 score. A score of 1 means that the hospital performs as expected, scores greater than one indicate worse performance than expected.
  
  
• Numerator: Below we list the numerator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for pressure ulcer and any secondary ICD-9-CM diagnosis codes for pressure ulcer stage III or IV (or unstageable). PSI06-Iatrogenic Pneumothorax Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for iatrogenic pneumothorax. PSI08-Postoperative Hip Fracture Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for hip fracture. PSI09-Perioperative Hemorrhage and Hematoma Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for perioperative hemorrhage or hematoma and any-listed ICD-9-CM procedure codes for control of perioperative hemorrhage or evacuation of hematoma. PSI10-Postoperative Acute Kidney Injury Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis codes for acute renal failure and any-listed ICD-9- CM procedure codes for dialysis. PSI11-Postoperative Respiratory Failure Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with either: • any secondary ICD-9-CM diagnosis code for acute respiratory failure; or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for 96 consecutive hours or more that occurs zero or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a mechanical ventilation for less than 96 consecutive hours (or undetermined) that occurs two or more days after the first major operating room procedure code (based on days from admission to procedure); or • any-listed ICD-9-CM procedure codes for a reintubation that occurs one or more days after the first major operating room procedure code (based on days from admission to procedure). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with a secondary ICD-9-CM diagnosis code for deep vein thrombosis or a secondary ICD-9-CM diagnosis code for pulmonary embolism (omitting cases from the numerator with isolated calf vein DVT). PSI13-Postoperative Sepsis Rate- Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for sepsis. PSI14-Postoperative Wound Dehiscence Rate-Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any-listed ICD-9-CM procedure codes for reclosure of postoperative disruption of the abdominal wall. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate -Discharges, among cases meeting the inclusion and exclusion rules for the denominator, with any secondary ICD-9-CM diagnosis codes for accidental puncture or laceration during a procedure and second abdominopelvic operation 1 day or more after the index procedure.
  
  
• Denominator: Below we list the denominator values for the composite components. The composite score is calculated as a ratio of the weighted observed to expected ratios for each of the components. PSI03-Pressure Ulcer Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI06-Iatrogenic Pneumothorax Rate- Surgical and medical discharges, for patients ages 18 years and older. Surgical and medical discharges are defined by specific DRG or MS-DRG codes. PSI08-Postoperative Hip Fracture Rate- Surgical discharges, ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI09-Perioperative Hemorrhage and Hematoma Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI10-Postoperative Acute Kidney Injury Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI11-Postoperative Respiratory Failure Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI12-Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate- Surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Surgical discharges are defined by specific DRG or MS-DRG codes. PSI13-Postoperative Sepsis Rate- Elective surgical discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for an operating room procedure. Elective surgical discharges are defined by specific DRG or MS-DRG codes with admission type recorded as elective (SID ATYPE=3). PSI14-Postoperative Wound Dehiscence Rate- Discharges, for patients ages 18 years and older, with any-listed ICD-9-CM procedure codes for abdominopelvic surgery. PSI15-Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate- Patients ages 18 years and older with any procedure code for an abdominopelvic procedure.
  
  
• Exclusions: Below we list the exclusions for the composite components. There are no additional exclusions for the composite measure as a whole. PSI03 – Pressure Ulcer Rate-Excludes cases with length of stay less than 5 days, with a principal diagnosis of pressure ulcer or secondary diagnosis of pressure ulcer present on admission, cases with evidence of hemiplegia, paraplegia or quadriplegia, spina bifida, anoxic brain damage, debridement or pedicle graft on the same day as the major operating room surgery or as the only major operating room procedure, and cases that were transferred from a different hospital or skilled nursing facility, and cases with MDC (major diagnostic classification) of 9 (skin, subcutaneous and breast) or 14 (pregnancy, childbirth and puerperium). PSI06 – Iatrogenic Pneumothorax Rate - Excludes cases with a principal diagnosis for iatrogenic pneumothorax or secondary diagnosis of iatrogenic pneumothorax on admission, cases with evidence of chest trauma, pleural effusion, thoracic surgery, lung or pleural biopsy, diaphragmatic repair, cardiac procedure, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI08 – Postoperative Hip Fracture Rate-Excludes cases with principal diagnosis of hip fracture or a secondary diagnosis of hip fracture on admission, cases where the only operating room procedure is hip fracture, where the procedure for hip fracture occurs before or on the same day as the first operating room procedure, and cases with a principal diagnosis of seizure, syncope, stroke and occlusion of arteries, coma, cardiac arrest, poisoning, trauma, delirium and other psychoses, anoxic brain injury, metastatic cancer, lymphoid malignancy, bone malignancy, self-inflicted injury, and cases with MDC (major diagnostic classification) of 8 (musculoskeletal system and connective tissue) or 14 (pregnancy, childbirth and puerperium). PSI09 – Perioperative Hemorrhage and Hematoma Rate - Excludes cases with principal diagnosis of perioperative hemorrhage or postoperative hematoma or secondary diagnosis present of perioperative hemorrhage on admission, cases where the only operating room procedure is control of postoperative hemorrhage, drainage of hematoma or miscellaneous hemorrhage- or hematoma-related procedure, any secondary diagnosis of perioperative hemorrhage or postoperative hematoma and any-listed procedure codes for control of perioperative hemorrhage or evacuation of hematoma or miscellaneous hemorrhage- or hematoma- related procedure occurring before the first operating room procedure, cases with diagnosis of coagulation disorder and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI10 – Postoperative Acute Kidney Injury-Excludes cases with a principal diagnosis or secondary diagnosis on admission of acute renal failure, acute myocardial infarction, cardiac arrhythmia, cardiac arrest, shock, hemorrhage, gastrointestinal hemorrhage, or chronic renal failure, cases with dialysis procedure before on the same day as the first operating procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI11 – Postoperative Respiratory Failure Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of acute respiratory failure, cases where the only operating procedure is tracheostomy or a tracheostomy occurs before the first operating procedure, cases with any listed diagnosis of neuromuscular disorder, craniofacial anomalies or degenerative neurological disorder, cases with any listed procedure of laryngeal or pharyngeal, nose, mouth, or pharynx surgery, procedures involving the face, esophageal resection, procedures for lung cancer, and cases with MDC (major diagnostic classification) of 4 (disease of respiratory system), 5 (diseases of the circulatory system), or 14 (pregnancy, childbirth and puerperium). PSI12 – Perioperative Pulmonary Embolism and Deep Vein Thrombosis Rate - Excludes cases with principal diagnosis or secondary diagnosis on admission of DVT, pulmonary embolism, cases where a procedure for interruption of vena cava occurs before or on the same day as the first operating room procedure, cases with any procedure for extracorporeal membrane oxygenation, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI13 – Postoperative Sepsis Rate – Excludes cases with principal diagnosis or secondary diagnosis on admission of sepsis, infection, cases with evidence of immunocompromised state or cancer, cases with a length of stay less than 4 days, and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI14 – Postoperative Wound Dehiscence Rate – Excludes cases with any listed evidence of immunocompromised state, cases where the procedure for abdominal wall reclosure occurs on or before the day of the first abdominopelvic surgery procedure, cases with a length of stay less than 2 days, and cases with MDC(major diagnostic classification) of 14 (pregnancy, childbirth and puerperium). PSI15 – Unrecognized Abdominopelvic Accidental Puncture or Laceration Rate-Excludes cases with a principal diagnosis or secondary diagnosis at admission of accidental puncture or laceration during a procedure and cases with MDC (major diagnostic classification) of 14 (pregnancy, childbirth and puerperium).
  
  
• HHS NQS Priority: Making Care Safer
  
  
• HHS Data Source: Administrative claims Component measures require: ICD-9 diagnosis and procedure codes, MDC, MSDRG, procedure day, age in year, gender, admission type, discharge disposition. All are drawn from administrative data.
  
  
• Measure Type: Composite
  
  
• Steward: Agency for Healthcare Research & Quality
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This updated version of PSI 90 addresses a number of concerns raised by the NQF Safety Standing Committee. Three additional PSIs have been added to the measure. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable. PSIs were better linked to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication. This is intended to allow the measure to more accurately reflect the impact of the events.
  • Impact on quality of care for patients:The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges. The composite measure was constructed to increase the statistical precision by increasing the sample size and to assist consumers, providers, and payers with their decision-making. This updated version would three additional PSIs: PSI09 Postoperative Hemorrhage orHematoma, PSI10 Physiologic and Metabolic Derangement, and PSI11 Postoperative Respiratory Failure .
  
  
  
• Does the measure address a program goal or objective? Yes.. PSI 90 is currently in the Value-Based Purchasing program. MAP is being asked to review an updated version of the measure. During the 2014 CDP review of the measure, the Safety Standing Committee raised concerns about the weighting of the various components of the composite, specificially that some of the more heavily weighted components were less clinically significant (i.e., accidental punctures and lacerations) and/or less preventable. To address these concerns several updates were made to the measure: Additional PSI’s were added (from 8 events to 11 events, expanding the type of complications included in this measure)Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventablePSIs were better linked to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication. This is intended to allow the measure to more accurately reflect the impact of the events.
  
  
• Is this a high-value measure? Yes. This is an outcome measure addressing patient safety. The PSI measures were developed to identify harmful healthcare related events that are potentially preventable. Patients that experience a PSI event are hospitalized for two to three times longer, have twp to twenty times higher rates of inpatient mortality and two to eight times higher total hospital charges.
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in the program measure set. MAP is being asked to consider an update to the measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. The measure is currently used in IQR, VBP, and HACRP. The national composite rate is 0.81.
  
  
• Does a review of its performance history raise any concerns? Yes. There are substantial differences between this version of PSI 90 and the version currently undergoing NQF review in the Patient Safety Project.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is currently used in IQR, VBP, and HACRP. This is a composite measure calculated through claims data. This measure would potentially reduce events that cause serious harm to patients.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Each measure used within the PSI 90 composite is an outcome measure that has been shown to be largely preventable through improved structures and processes of care. Each measure has an evidence review form as part of the NQF endorsement process. The literature to support each measure is updated on a schedule basis.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2015
  
  
• Project for Most Recent Endorsement Review: Patient Safety 2015
  
  
• Review for Importance: The measure meets the Importance criteria (1a. Evidence, 1b. Performance Gap) 1a. Evidence: 16-Y; 8-N I; 1b. Performance Gap: 9-H; 9-M; 6-L; 0-I; 1c. Composite- Quality Construct and Rationale: 6-H; 7-M; 11-L; 0-I Rationale: · The Committee agreed that the outcomes in this measure were associated with one or more healthcare actions. However, there was concern that some of the elements of the composite had variable preventability. · The developers reported that the items within the composite are positively correlated. The correlations range in the low 0.08 up to the 30s (not very high). · The developers referenced several processes of care that are associated with lower rates for each of the components in the composite.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria (2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity) 2a. Reliability: 4-H; 10-M; 9-L; 1-I 2b. Validity: 2-H; 11-M; 7-L; 2-I 1c. Composite Construction: 4-H; 12-M; 7-L; 1-I Rationale: · The Committee agreed that the updated version of the measure provided by AHRQ was improved from the 2014 version reviewed by the Committee, specifically noting that the new weighting focusing on harm rather than just the frequency of events, was more clinically relevant than the previous version of the measure. · During reliability testing, the developers examined the true difference rather than random chance and noise. Their results show a reliability scores in the 70s, which is comparable to other endorsed measures · Aggregating a number of individual measures into a single composite can generate an overall performance score that is more reliable than if the individual measure scores were taken in isolation. · Empirical field validity testing was conducted at the performance measure score level for the overall composite by correlating the composite scores with the rates calculated from the 3M Potentially Preventable Readmissions measure. .The Pearson correlation value, was 0.11 with a p-value of <0.0001.
  
  
• Review for Feasibility: 12-H; 8-M; 3-L; 1-I (3a. Clinical data generated during care delivery; 3b. Electronic sources; 3c.Susceptibility to inaccuracies/ unintended consequences identified 3d. Data collection strategy can be implemented) Rationale: · The Committee had no concerns about the feasibility of this measure given that it is gathered with administrative claims data.
  
  
• Review for Usability: 12-H; 6-M; 6-L; 0-I (Meaningful, understandable, and useful to the intended audiences for 4a. Public Reporting/Accountability and 4b. Quality Improvement) Rationale: · There were concerns about the use of this measure in value-based purchasing, despite the improvements the developer has made, because may not accurately reflect that an actual preventable complication occurred or may focus on preventing measured events that are less clinically important. · This measure is used to monitor performance in national and regional reporting. It was also developed to enable comparative reporting and quality improvement at the provider or the hospital level.
  
  
• Review for Related and Competing Measures: Concerns were raised by the Committee that some of the elements of this measure, notably the central line related blood stream infections and post-operative hip fracture, may be better captured in other NQF approved measures rather than using administrative claims data. In addition, this measure is related to NQF 532, which is the pediatric version of the same measure 0347.
  
  
• Endorsement Public Comments: Summary pending
  
  
• Endorsement Committee Recommendation: 14-Y; 10-N

  Since 58% of the Committee voted to recommend this measure, it did not achieve consensus. It will move forward to the comment period and the Committee will discuss and revote after the public comment.

  This measure was last endorsed in 2009; it is a composite measure of 11 inpatient Patient Safety Indicators. In 2014 the Committee raised concerns about the weighting of the various components of the composite, specificially that some of the more heavily weighted components were less clinically significant (i.e., accidental punctures and lacerations) and/or less preventable. In addition, there were concerns that the events measured are not always reflective of an actual patient safety event that resulted in preventable patient harm. To address the concerns of the 2014 Committee, AHRQ made several updates to the measure to address the Committee’s concerns.

  1. Additional PSIs were included (from 8 events to 11 events, which expanded the type of complications included this measure),
  2. Two of the component PSIs were redesigned; specifically PSI 12 with the removal of isolated calf deep vein thromboses (DVT) which have limited clinical relevance and PSI 15 with a greater focus on accidental punctures and lacerations that occur during abdominal/pelvic surgery and those that result in re-operation within one day which reflect events that are more likely preventable, and
  3. The measure was modified to more accurately reflect the impact of the events by better linking the PSIs to important changes in clinical status with “harm weights” that are based on diagnoses that were assigned after the complication.

  The Committee agreed that the changes to the measure were highly responsive to the concerns raised during the 2014 Committee discussion. However, new concerns were raised: some post-operative DVT or other events included in the composite may not be preventable; the definition of ICD-9 based central line related blood stream infections may be less precise than other definitions (i.e., NHSN which reports the information differently); and concerns about this measure being included in value-based purchasing programs particularly when it is likely that not all of these events are preventable and that it may distract from efforts to reduce more impactful safety events. In addition, there were concerns that some of the indicators of the measure may not reflect preventable patient safety events because it comes from ICD-9 data of inpatient complications, which sometimes did not directly reflect that an actual preventable complication occurred in the validation of the components of the composite. During the vote, the Committee agreed that the measure meets the four NQF criteria; however, consensus was not reached on a recommendation for endorsement (58% yes, 42% no). The Committee will re-consider the recommendation for endorsement after reviewing the public comments.
  
  

Measure Specifications

• NQF Number (if applicable): 1664
  
  
• Description: 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 endorsed specifications of the measure are: 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. The Alcohol and Other Drug Disorder Treatment at Discharge (SUB-3a) rate describes only those who receive a prescription for FDA-approved medications for alcohol or drug use disorder OR a referral for addictions treatment. 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).)
  
  
• 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: Paper medical record
  
  
• Measure Type: Process
  
  
• Steward: The Joint Commission
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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
  
  
• Preliminary analysis summary
  • Contribution to program measure set:Adding this measure set would enhance the substance abuse measures currently in the set by helping to ensure patients are offered treatment. Studies have shown that less than one in 20 patients with a substance abuse disorder are offered treatment.
  • Impact on quality of care for patients:Individuals with serious mental illnesses have high rates of substance abuse disorders which frequently go untreated and can result in poorer outcomes. 40 to 60% of psychiatric inpatients have been found to have substance abuse disorders. Improving care of these disorders could lead to better outcomes and fewer co-morbidities. Additionally, alcohol, drug, and tobacco use are the cause of more than one out of every four deaths in the United States annually. Substance abuse also has severe economic impacts. Annual health care spending on alcohol and drug abuse is approximately $19 billion and $14 billion respectively.
  
  
  
• Does the measure address a program goal or objective? Yes. This measure would address an important quality issue in inpatient psychiatric facilities. Individuals with serious mental illnesses have high rates of substance abuse disorders which frequently go untreated and can result in poorer outcomes. Approximately 40-60% of psychiatric inpatients have substance abuse disorder. (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.) ?
  
  
• Is this a high-value measure? Yes. This is a process measure with a strong evidence link to improved outcomes. Studies have shown that only 10% of patients with substance abuse disorders received care that adhered to recommended practices. (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) (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.) Less than one in 20 patients with a substance abuse disorder are 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 this measure fill a gap in the program measure set? Yes. This measure would enhance the domain of effective treatment and prevention. Improving care of substance abuse disorders could result in improved outcomes and decreased risk of comorbidities. (National Institute on Alcohol Abuse and Alcoholism (NIAAA), Helping Patients Who Drink Too Much: A Clinician’s Guide, 2005 Edition, Rockville, MD.) In their Fall web meeting, the Hospital Workgroup stressed the importance of addressing substance abuse issues.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. This measure is part of the Joint Commissions Substance Abuse (SUB) measure set. The SUB measure set is used as a core measure set in the Joint Commission’s ORYX program. Performance results were not available.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is currently used by the Joint Commission. This measure would enhance the substance abuse measures currently in the measure set by assessing if a patient was offered treatment. Yes. Annual health care spending on alcohol and drug abuse is approximately $19 billion and $14 billion respectively. Alcohol, drug, and tobacco use are the cause of more than one out of every four deaths in the United States annually. As noted above, treating patients substance abuse could result in better outcomes for their physical and mental co-morbidities.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Yes. Endorsed; MUC same as endorsed version:Yes
  
  
• 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 is 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) Citations: • 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 Endorsement Maintenance 2014 - Phase II
  
  
• Review for Importance: The measure meets the Importance criteria(1a. High Impact: 1b. Performance Gap, 1c. Evidence)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-1Rationale:• 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: The measure meets the Scientific Acceptability criteria(2a. Reliability - precise specifications, testing; 2b. Validity - testing, threats to validity)2a. Reliability: H-0; M-19; L-0; I-0; 2b. Validity: H-0; M-16; L-5; I-0Rationale:• 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: 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: 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: 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: Please refer to the TOB-1 measure review on page 37 for discussion of comments related to the suite of tobacco measures.
  
  
• Endorsement Committee Recommendation: 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.

  Consensus Standards Approval Committee (CSAC) Review (January 24, 2014): Y-12; N-0; A-1Decision: Approved for endorsement.

  Board of Directors (February 18, 2014):Decision: Ratified for endorsement
  
  

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: The measure estimates a facility-level risk-standardized readmission rate for unplanned, all-cause readmission within 30 days of discharge from an Inpatient Psychiatric Facility of adult Medicare fee-for-service (FFS) patients with a principal diagnosis of a psychiatric disorder. The performance period for the measure is 24 months.
  
  
• Numerator: The outcome for this measure is unplanned, all-cause 30-day readmission. Readmission is defined as a subsequent inpatient admission to an IPF or short-stay acute care hospital (including critical access hospitals) for any cause, with the exception of certain planned readmissions, within 30 days from the date of discharge from an eligible index psychiatric admission in an Inpatient Psychiatric Facility.
  
  
• Denominator: The target population for this measure is Medicare FFS beneficiaries aged 18 years and older with a principal diagnosis of a psychiatric disorder discharged from an Inpatient Psychiatric Facility. Eligible index admissions require enrollment in Medicare Parts A & B for 12 months prior to the index admission, the month of admission, and at least 30 days post discharge; discharged alive; and not transferred to an IPF or short-stay acute care hospital. A readmission within 30-days will also be eligible as an index admission, if it meets all other eligibility criteria. The performance period for the measure is 24 months.
  
  
• Exclusions: The measure excludes admissions for patients: - Subsequent admission on day of discharge and following 2 days (transfers/interrupted stay period) - Nonpsychiatric principal discharge diagnosis - Discharged against medical advice - With unreliable data (e.g. has a death date but also admissions afterwards)
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• 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: Conditional support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:Readmissions to IPFs are a common occurrence that negatively impacts patients and drives up the cost of care. An analysis of 2012-2013 claims data shows an opportunity for improvement. The mean observed readmission rate was 20.7% with a range of 16.6%-24.4%. The crude risk-adjusted mean rate was 22.6% with a range of 19.7%-25%. *The stage of development for this MUC was updated to "Fully Developed" on December 3, 2015, after the MUC was publicly released.
  • Impact on quality of care for patients:Implementing this measure could increase the urgency to implement strategies to reduce readmissions such as improved care transitions and ensuring the patient is stabilized before discharge.
  
  
  
• Does the measure address a program goal or objective? Yes. This measure addresses the CMS high priority domain of care coordination. ?
  
  
• Is this a high-value measure? Yes. This is an outcome measure. Hospital readmissions can be very disruptive for patients and are associated with significantly higher costs. An analysis of 2012-2013 claims data shows an opportunity for improvement. The mean observed readmission rate was 20.7% with a range of 16.6%-24.4%. The crude risk-adjusted mean rate was 22.6% with a range of 19.7%-25%. AHRQ noted that between 40% and 50% of patients with a history of repeated psychiatric hospitalizations are readmitted within 12 months.
  
  
• Does this measure fill a gap in the program measure set? Yes. MAP has previously noted the need for readmission measures in the IPFQR set. Although a number of measures in the set currently address care coordination, they are process measures.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure was developed for the IPF setting but is largely harmonized with NQF #1789 Yes. Readmissions are not currently addressed in the IPFQR measure set but are a common and costly problem that negatively impacts patients. Additionally this measure is derived from claims data and is largely harmonized with acute care hospital readmissions measures.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  
• Does the measure address a high-priority quality issue in the dual eligible beneficiary population? Yes.
  
  

Rationale for measure provided by HHS
Patient Volume Analysis of calendar year 2013 IPF claims data showed that 308,915 Medicare beneficiaries had 471,349 IPF stays. This group of patients is particularly vulnerable. Sixty-six percent of discharges are for patients under 65 indicating Medicare eligibility due to disability; 56% of discharges also have dual eligibility with Medicaid indicating they have limited financial resources. Twenty-nine percent of Medicare beneficiaries who used IPF services in 2013 had more than one stay. For CY 2012 and CY 2013, approximately one-third of all admissions for a principal psychiatric disorder (ICD-9 codes 290-319) were to short-stay acute care hospitals (including critical access hospitals). However, of the 1669 short-stay acute care hospitals with psychiatric admissions, only 39% had 25 or more psychiatric admissions. Forty percent of the psychiatric admissions to short-stay acute care hospitals were to hospitals that also had IPF units. The HWR measure for short-stay acute care hospitals includes some of these diagnoses (i.e., dementia, substance use, and screening/history of mental health and substance use). Consequences of Readmissions Readmission is considered an adverse event because it indicates deterioration in health status after discharge from the IPF that requires an acute level of care. In addition to patient burden, readmissions impacts cost. A MedPAC report indicated that Medicare payments to IPFs averaged nearly $10,000 per discharge (MedPAC, 2014) MedPAC analyses also showed that spending for Medicare beneficiaries who use IPF services is substantially higher than for all fee-for-service beneficiaries, due in part to the IPF stays (MedPAC, 2010). Performance Variation There is variation in 30-day all-cause readmission rates across IPFs, which is noted in Item 44: Evidence of performance gap. Evidence of Effective Interventions to Reduce Readmissions Some individual studies and systematic reviews have supported the positive effect of the following interventions in reducing psychiatric readmissions: • Follow-up within 7 days of discharge (Mark, 2013) • Stabilizing condition prior to discharge (Durbin, 2007) • Transition/discharge practices (Vigod, 2013; Steffen, 2009) • Intensive case management (Dieterich, 2010) Citations: *Dieterich M, Irving CB, Park B, Marshall M. Intensive case management for severe mental illness. The Cochrane database of systematic reviews. 2010(10):Cd007906. *Durbin J, Lin E, Layne C, Teed M. Is readmission a valid indicator of the quality of inpatient psychiatric care? J. Behav. Health Serv. Res. 2007;34(2):137-150. *Mark T, Tomic KS, Kowlessar N, Chu BC, Vandivort-Warren R, Smith S. Hospital readmission among medicaid patients with an index hospitalization for mental and/or substance use disorder. J. Behav. Health Serv. Res. 2013;40(2):207-221. *MedPAC. Chapter 6: Inpatient Psychiatric Care in Medicare: Trends and Issues. June 2010 Report to Congress: Aligning Incentives in Medicare. Washington, DC: MedPAC; 2010:161-187. * MedPAC. Inpatient Psychiatric Facility Services Payment System. Washington, DC: MedPAC; October 2014. *Steffen S, Kosters M, Becker T, Puschner B. Discharge planning in mental health care: a systematic review of the recent literature. Acta Psychiatr. Scand. 2009;120(1):1-9. *Vigod SN, Kurdyak PA, Dennis CL, et al. Transitional interventions to reduce early psychiatric readmissions in adults: systematic review. Br. J. Psychiatry. 2013;202(3):187-194.

Measure Specifications

• NQF Number (if applicable):
  
  
• Description: Measure estimates risk-adjusted rates of inpatient admissions or emergency department (ED) visits for cancer patients >18 years of age with at least one of the following diagnoses—anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, or sepsis—within 30 days of hospital outpatient chemotherapy treatment. Two rates are reported.
  
  
• Numerator: The outcomes for this measure are one or more inpatient admissions or one or more emergency department (ED) visits for one of the following diagnoses—anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, or sepsis—within 30 days among cancer patients receiving a hospital outpatient chemotherapy treatment. Qualifying diagnosis on the admission or ED visit claim must be listed as (1) the primary diagnosis or (2) a secondary diagnosis accompanied by a primary diagnosis of cancer. Outcomes are identified separately for the inpatient and ED categories. A patient can only qualify for an outcome once. Patients who experience both an inpatient admission and an ED visit during the measurement period are counted towards the inpatient admission outcome. Among those with no qualifying inpatient admissions, qualifying ED visits will be counted. Outcome Attribution: The outcome is attributed to the hospital outpatient facility where the patient received chemotherapy treatment during the 30 days prior to the outcome.
  
  
• Denominator: The measure cohort includes Medicare Fee-for-Service (FFS) patients aged 18 years and older as of the start of the measurement period with a diagnosis of any cancer (except leukemia) who received at least one hospital outpatient chemotherapy treatment at the reporting facility during the measurement period.
  
  
• Exclusions: 1) Patients with a diagnosis of leukemia at any time during the measurement period. 2) Patients who were not enrolled in Medicare FFS Parts A and B in the year prior to the first outpatient chemotherapy treatment during the measurement period. 3) Patients who received chemotherapy treatments for whom Medicare FFS Parts A and B enrollment is not maintained for the 30-days following treatment for at least one chemotherapy treatment during the measurement period.
  
  
• HHS NQS Priority: Communication and Care Coordination, Effective Prevention and Treatment
  
  
• HHS Data Source: Claims
  
  
• 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: Conditional support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure fits in a high-priority domain and would align PCHQR with other measure sets that include admissions and readmissions measures, including ASCQR and HRRP.The measure has not been submitted for endorsement to NQF. This measure was conditionally supported by the MAP in 2013 for use in the PCHQR program, pending NQF endorsement.
  • Impact on quality of care for patients:According to research by the measure developer, nearly 20% of chemotherapy patients are affected by potentially preventable adverse events that are so severe they require a hospital admission of ED visit. Incentivizing HODs to better manage chemotherapy complications should reduce burden on patients and lower cost for payers.
  
  
  
• Does the measure address a program goal or objective? Yes. It addresses two NQS priorities: promoting effective communication and coordination of care, and promoting the most effective prevention and treatment practices for the leading causes of mortality, one of which - care coordination - is a CMS high-priority domain.
  
  
• Is this a high-value measure? Yes. It is an outcome measure: included diagnoses for inpatient admission are significant adverse events, such as pneumonia and sepsis, that may be due to outpatient chemotherapy patients having significant unmet needs that contripute to a hospital admission or ED visit. Analysis of this measure suggests approximately 18% of the denominator experiences either a hospital admission or ED visit following outpatient chemotherapy treatment, with a range of performance across hospitals.MAP previously reviewed an early version of this measure and conditionally supported it, pending NQF endorsement. This is an update to the measure and this version includes patients with pneumonia or sepsis. This is now only a claims-based measure (the old specs mentioned EHRs).
  
  
• Does this measure fill a gap in the program measure set? Yes. No measures in the set track unplanned admissions or ED visits following a procedure. Care coordination is a high-priority domain identified by CMS.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. Tested at the PPS-exempt cancer hospital setting; facility level of analysis.
  
  
• Is the measure currently in use? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure is harmonized with other, similar measures, by excluding planned visits, and capturing 30 days from the date of the procedure. This measure was conditionally supported by the MAP in 2013 for use in the PCHQR program, pending NQF endorsement. The measure is entirely derived from Medicare FFS claims data, and unlikely to be burdensome to calculate.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Never Submitted
  
  

Rationale for measure provided by HHS
Cancer patients receiving chemotherapy have much higher rates of admissions and ED use than other patients. A study of 2007 commercial claims data for more than 14 million patients found that cancer patients average one admission per year; 40 percent of those admissions were chemotherapy related (Kolodziej et al. 2011). The authors also found that cancer patients average approximately two ED visits per year, about half of which were chemotherapy related. Common complications of chemotherapy treatment include nausea, emesis, anemia, neutropenic fever, diarrhea, dehydration, and pain (Burton et al. 2007; Crawford et al. 2004; Groopman and Itri 2000; Osoba et al. 1997; Richardson and Dobish 2007; Stein et al. 2010). Chemotherapy-related admissions and ED visits may be due to outpatient chemotherapy patients having unmet needs and gaps in care, which, if addressed, could reduce admissions and ED visits and increase patients’ quality of life (Hassett et al. 2006; Mayer et al. 2011; McKenzie et al. 2011). Although it is extremely unlikely that all admissions and ED visits related to chemotherapy can be avoided by prevention and treatment of side effects and complications, there is evidence and consensus among providers on ways to prevent and treat each of the symptoms included in the numerator of this measure. Measurement of admissions and ED visits for patients receiving outpatient chemotherapy should encourage reporting facilities to take steps to prevent and improve management of side effects and complications from treatment. Poor performance on the measure would reflect high resource use and significant consequences for patient/society due to poor quality; admissions and ED visits are costly to payers and reduce quality of life for patients. Burton, A.W., G.J. Fanciullo, R.D. Beasley, and M.J. Fisch. “Chronic Pain in the Cancer Survivor: A New Frontier”. Pain Medicine, vol. 8, 2007, pp. 189–198. Crawford, J.C., D.C. Dale, and G.H. Lyman. “Chemotherapy-Induced Neutropenia.” Cancer, vol. 15, 2004, pp. 228–237. Groopman, J.E., and L.M. Itri. “Chemotherapy-Induced Anemia in Adults: Incidence and Treatment.” Journal of the National Cancer Institute, vol. 91, 2000, pp. 1616–1634. Hassett, M.J., J. O’Malley, J.R. Pakes, J.P. Newhouse, and C.C. Earle. “Frequency and Cost of Chemotherapy-Related Serious Adverse Effects in a Population Sample of Women with Breast Cancer.” Journal of the National Cancer Institute, vol. 98, no. 16, 2006, pp. 1108–1117. Kolodziej, M., J.R. Hoverman, J.S. Garey, J. Espirito, S. Sheth, A. Ginsburg, M.A. Neubauer, D. Patt, B. Brooks, C. White, M. Sitarik, R. Anderson, and R. Beveridge. “Benchmarks for Value in Cancer Care: An Analysis of a Large Commercial Population.” Journal of Oncology Practice, vol. 7, 2011, pp. 301–306. Mayer, D.K., D. Travers, A. Wyss, A. Leak, A. Waller. “Why Do Patients with Cancer Visit Emergency Departments? Results of a 2008 Population Study in North Carolina.” Journal of Clinical Oncology, vol. 26, no. 19, 2011, pp. 2683–2688. McKenzie, H., L. Hayes, K. White, K. Cox, J. Fethney, M. Boughton, and J. Dunn. “Chemotherapy Outpatients’ Unplanned Presentations to Hospital: A Retrospective Study.” Support Care Cancer, vol. 19, 2011, pp. 963–969. Osoba, D., B. Zee, D. Warr, J. Latreilee, L. Kaizer, and J. Pater. “Effect of Postchemotherapy Nausea and Vomiting on Health-Related Quality of Life.” Support Care Cancer, vol. 5, 1997, pp. 307–313. Richardson, G., and R. Dobish. “Chemotherapy Induced Diarrhea.” Journal of Oncology Pharmacy Practice, vol. 13, no.4, 2007, pp. 181–98. Stein, A., W. Voigt, and K. Jordan. “Chemotherapy-Induced Diarrhea: Pathophysiology, Frequency, and Guideline-Based Management.” Therapeutic Advances Medical Oncology, vol. 2, 2010, pp. 51–63.

Measure Specifications

• NQF Number (if applicable): 753
  
  
• Description: Organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients at least 18 years of age undergoing inpatient colon procedures and/or abdominal hysterectomies as reported through the ACS-NSQIP or CDC NHSN. The measure yields separate SIRs for each procedure. (The endorsed specifications of the measure are: Prototype measure for the facility adjusted Standardized Infection Ratio (SIR) of deep incisional and organ/space Surgical Site Infections (SSI) at the primary incision site among adult patients aged >= 18 years as reported through the ACS National Surgical Quality Improvement Program (ACS-NSQIP) or CDC National Health and Safety Network (NHSN). Prototype also includes a systematic, retrospective sampling of operative procedures in healthcare facilities. This prototype measure is intended for time-limited use and is proposed as a first step toward a more comprehensive SSI measure or set of SSI measures that include additional surgical procedure categories and expanded SSI risk-adjustment by procedure type. This single prototype measure is applied to two operative procedures, colon surgeries and abdominal hysterectomies, and the measure yields separate SIRs for each procedure.)
  
  
• Numerator: Deep incisional primary (DIP) and organ/space SSIs during the 30-day postoperative period among patients at least 18 years of age undergoing inpatient colon surgeries or abdominal hysterectomies. SSIs will be identified before discharge from the hospital, upon readmission to the same hospital, or during outpatient care or admission to another hospital (post-discharge surveillance). Case accrual will be guided by sampling algorithms as described below.
  
  
• Denominator: Using multivariable logistic regression models for colon surgeries and abdominal hysterectomies, the expected number of SSIs is obtained. These expected numbers are summed by facility and surgical procedure and used as the denominator of this measure
  
  
• Exclusions: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded.(The endorsed specifications of the measure are: Persons under the age of 18, those having a procedure performed on an outpatient basis, those with ASA Class VI (6) are excluded. In the NHSN, patients without primary closure of the surgical incision are not considered eligible cases and are excluded- the NSQIP will match this practice for this measure, although this is not standard practice within the NSQIP.)
  
  
• 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: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Conditional support, pending NQF annual update
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This is an update to the name of the measure from “reliability adjusted SIR” to “Adjusted Ranking Metric (ARM).”
  • Impact on quality of care for patients:The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
  
• Does the measure address a program goal or objective? Yes. The priority domain is to make care safer by reducing harm caused in the delivery of care.?
  
  
• Is this a high-value measure? Yes. This is an update to a measure currently in the program. The continued use of this measure will promote SSI prevention activities, which will lead to an improvement in patient outcomes, reducing avoidable medical costs, patient morbidity and mortality. Guidelines to prevent SSIs are available here (http://www.cdc.gov/hicpac/SSI/001_SSI.html).
  
  
• Does this measure fill a gap in the program measure set? N/A. This measure is currently in this program – the name is being changed from reliability adjusted SIR to the Adjusted Ranking Metric (ARM). Currently, there are three measures in the program measure set implemented and finalized that address the NQS priority of making care safe, two additional ones are proposed. This is the only SSI measure.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. It is tested at the hospital/acute care facility level, at the facility level of analysis.
  
  
• Is the measure currently in use? Yes. This measure is currently used in this program, but the name of the measure is changing from reliability adjusted SIR to the Adjusted Ranking Metric (ARM).
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It is currently in the program.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
Affects large numbers, Frequently performed procedures, A leading cause of morbidity/mortality, High resource use, Severity of illness, Patient/societal consequences of poor quality. SSIs estimated to account for 20% of all HAIs[1] 290,485 estimated SSIs/yr[2] Estimated 8,205 deaths associated with SSIs each year[1] Estimated 11% of all deaths occurring in intensive care units are associated with SSIs[1] $34,670 medical cost/SSI[2] Total >$10 billion attributable to SSI in U.S. each year[2] Estimated additional 7-10 days of hospitalization for each SSI per patient[1] [1] Klevens RM, Edwards JR, et al. Estimating healthcare-associated infection and deaths in U.S. hospitals, 2002. Public Health Reports 2007; 122:160-166. [2] Scott, RD. The Direct Medical Costs of Healthcare-Associated Infections in U.S. Hospitals and the Benefits of Prevention. http://www.cdc.gov/ncidod/dhqp/pdf/Scott_CostPaper.pdf accessed April 12, 2010.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Patient Safety Measures
  
  
• Review for Importance: The measure addresses a high impact area. Each year, approximately 11 percent of all deaths in ICUs are associated with SSIs, resulting in up to 20,000 deaths and $2 billion in additional costs.2 Moreover, evidence-based interventions have shown significant reductions in SSI rates and improved health outcomes.
  
  
• Review for Scientific Acceptability: See CDP Recommendation]
  
  
• Review for Feasibility: See CDP Recommendation]
  
  
• Review for Usability: See CDP Recommendation]
  
  
• Review for Related and Competing Measures: See CDP Recommendation]
  
  
• Endorsement Committee Recommendation: The Steering Committee discussed the newly-harmonized measure in a supplemental conference call, reviewing the relevant changes, while also receiving clarification from the developers on several issues. Committee members inquired as to why these two particular measures had been chosen, and asked for clarification on the plan for public reporting. The developer explained that the CMS IPPS requirements released on August 1, 2011, call for abdominal hysterectomies and colon surgeries to be reported by the CDC to CMS. The NHSN will serve as the single reporting system for CMS-required reporting. However, facilities may choose which calculations of performance on the measure can be accomplished using either the NHSN or NSQIP data system. The measure developer acknowledged that for hospitals participating in both systems, there could be duplication.The Steering Committee questioned why both organ space and deep incisional infections were included in the measure. The developer described the approach as a long standing precedent and stated that superficial infections are considered trivial events and therefore not included. However, organ space infections that drain through the incisions are classified as deep incisional infections. The combination of organ space and deep incisional infections are considered a clinically coherent grouping. The Committee expressed their appreciation for the developers’ efforts at harmonization, and agreed that the measure continues to meet the four major evaluation criteria. The Steering Committee recommended this measure for endorsement in a unanimous vote.This outcome measure replaces NQF-endorsed measure #0299 (Surgical Site Infection Rate) and addresses the National Priority area of safety.
  
  

Measure Specifications

• NQF Number (if applicable): 1717
  
  
• Description: Standardized infection ratio (SIR) of hospital-onset CDI Laboratory-identified events (LabID events) among all inpatients in the facility, excluding well-baby nurseries and neonatal intensive care units (NICUs). Additional metric added- Adjusted Ranking Metric also known as the “reliability-adjusted SIR.” (The endorsed specifications of the measure are: Standardized infection ratio (SIR) of hospital-onset CDI Laboratory-identified events (LabID events) among all inpatients in the facility, excluding well-baby nurseries and neonatal intensive care units (NICUs))
  
  
• Numerator: Total number of observed hospital-onset CDI LabID events among all inpatients in the facility, excluding well baby-nurseries and NICUs
  
  
• Denominator: Total number of expected hospital-onset CDI LabID events, calculated using the facility´s number of inpatient days, bed size, affiliation with medical school, microbiological test used to identify C. difficile, and community-onset CDI admission prevalence rate
  
  
• Exclusions: Data from patients who are not assigned to an inpatient bed are excluded from the denominator counts, including outpatient clinic and emergency department visits. Additionally, data from well-baby nurseries and NICUs are excluded from the denominator count
  
  
• 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: Endorsed; MUC same as endorsed version:No
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional support, pending NQF annual update
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure would promote alignment between programs assessing general acute care and cancer hospitals (IQR and PCHQR). This measure is included in the MAP Safety Family of Measures. This measure addresses a condition that is a significant cause of morbidity and mortality among hospital patients and is associated with increased healthcare costs. The measure addresses a common condition in the Medicare FFS population that is associated with significant variation in costs and an opportunity for improvement. This measure is fully-specified and tested, but the update has not been reviewed by NQF.
  • Impact on quality of care for patients:The measure is already in the program and will continue to promote multi-drug resistant organism prevention activities, such as CDI. CDC estimated that 107,700 infections occurred in United States acute care hospitals in 2011 (http://www.cdc.gov/hicpac/pubs.html). Adherence to clinical guidelines has resulted in decreased rates of infection.
  
  
  
• Does the measure address a program goal or objective? Yes. The priority domain for this MUC is making care safer by reducing harm caused in the delivery of care.
  
  
• Is this a high-value measure? Yes. CDI is a significant cause of morbidity and mortality among hospital patients and is associated with increased healthcare costs. CDI has been found to cause 12% of healthcare associated infections (http://www.uptodate.com/contents/clostridium-difficile-infection-prevention-and-control?source=search_result&search=Clostridium+difficile+Infection&selectedTitle=4~150), have a mortality rate of 16.7% after 1 year, and have a total cost per year of $1 billion to 1.6 billion (http://www.cdc.gov/HAI/pdfs/hai/Scott_CostPaper.pdf).The specs have been updated to include the addition of the Adjusted Ranking Metric (ARM), also known as the “reliability-adjusted SIR”. The reliability-adjusted SIR can be used for annual aggregation. The reliability-adjusted SIR combines the method of indirect standardization with a Bayesian rand.
  
  
• Does this measure fill a gap in the program measure set? N/A. This is an update to a measure currently in the program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes.
  
  
• Is the measure currently in use? Yes. This measure is currently used in several programs: PPS-Exempt Cancer Hospital Quality Reporting Program, Hospital Acquired Condition Reduction Program, Hospital Inpatient Quality Reporting, Hospital Value-Based Purchasing, Inpatient Rehabilitation Facility Quality Reporting, Long-Term Care Hospital Quality
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. This measure would support alignment since it is included in federal and private programs. This measure would promote alignment between programs assessing general acute care and cancer hospitals (IQR and PCHQR). This measure is also included in the MAP Safety Family of Measures.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:No
  
  

Rationale for measure provided by HHS
Clostridium difficile is responsible for a spectrum of C. difficile infections (CDI), including uncomplicated diarrhea, pseudomembranous colitis, and toxic megacolon, which can, in some instances lead to sepsis and even death. In recent years, a previously unrecognized strain of C. difficile, with increased virulence and high levels of antimicrobial resistance, has resulted in outbreaks in healthcare facilities in the United States. Additionally, CDI has become more common in the community setting, with increased risk in those with history of recent inpatient stay in a healthcare facility. Significant increases in cost of inpatient care have been seen in cases of CDI.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2013
  
  
• Project for Most Recent Endorsement Review: Patient Safety – Complications Endorsement Maintenance: Phase II
  
  
• Review for Importance: The measure meets the Importance criteria(1a. High Impact: 1b. Performance Gap, 1c. Evidence)1a. Impact: H-15; M-1; L-0; I-0 1b. Performance Gap: H-6; M-10; L-0; I-0 1c. Evidence: Y-16; N-0Rationale:· This measure is important since concern about Clostridium difficile Infection (CDI) has risen significantly in the medical community. Rates of CDI are highest for patients in healthcare facilities and increase with patient age.· In 2010, 715 facilities from 28 states monitored CDI events in NHSN. A total of 20,803 HO CDI events were reported from 5,757,846 admissions and 28,279,284 patient-days. CDI incidence rates differed significantly by facility teaching type, bed size, test type, and Community Onset (CO) prevalence.· The measure is supported by clinical practice guidelines from the Society for Healthcare Epidemiology or America (SHEA), Infectious Disease Society of America (IDSA) and the CDC Healthcare infections Control Practices Advisory Committee (HICPAC). By adhering to these guidelines can decrease the rate of CDI transmission and infection.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability – precise specifications, testing; 2b. Validity – testing, threats to validity)2a. Reliability: H-7; M-9; L-0; I-0 2b. Validity: H-7; M-9; L-0; I-0Rationale:· The denominator time window in 10,000 patient days was used to create an easily understandable time period for measure calculations. The Committee expressed concern that the number of infections may be low since the measure included a lengthy time period. However, the developer explained that CDI was increasing and that rates are reviewed annually, and that this is the standard way that CDI rates are reported.· The time window is monthly reporting, with each facility completing a reporting plan to that they are following infections.· Neonates and babies less than one year of age are excluded from the measure since whether an infection is present or whether they are carriers is not clear and easy to differentiate.· More sensitive testing for CDI has become available, through the use of Polymerase Chain Reaction (PCR), and is increasingly available to facilities. Because PCR-based tests are more sensitive, it may appear that facilities using PCR-based testing would have higher rates than non-PCR based testing.· The Committee was satisfied with the Standardized Infection Ratio (SIR) methodology and did not have concerns about the measure’s validity or reliability.
  
  
• Review for Feasibility: H-10; M-6; 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 Committee noted that the use of antibiotics to treat CDI could be susceptible to overuse and misuse. The developer indicated that they will have an antimicrobial use and resistance model to monitor this issue through NHSN, which will likely be ready in August 2013.
  
  
• Review for Usability: H-12; M-4; L-0; I-0(Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting/Accountability and 3b. Quality Improvement)Rationale: This measure will be included in CMS´ Hospital Inpatient Quality Reporting (IQR) Program for events identified starting in January 2013.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments:

  Comments included: Standardized infection rates are not as meaningful to consumers as the actual risk-adjusted rates of infection per admission.

  Developer response: We appreciate the commenter’s feedback. The standardized infection ratio (SIR) offers clear advantages to healthcare consumers over infection rates as the summary metric for this measure. The SIR produces a single risk-adjusted metric that can be further aggregated to the state, regional, or national level, all while maintaining appropriate comparisons between healthcare facilities. Further, observed-to-predicted ratios, such as the SIR, are widely used in public reporting of healthcare quality data. CDC, the Centers for Medicare and Medicaid Services, health departments in many states, and Consumers Union all use the SIR to report HAI data.

  Committee response: The Committee was satisfied with the developer’s response and reaffirmed its recommendation of measure 1717 as specified. However, they suggested the developer consider reporting actual risk-adjusted rates of infection per admission in the future. The Committee also recognized the importance of measures that are meaningful to consumers and it was noted as an area of future measure development in the draft report.
  
  

• Endorsement Committee Recommendation: Y-16; N-0 CSAC Approved (November 7, 2012). Board Endorsed (December 13, 2012).
  
  

Measure Specifications

• NQF Number (if applicable): 1716
  
  
• Description: Standardized infection ratio (SIR) of hospital-onset unique blood source MRSA Laboratory identified events (LabID events) among all inpatients in the facility
  
  
• Numerator: Total number of observed hospital-onset unique blood source MRSA LabID events among all inpatients in the facility
  
  
• Denominator: Total number of expected hospital-onset unique blood source MRSA LabID events, calculated using the facility´s number of inpatient days, bed size, affiliation with medical school, and community-onset MRSA bloodstream infection admission prevalence rate.
  
  
• Exclusions: Data from patients who are not assigned to an inpatient bed are excluded from the denominator counts. These include outpatient clinic and emergency department visits.
  
  
• 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: Endorsed; MUC same as endorsed version:No
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has not been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional support, pending NQF review and endorsement of revised specifications
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The measure promotes alignment between programs, since it is currently in use in the PPS-Exempt Cancer Hospital Quality Reporting Program, Hospital Inpatient Quality Reporting, Hospital Value-Based Purchasing, Inpatient Rehabilitation Facility Quality Reporting, and Long-Term Care Hospital Quality Reporting. This measure is fully-specified and tested, but the update has not been reviewed by NQF.
  • Impact on quality of care for patients:The measure is already in the program and will continue to promote multi-drug resistant organism prevention activities, (http://www.cdc.gov/hicpac/pubs.html) including MRSA, which will help improve patient outcomes including reduction of avoidable costs, morbidity, and mortality.
  
  
  
• Does the measure address a program goal or objective? Yes. ?This measure would make care safer by reducing harm caused in the delivery of care, a high priority domain identified for this program by CMS.
  
  
• Is this a high-value measure? Yes. MAP is being asked to review an updated version of an NQF-endorsed measure that is already in the program. The specs have been updated to include the addition of the Adjusted Ranking Metric (ARM), also known as the “reliability-adjusted SIR”. The reliability-adjusted SIR can be used for annual aggregation. The reliability-adjusted SIR combines the method of indirect standardization with a Bayesian rand.
  
  
• Does this measure fill a gap in the program measure set? N/A. This is an update to a measure currently in the program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure is tested at the hospital inpatient, inpatient rehab, and long-term care hospital setting at the facility level.
  
  
• Is the measure currently in use? Yes. The NQF endorsed version is currently in use in Hospital Inpatient Quality Reporting, Hospital Value-Based Purchasing, Inpatient Rehabilitation Facilitiy Quality Reporting, and Long-Term Care Hospital Quality Reporting.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It contributes to alignment because it is currently in use in several programs: Hospital Inpatient Quality Reporting, Hospital Value-Based Purchasing, Inpatient Rehabilitation Facility Quality Reporting, and Long-Term Care Hospital Quality Reporting.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:No
  
  

Rationale for measure provided by HHS
Clinical guidelines for the management of multidrug resistant organisms (MDROs), including MRSA, have been published. Adherence to the recommendations in the guidelines can result in decreased rates of MDRO transmission and infection. Decreasing rates of infection will result in a lower SIR, which indicates improving performance.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2013
  
  
• Project for Most Recent Endorsement Review: Patient Safety – Complications Endorsement Maintenance: Phase II
  
  
• Review for Importance: The measure meets the Importance criteria(1a. High Impact: 1b. Performance Gap, 1c. Evidence)1a. Impact: H-15; M-1; L-0; I-0 1b. Performance Gap: H-10; M-6; L-0; I-0 1c. Evidence: Y-15; N-1Rationale:· The measure is aimed at reducing infection rates. Multidrug-Resistant Organisms (MDROs), including Methicillin-resistant Staphylococcus aureus (MRSA), have been associated with increased mortality, length of stay and cost. Additionally, 56.8% of all central line-associated bloodstream infections reported to the National Healthcare Safety Network (NHSN) in 2006-2007 caused by Staphylococcus aureus were MRSA.· In 2010, MRSA bacteremia was monitored in 548 facilities from 29 states. A total of 1,078 Healthcare Facility-Onset (HO) MRSA bacteremia events were reported from 3,807,920 admissions and 17,427,005 patient-days. MRSA bacteremia incidence rates differed significantly by teaching type and bed size.· Following the 2006 Healthcare Infection Control Practices and Advisory Committee (HICPAC) guideline can be used to reduce the incidence and transmission of infections with MDROs in healthcare facilities.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria(2a. Reliability – precise specifications, testing; 2b. Validity – testing, threats to validity)2a. Reliability: H-7; M-9; L-0; I-0 2b. Validity: H-7; M-9; L-0; I-0Rationale:· The measure examines the hospital onset of MRSA that occurs more than three days after admission to a facility. It counts patient days within the facility, which are collected and entered by infection preventionists. Data are presented as a standardized infection ratio and the denominator is measured in 1000 patient days.· The Committee requested clarification on the CDC’s risk-adjustment methods, with some questioning whether the measure could account for institutions with higher concentrations of immune-compromised patients (e.g., cancer hospitals). The CDC provided additional information on the variables included in the Standardized Infection Ratio (SIR) for this measure.· The Committee was satisfied with the SIR methodology and did not have concerns about the measure’s validity or reliability.
  
  
• Review for Feasibility: H-10; M-6; 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:· Data are entered both manually and through an automated system.· There was concern that lab tests confirming MRSA may not be ordered by hospitals in order to artificially reduce the number of MRSA infections reported. The developer thought this would be unlikely; however, they stated that if they had an indication of this type of situation, they could create another measure relating to the use of antimicrobials without obtaining a culture as another method of capturing MRSA infections focused exclusively treatment.
  
  
• Review for Usability: H-11; M-5; L-0; I-0(Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting/Accountability and 3b. Quality Improvement)Rationale: This measure will be included in CMS´ Hospital Inpatient Quality Reporting (IQR) Program for events identified starting in January 2013.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments:

  Comments included: Standardized infection rates are not as meaningful to consumers as the actual risk-adjusted rates of infection per admission.

  Developer response: We appreciate the commenter’s feedback. The standardized infection ratio (SIR) offers clear advantages to healthcare consumers over infection rates as the summary metric for this measure. The SIR produces a single risk-adjusted metric that can be further aggregated to the state, regional, or national level, all while maintaining appropriate comparisons between healthcare facilities. Further, observed-to-predicted ratios, such as the SIR, are widely used in public reporting of healthcare quality data. CDC, the Centers for Medicare and Medicaid Services, health departments in many states, and Consumers Union all use the SIR to report HAI data.

  Committee response: The Committee was satisfied with the developer’s response and reaffirmed its recommendation of measure 1716 as specified. However, they suggested the developer consider reporting actual risk-adjusted rates of infection per admission in the future. The Committee also recognized the importance of measures that are meaningful to consumers and it was noted as an area of future measure development in the draft report.
  
  

• Endorsement Committee Recommendation: Y-16; N-0 CSAC Approved (November 7, 2012). Board Endorsed (December 13, 2012).
  
  

Measure Specifications

• NQF Number (if applicable): 382
  
  
• Description: Percentage of patients, regardless of age, with a diagnosis of breast, rectal, pancreatic or lung cancer receiving 3D conformal radiation therapy who had documentation in medical record that radiation dose limits to normal tissues were established prior to the initiation of a course of 3D conformal radiation for a minimum of two tissues
  
  
• Numerator: Patients who had documentation in medical record that radiation dose limits to normal tissues were established prior to the initiation of a course of 3D conformal radiation for a minimum of two tissues
  
  
• Denominator: All patients, regardless of age, with a diagnosis of breast, rectal, pancreatic or lung cancer receiving conformal radiation therapy
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Administrative claims, Administrative clinical data, Paper medical record, Record review
  
  
• Measure Type: Process
  
  
• Steward: American Medical Association - Physician Consortium for Performance Improvement
  
  
• Endorsement Status: Endorsed; MUC same as endorsed version:Yes
  
  
• 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: Conditional support, pending NQF endorsement
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is currently in the program and is undergoing a substantial change. The update is to expand the denominator to include breast and rectal cancers.
  • Impact on quality of care for patients:The continued use of this measure will promote effective coordination of care for oncology patients by identifying normal tissue dose constraints for those who receive radiation therapy treatments. Even though there is no specific data available, the American College of Radiation Oncology has found that normal dose constraints are not frequently included in the patient chart.
  
  
  
• Does the measure address a program goal or objective? Yes. The measure promotes effective communication and coordination of care for oncology patients who received normal tissue radiation dose limits.
  
  
• Is this a high-value measure? Yes. MAP is asked to review an update to this measure, which is currently in the PPS-exempt Cancer Hospital Quality Reporting Program. This is an update to expand the denominator to include breast and rectal cancers.
  
  
• Does this measure fill a gap in the program measure set? N/A. The measure is already in the PPS-Exempt Cancer Hospital Reporting program.
  
  
• Measure development status: Fully Developed
  
  
• Is the measure fully tested for the program's setting and level of analysis? Yes. The measure is tested at the ambulatory/office-based care, community hospital, hospital inpatient, and hospital/acute care facility setting and at the clinician level of analysis.
  
  
• Is the measure currently in use? Yes. It is currently being reported in PQRS as well as in PPS-Exempt Cancer Hospital Reporting programs.
  
  
• Does a review of its performance history raise any concerns? No.
  
  
• Does the MUC contribute to alignment and efficient use of measurement resources (burden and cost of measurement)? Yes. It supports alignment since it is currently being reported in PQRS as well as in PPS-Exempt Cancer Hospital Reporting programs.
  
  
• Is the measure NQF endorsed for the program's setting and level of analysis? Endorsed; MUC same as endorsed version:Yes
  
  

Rationale for measure provided by HHS
This measure is rated as moderate by the measure developer. The quality of the body of evidence supporting the guideline recommendation is summarized according to the National Comprehensive Cancer Network (NCCN) categories of evidence and consensus as being based on "lower-level evidence". Lower-level evidence is later described as evidence that may include non-randomized trials; case series; or when other data are lacking, the clinical experience of expert physicians. Although there is no explicit statement regarding the overall consistency of results across studies in the guidelines supporting the measure, the recommendation received uniform NCCN consensus that the intervention is appropriate. The description of the evidence review in the guideline did not address the overall quantity of studies in the body of evidence. However, 330 articles are cited in NCCN´s pancreatic adenocarcinoma guideline. 408 and 172 articles are cited in NCCN´S non small cell lung cancer and small cell lung cancer guidelines, respectively. A panel of experts with members from each of the NCCN Member Institutions develops the NCCN Guidelines. Specialties that must be included on a particular panel are identified before that panel is convened but also evolve as the standard of care changes over time. This multidisciplinary representation varies from panel to panel. The NCCN Guidelines Panel Chairs are charged with ensuring that representatives of all treatment strategies are included. Many of the panels also include a patient representative, especially when issues of long-term care and patient preference are paramount in the panel´s considerations.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2012
  
  
• Project for Most Recent Endorsement Review: Cancer Endorsement Maintenance 2011
  
  
• Review for Importance: The measure meets the Importance criteria.(1a. High Impact; 1b. Performance Gap; 1c. Evidence)1a. Impact: H-12; M-4; L-0; I-0; 1b. Performance Gap: H-2; M-12; L-2; I-0; 1c. Evidence: Y-14, N-2, I-0Rationale:• The measure applies to lung and pancreatic cancer, with lung especially being a prevalent cancer with high morbidity and mortality. Radiation is a commonly used treatment.• There was evidence cited showing 89% compliance with the PQRS measure, which highlights some, but not much room for improvement. The Steering Committee considered this a “never event” and felt compliance should be 100%.• The Steering Committee stated the importance of calculating dose limits when giving radiation to a patient and noted that there is evidence to support this practice.
  
  
• Review for Scientific Acceptability: The measure meets the Scientific Acceptability criteria.(2a. Reliability – precise specifications, testing; 2b. Validity – testing, threats to validity)2a. Reliability: H-11; M-5; L-0; I-0; 2b. Validity: H-7; M-9; L-0; I-0Rationale:• The measure contains specifications that allow for reliable ascertainment and data on reliability.• The measure includes data on face validity from an expert panel.
  
  
• Review for Feasibility: H-11; M-5; L-0; I-0(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:• The data elements are all feasibly extracted from an EHR and generated during routine care delivery.
  
  
• Review for Usability: H-10; M-6; L-0; I-0(Meaningful, understandable, and useful to the intended audiences for 3a. Public Reporting and 3b. Quality Improvement)Rationale:• The measure has been successfully implemented in PQRS.• The measure should be easily understood for public reporting.
  
  
• Endorsement Public Comments: Comments included:• Commenters were concerned that the measure only assesses standard practice that should be occurring routinely.Developer Response:• Identifying normal tissue dose constraints is an important step in the process of care for patients receiving radiation therapy treatments with significant impact on outcomes including reducing the toxic effects of radiation to normal tissues and subsequently reducing the long term potential for late carcinogenesis and a second malignancy, while delivering the desired dose distribution of radiation to target tissue. Unfortunately, as indicated by performance rates for this measure noted in the submission form, adherence remains suboptimal demonstrating a significant opportunity to improve the care provided to cancer patients.Steering Committee Response:• The Steering Committee agrees with the developer’s response, which is in line with discussions that occurred at the in-person meeting and on related conference calls.
  
  
• Endorsement Committee Recommendation: Y-16; N-0Rationale: The Steering Committee noted that there is near universal concordance from an expert panel, excellent reliability, usability, and feasibility, and the target population comprises large numbers. There is no contradictory evidence for the measure.