NQF

Agenda Synopsis

Full Agenda

Measure Index

• Standardized Transfusion Ratio for Dialysis Facilities (Public comments received:1; MUC ID: MUC2019-64)
  
  

• Maternal Morbidity (Public comments received:4; MUC ID: MUC2019-114)
  
  
• Hospital Harm - Severe Hyperglycemia (Public comments received:5; MUC ID: MUC2019-26)
  
  

• Follow-Up After Psychiatric Hospitalization (Public comments received:2; MUC ID: MUC2019-22)
  
  

• National Healthcare Safety Network (NHSN) Catheter-Associated Urinary Tract Infection Outcome Measure (Public comments received: 0; MUC ID: MUC2019-18)
  
  
• National Healthcare Safety Network (NHSN) Central Line Associated Bloodstream Infection Outcome Measure (Public comments received: 0; MUC ID: MUC2019-19)
  
  

Full Measure Information

Measure Specifications

• NQF Number (if applicable): 2979
  
  
• Description: The risk adjusted facility level transfusion ratio (STR) is specified for all adult dialysis patients. It is a ratio of the number of eligible red blood cell transfusion events observed in patients dialyzing at a facility, to the number of eligible transfusion events that would be expected under a national norm, after accounting for the patient characteristics within each facility. Eligible transfusions are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.This measure is calculated as a ratio, but can also be expressed as a rate.
  
  
• Numerator: Number of eligible observed red blood cell transfusion events: An event is defined as the transfer of one or more units of blood or blood products into a recipient’s blood stream (code set is provided in the numerator details) among patients dialyzing at the facility during the inclusion episodes of the reporting period. Inclusion episodes are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.
  
  
• Denominator: Number of eligible red blood cell transfusion events (as defined in the numerator statement) that would be expected among patients at a facility during the reporting period, given the patient mix at the facility. Inclusion episodes are those that do not have any claims pertaining to the comorbidities identified for exclusion, in the one year look back period prior to each observation window.
  
  
• Exclusions: All transfusions associated with transplant hospitalization are excluded. Patients are also excluded if they have a Medicare claim for: hemolytic and aplastic anemia, solid organ cancer (breast, prostate, lung, digestive tract and others), lymphoma, carcinoma in situ, coagulation disorders, multiple myeloma, myelodysplastic syndrome and myelofibrosis, leukemia, head and neck cancer, other cancers (connective tissue, skin, and others), metastatic cancer, and sickle cell anemia within one year of their patient time at risk. Since these comorbidities are associated with higher risk of transfusion and require different anemia management practices that the measure is not intended to address, every patient's risk window is modified to have at least 1 year free of claims that contain these exclusion eligible diagnoses.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims;CROWNWeb
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Management of chronic conditions
  
  
• 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 for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This measure is based on NQF #2979, which is currently included in the ESRD QIP program. The measure has undergone substantial updates related to the codes used in the transfusion definition and the handling of Medicare Advantage. The measure addresses the Meaningful Measure Area of management of chronic conditions for ESRD QIP. This updated and re-specified claims-based outcome measure has been submitted endorsement review by the NQF Renal Standing Committee in CDP Fall Cycle 2019. Conditional support pending NQF review and endorsement.
  • Impact on quality of care for patients:This measure encourages the appropriate prevention and management of anemia for patients in dialysis facilities.
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure addresses the Meaningful Measure Area of management of chronic conditions. ESRD QIP aims to incorporate measures that address the care coordination and safety of ESRD patients when receiving care. This measure is an updated version of the existing measure, NQF #2979 in ESRD QIP.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? Yes. This is an outcome measure that assesses the ratio of the number of eligible red blood cell transfusion events observed in patients dialyzing at a facility, to the number of eligible transfusion events that would be expected under a national norm, after accounting for the patient characteristics within each facility. MAP should consider the role that dialysis facilities have in making decisions about transfusions and their role in impacting this important patient outcome.
  
  
• Does the measure address a quality challenge? Yes. The STrR calculates a ratio of the number of eligible red blood cell transfusion events observed in patients dialyzing at a facility, to the number of eligible transfusion events that would be expected under a national norm, after accounting for the patient characteristics within each facility. The distribution of standardized transfusion ratio (STrR) using Medicare claims data ranged from from a mean of 1.025 in 2014 to a mean of 1.058 in 2017. The range of facility performance in 2017 ranges from 0.273 (10th percentile) to 1.865 (90th percentile). This range represents an opportunity for improvement.
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? N/A. This measure is an updated version of the existing measure, NQF #2979, in ESRD QIP. There are two significant differences between the current NQF-endorsed STrR used on DFC and in QIP PY2021 and the proposed revision submitted here. There are several differences in the updated proposed measure. The inpatient transfusion events are identified using on a broader definition that include revenue center codes only, ICD9/ICD10 procedure codes or value codes alone or in combination. The proposed revision will result in identification of a greater number of inpatient transfusion events compared to the currently implemented STrR. In addition, the proposed revision will effectively counter a provider coding bias that was accentuated by the conversion from ICD9 to ICD10 code sets in late CY2015. The proposed STrR revision also excludes all Medicare Advantage patients time at risk from both the measure numerator and denominator. This proposed change is being made to mitigate potential bias associated with inclusion of Medicare Advantage patients. The bias derives from the absence of complete outpatient claims data for Medicare Advantage patients, severely limiting the identification of outpatient transfusion events for these individuals, and, eliminating a key source for claims-based exclusion comorbidities.
  
  
• Can the measure can be feasibly reported? Yes. This is a claims-based measure. MAP should also consider the role that transfucsion coding practices mau have on influrancing performance on this measure.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? Yes. The measure is specified and tested at the facility level of analysis in the dialysis facility setting.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? No. This measure is not in current use. The developer does not anticipate unintended negative consequences.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: Diabetes is a condition that impacts many rural residents. Moreover, rural patients may be diagnosed late in the course of illness and thus be more likely to need dialysis. The Workgroup confirmed that there are dialysis facilities in rural areas.
  • Data collection issues: None
  • Calculation issues: None
  • Unintended consequences: The Workgroup noted that some rural patients need to travel 100 miles or more to receive dialysis.
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 3.9
  • Vote Counts: (1 – 0 votes; 2 – 0 votes; 3 – 2 votes; 4 – 11 votes; 5 – 1 vote)
  • Program gap areas:The Workgroup recommended the addition of end-of-life care planning measures for the ESRD QIP.
  
  
  

Rationale for measure provided by HHS
The Medicare ESRD Program requires Medicare certified dialysis facilities to manage the anemia of CKD as one of their responsibilities under the Conditions for Coverage (1). In addition, the Medicare ESRD Program has included payment for ESAs in dialysis facility reimbursement since 1989. It is notable that inclusion of ESAs in dialysis program payment was associated with a dramatic reduction in the use of blood transfusions in the US chronic dialysis population (2-3). Recently, reliance on achieved hemoglobin concentration as an indicator of successful anemia management in this population has been de-emphasized and use of other clinically meaningful outcomes, such as transfusion avoidance, have been recommended as alternate measures of anemia management (4-7).
Best dialysis provider practice should include effective anemia management algorithms that focus on 1) prevention and treatment of iron deficiency, inflammation and other causes of ESA resistance, 2) use of the lowest dose of ESAs that achieves an appropriate target hemoglobin that is consistent with FDA guidelines and current best practices, and 3) education of patients, their families and medical providers to avoid unnecessary blood transfusion so that risk of allosensitization is minimized, eliminating or reducing one preventable barrier to successful kidney transplantation.
The decision to transfuse blood is intended to improve or correct the pathophysiologic consequences of severe anemia, defined by achieved hemoglobin or hematocrit%, in a specific clinical context for each patient situation (8). Consensus guidelines in the U.S. and other consensus guidelines defining appropriate use of blood transfusions are based, in large part, on the severity of anemia (9-11). Given the role of hemoglobin as a clinical outcome that defines anemia as well as forms a basis for consensus recommendations regarding use of blood transfusion, it is not surprising that the presence of decreased hemoglobin concentration is a strong predictor of subsequent risk for blood transfusion in multiple settings, including chronic dialysis (12-21). For example, Gilbertson, et al found a nearly four-fold higher risk-adjusted transfusion rate in dialysis patients with achieved hemoglobin <10 gm/dl compared to those with >10 gm/dl hemoglobin. (19) In addition to achieved hemoglobin, other factors related to dialysis facility practices, including the facility’s response to their patients achieved hemoglobin, may influence blood transfusion risk in the chronic dialysis population (22, 25). In an observational study recently published by Molony, et al (2016) comparing different facility level titration practices, among patients with hemoglobin <10 and those with hemoglobin>11, they found increased transfusion risk in patients with larger ESA dose reductions and smaller dose escalations, and reduced transfusion risk in patients with larger ESA dose increases and smaller dose reductions (25). The authors reported no clinically meaningful differences in all-cause or cause-specific hospitalization events across groups.
The Food and Drug Administration position defining the primary indication of ESA use in the CKD population is for transfusion avoidance, reflecting the assessment of the relative risks and benefits of ESA use versus blood transfusion. Several historical studies, and one recent research study reviewed by Obrador and Macdougall, document the specific risks of allosensitization after blood transfusion and the potential for transfusion-associated allosensitization to interfere with timely kidney transplantation. (23) A recent analysis demonstrated increased odds ratios for allosensitization associated with transfusion, particularly for men and parous women. That study also demonstrated a 28% reduction in likelihood of transplantation in transfused individuals, based on a multivariate risk-adjusted statistical model. (24) REFERENCES1. ESRD Facility Conditions for Coverage. https://www.cms.gov/Center/Special-Topic/End-Stage-Renal-Disease-ESRD-Center.html. 2. Eschbach et al. Recombinant Human Erythropoietin in Anemic Patients with End-Stage Renal Disease. Results of a Phase III Multicenter Clinical Trial. Annals of Internal Medicine. 1989;111:992-1000.3. Powe et al. Early dosing practices and effectiveness of recombinant human erythropoietin. Kidney International, Vol. 43 (1993), pp. 1125—1133. 4. FDA Drug Safety Communication: Modified dosing recommendations to improve the safe use of Erythropoiesis-Stimulating Agents (ESAs) in chronic kidney disease. http://www.fda.gov/Drugs/DrugSafety/ucm259639.htm. 5. Kidney Disease: Improving Global Outcomes (KDIGO) Anemia Work Group. KDIGO Clinical Practice Guideline for Anemia in Chronic Kidney Disease. Kidney inter., Suppl. 2012; 2: 279–335. http://www.kdigo.org/clinical_practice_guidelines/pdf/KDIGO-Anemia%20GL.pdf.6. Kliger et al. KDOQI US Commentary on the 2012 KDIGO Clinical Practice Guideline for Anemia in CKD. Am J Kidney Dis. 62(5):849-859. 7. Berns, Jeffrey S., Moving Away From Hemoglobin-Based Anemia Performance Measures in Dialysis Patients. Am J Kidney Dis. 2014;64(4):486-488. 8. Whitman, Shreay, Gitlin, van Oijen, & Spiegel. Clinical Factors and the Decision to Transfuse Chronic Dialysis Patients. Clin J Am Soc Nephrol 8: ccc–ccc, 2013. doi: 10.2215/CJN.00160113. 9. Carson et al. Red Blood Cell Transfusion: A Clinical Practice Guideline From the AABB. Ann Intern Med. 2012;157:49-58. 10. American Society of Anesthesiologists Task Force on Perioperative Blood Transfusion and Adjuvant Therapies. Practice guidelines for perioperative blood transfusion and adjuvant therapies: an updated report by the American Society of Anesthesiologists Task Force on Perioperative Blood Transfusion and Adjuvant Therapies. Anesthesiology. 2006;105:198–208. 11. Munoz et al. “Fit to flyâ€; overcoming barriers to preoperative haemoglobin optimization in surgical patients. Br J Anaesth. 2015 Jul;115(1):15-24. 12. Dunne, Malone, Tracy, Gannon, and Napolitano. Perioperative Anemia: An Independent Risk Factor for Infection, Mortality, and Resource Utilization in Surgery. Journal of Surgical Research 102, 237-244 (2002). 13. Covin R, O'Brien M, Grunwald G, Brimhall B, Sethi G, Walczak S, Reiquam W, Rajagopalan C, Shroyer AL Factors affecting transfusion of fresh frozen plasma, platelets, and red blood cells during elective coronary artery bypass graft surgery. Arch Pathol Lab Med. 2003 Apr;127(4):415-23. 14. Jans et al. Role of preoperative anemia for risk of transfusion and postoperative morbidity in fast-track hip and knee arthroplasty. Transfusion. 2014 Mar;54(3):717-26.15. Saleh et al. Allogenic Blood Transfusion Following Total Hip Arthroplasty: Results from the Nationwide Inpatient Sample, 2000 to 2009. J Bone Joint Surg Am. 2014;96:e155(1-10).16. Ejaz, Spolverato, Kim, Frank, and Pawlik. Variations in triggers and use of perioperative blood transfusions in major gastrointestinal surgery. Br. J. Surg. 2014 Oct;101(11):1424-33.17. Foley, Curtis, & Parfrey. Hemoglobin Targets and Blood Transfusions in Hemodialysis Patients without Symptomatic Cardiac Disease Receiving Erythropoietin Therapy. Clin J Am Soc Nephrol 3: 1669–1675, 2008. doi: 10.2215/CJN.02100508. 18. Hirth, Turenne, Wilk et al. Blood transfusion practices in dialysis patients in a dynamic regulatory environment. Am J Kidney Dis. 2014 Oct;64(4):616-21. doi: 10.1053/j.ajkd.2014.01.011. Epub 2014 Feb. 19. Gilbertson, Monda, Bradbury & Collins. RBC Transfusions Among Hemodialysis Patients (1999-2010): Influence of Hemoglobin Concentrations Below 10 g/dL. Am J Kidney Dis. 2013; Volume 62 , Issue 5 , 919 – 928.20. Collins et al. Effect of Facility-Level Hemoglobin Concentration on Dialysis Patient Risk of Transfusion. Am J Kidney Dis. 2014; 63(6):997-1006. 21. Cappell et al. Red blood cell (RBC) transfusion rates among US chronic dialysis patients during changes to Medicare end-stage renal disease (ESRD) reimbursement systems and erythropoiesis stimulating agent (ESA) labels. BMC Nephrology 2014, 15:116. 22. House AA, Pham B, Pagé DE. Transfusion and recombinant human erythropoietin requirements differ between dialysis modalities. Nephrol Dial Transplant. 1998 Jul;13(7):1763-9. 23. Obrador and Macdougall. Effect of Red Cell Transfusions on Future Kidney Transplantation. Clin J Am Soc Nephrol 8: 852–860, 2013.24. Ibrahim, et al. Blood transfusions in kidney transplant candidates are common and associated with adverse outcomes. Clin Transplant 2011: 25: 653–659. 25. Molony, et al. Effects of epoetin alfa titration practices, implemented after changes to product labeling, on hemoglobin levels, transfusion use, and hospitalization rates. Am J Kidney Dis 2016: epub before print (published online March 12, 2016).

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2017
  
  
• Project for Most Recent Endorsement Review: Renal 2015-2017
  
  
• Review for Importance: 1a. Evidence: Y-18; N-2; 1b. Performance Gap: H-2; M-12; L-5; I-1Rationale:• The Committee discussed whether or not this measure would be more appropriatelycategorized as an intermediate outcome. The Committee discussed how the use of scarceresources, particularly when comparing an event to a non-event--even if it is a relatively scarceevent-- is considered an appropriate health outcome metric for the healthcare system, but notfor the individual patient. The Committee proceeded to evaluate the measure as an outcomemeasure.• The Committee passed the measure on evidence, agreeing that providers can take actions (e.g.,utilization of treatments to increase blood cell production) to reduce the occurrence oftransfusions.• Committee members noted that dialysis patients who are eligible for kidney transplant and aretransfused risk the development of becoming sensitized to the donor pool, thereby leading topotential negative consequences for kidney transplantation. Monitoring the risk-adjustedtransfusion rate at the dialysis facility level, relative to a national standard, allows for detectionof treatment patterns in dialysis-related anemia management.• Some Committee members noted they found the evidence to be most convincing in terms ofnegative downstream implications for a kidney transplant; others noted that downstreameffects are difficult to know, as are the appropriate number of transplants in terms of cost andpatient outcomes. Overall, the Committee agreed that the national standard of practice istransfusion avoidance.• CROWNWeb and Medicare claims data for 2011-2014 showed that standardized transfusionratios vary across facilities. Analyses of the standardized transfusion ratios (STrR) by race, sexand ethnicity indicate relatively little variation and no disparities substantial to the measure 25among these groups. The Committee agreed that opportunity for improvement for performanceof this measure remains moderate.
  
  
• Review for Scientific Acceptability: 2a. Reliability: H-0; M-15; L-5; I-0; 2b. Validity: H-0; M-15; L-5; I-0Rationale:• Some Committee members had concerns about the specifications, specifically the lack ofexclusion related to patients who may need transfusions due to acute gastrointestinal bleeds,trauma, or other unplanned surgery.• Developers provided results of reliability testing of the performance measure score usingMedicare claims data from 2011-2014 at the facility level of analysis. Inter-unit reliability (IUR)was estimated using a bootstrap approach, which uses a resampling scheme to estimate thewithin-facility variation that cannot be directly estimated by a one-way analysis of variance. IURshad a range of 0.60-0.66 across the years 2011, 2012, 2013 and 2014, indicating that aroundtwo-thirds of the variation in the one-year STrR can be attributed to the between-facilitydifferences and one-third to within-facility variation. Committee members noted that whenstratified by facility size, the measure has higher IUR in larger dialysis facilities and lower IUR insmaller facilities. While some concern was expressed over the lower reliability for small facilities,the Committee generally agreed that the testing results demonstrate moderate reliability.• To demonstrate validity of the performance measure score, developers used Poisson regressionmodels to measure the association between STrR and other facility level outcomes,Standardized Mortality Ratio (SMR, NQF #0369) and Standardized Hospitalization Ratio (SHR,NQF 1463). The results from the Poisson model indicated that the StrR tertiles were significantlyassociated with both SMR and SHR. The developer also noted that a similar analysis wasperformed to compare StTR scores with facility-achieved hemoglobin levels; the analysis foundthat the percentage of patients with hemoglobin greater than 10 was positively associated withrisk of transfusion.• In addition, face validity was demonstrated, including a statement from the developers that sixout of the six voting members of CMS's 2012 Technical Expert Panel voted to recommend thedevelopment of a facility-level standardized transfusion average. Overall, the Committee agreedthat the testing results demonstrate moderate validity.
  
  
• Review for Feasibility: 3. Feasibility: H-15; M-4; L-0; I-0(3a. Data generated during care; 3b. Electronic sources; and 3c. Data collection can be implemented(eMeasure feasibility assessment of data elements and logic)Rationale:• The Committee agreed that it is feasible to collect the data. Members also agreed that the dataelements are generated as part of the care delivery process.
  
  
• Review for Usability: 4. Usability and Use: H-5; M-13; L-1; I-0(4a. Accountability/transparency; and 4b. Improvement – progress demonstrated; and 4c. Benefitsoutweigh evidence of unintended negative consequences)26Rationale:• This measure is publically reported nationally in Dialysis Facility Compare (DFC) and will be inEnd Stage Renal Disease Quality Incentive Program (ESRD QIP) starting 2018.• Committee members noted that a potential unintended consequence of the STrR would be tocreate an incentive for dialysis facilities to target higher hemoglobin levels, as targetinghemoglobin concentrations above 12 to 13 grams per deciliter is associated with elevated risk ofcardiac events and related mortality. However, the Committee accepted the developer’srationale that the potential for unintended consequences is low with appropriate provideranemia management practices.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Public Comments: 6. Public and Member Comment• The Kidney Care Partners notes that during the last project, this Standing Committee reviewedthe STrR as #2699 and did not recommend it. The commenter expresses concern about thespecifications, reliability, validity (risk model), and harmonization. In regards to validity, thecommenter does not believe the new measure addressed the Committee’s concerns abouthospital- and physician-related factors. Overall, they remain concerned about the reliability, aswell as the specifications and validity. The commenter strongly encouraged the Committee toreconsider the reliability testing data, which document reliability issues with the STrR for smallfacilities, and comment specifically on the STrR’s reliability for such facilities.• The Committee thoroughly reviewed the specifications, reliability, and validity of the measureduring the in-person and maintained that the measure meets the NQF criteria.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-16; N-4
  
  

Measure Specifications

• NQF Number (if applicable): 0
  
  
• Description: Structural Measure to address severe maternal morbidity in the inpatient hospital setting.
  
  
• Numerator: Not Applicable (this is a structural measure)
  
  
• Denominator: Not Applicable
  
  
• Exclusions: None
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: TBD
  
  
• Measure Type: Structure
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Preventable healthcare harm
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Do Not Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:While the Hospital Inpatient Quality Reporting program does not currently include any measures assessing maternal morbidity, the measure is a structural measure without evidence on how participation in a QI collaborative can improve maternal morbidity, or that attestation to the same is indicative of maternal care quality and better outcomes. The developer should complete measure development and submit to NQF for review and endorsement.
  • Impact on quality of care for patients:Participation in QI initiatives should be undertaken by hospitals to share best practices and drive improvement in clinical care. It is unclear how participation in these QI initiatives will impact outcomes most important to patients, or how strong the links between attestation and actual quality care are. Efforts should be undertaken to develop quality outcome measures that address severe morbidity and mortality rates during delivery and the postpartum period.
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure aims to address the Meaningful Measure Area of preventable healthcare harm for the IQR program. The measure is in early development and will be focused on reducing maternal morbidity and mortality.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? No. The developer does not provide peer reviewed evidence that participation in QI collaboratives leads to reductions in maternal morbidity and mortality to support this structure measure.
  
  
• Does the measure address a quality challenge? Yes. Maternal morbidity is a significant US health care quality issue. Severe morbidity rates for delivery and postpartum hospitalizations for the 2008–2009 period were 129 and 29, respectively, for every 10,000 delivery hospitalizations. However, the developer does not provide evidence of a performance gap to support this measure or how a performance gap in participation in a QI collborative will improve maternal morbidity outcomes (Callaghan et al.,2012).
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? Yes. The Hospital Inpatient Quality Reporting program does not currently include any measures assessing maternal morbidity and mortality.
  
  
• Can the measure can be feasibly reported? Yes. The measure is expected to be reported to the program through attestation.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? N/A. Specifications and testing information for this measure have not been provided. The developer states that the intended care setting and level of analysis is to be determined. The target population is also to be determined, but the developer notes it will most likely be all payer.
  
  
• Measure development status: Early Development
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? N/A. This measure is not currently in use.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: Maternal morbidity is a significant problem for rural areas. Relevant improvement collaboratives exist in some rural areas (e.g., Alaska) but it is unclear whether similar opportunities exist more broadly.
  • Data collection issues: None
  • Calculation issues:Many rural hospitals do not have OB departments, so clarity is needed on whether such hospitals would be included in the measure and/or if a minimum number of deliveries would be needed to be included in the measure.
  • Unintended consequences: Small hospitals in rural areas might not be able to provide optimal obstetric care in high risk cases due to lack of resources (although they can and do connect such patients to facilities/services to meet this need).
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 3.3
  • Vote Counts: (1 – 3 votes; 2 – 1 vote; 3 – 2 votes; 4 – 3 votes; 5 – 4 votes)
  • Program gap areas:The Workgroup recommended inclusion of measures that assess care coordination.
  
  
  

Rationale for measure provided by HHS
The rationale for this measure to address Severe Maternal Morbidity (SMM) is that SMM is increasing at an alarming rate in the U.S. Rates have nearly doubled over the past decade. Evidence shows that there is a high rate of preventability of SMM and 60% of maternal deaths are preventable. Identification and effective treatment of SMM are very essential to prevent conditions that lead to maternal mortality. There are currently no quality measures that address maternal morbidity as a whole and the CMS Office of the Administrator (OA) is very dedicated in addressing this healthcare crisis. The structural measure will evaluate how many hospitals and health systems are working within any type of quality improvement collaborative which has proven to help prevent and manage SMM. This measure will eventually be replaced by a comprehensive outcome measure.

Measure Specifications

• NQF Number (if applicable): 0
  
  
• Description: This measure assesses the proportion of hospital days with a severe hyperglycemic event for hospitalized patients 18 or older who have a diagnosis of diabetes mellitus, have received at least one administration of insulin or an anti-diabetic medication during the hospital admission, or have had an elevated blood glucose level (>200 mg/dL) during their hospital admission.
  
  
• Numerator: Number of hospital days with a severe hyperglycemic event, defined as: (1) a day with at least one blood glucose value >300 mg/dL; or (2) a day without any measurement of blood glucose level, and not preceded by two consecutive days where blood glucose levels were measured and all values were <200 mg/dL.Hospital days are measured in 24-hour periods starting from the time of arrival at the hospital (including Emergency Department).
  
  
• Denominator: The initial population is patients 18 years and older (age at the start of the hospital encounter) with a discharged inpatient hospital encounter during the measurement period, and at least one of the following: (1) a diagnosis of diabetes that starts before or during the encounter; or (2) at least one administration of insulin or any anti-diabetic medication during the encounter; or (3) at least one blood glucose value >200 mg/dL at any time during the encounter. The measure includes inpatient admissions for patients who were directly admitted, or who were initially seen in the emergency department or in observation status and subsequently became an inpatient.The denominator is the total number of eligible days across all encounters which match the initial population criteria. We do not count the first 24-hour period after admission to the hospital (including the Emergency Department) or the last time period before discharge, if it was less than 24 hours. Eligible encounters that exceed 10 days are truncated to equal 10 days.
  
  
• Exclusions: N/A
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: EHR
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Preventable healthcare harm
  
  
• 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? Yes
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This fully developed and specified measure addresses the priority area of preventable healthcare harm for the IQR program. IQR currently does not include a measure that assesses severe hyperglycemia events that are largely avoidable through proper glycemic monitoring and intervention.This measure has been submitted for endorsement review to the NQF Patient Safety Standing Committee in CDP Fall Cycle 2019. Conditional support pending NQF review and endorsement.
  • Impact on quality of care for patients:Measuring hyperglycemia events in the hospital setting will provide hospitals with a reliable and timely measurement of their hyperglycemia event rates. With a systematic EHR-based hospital harm measure in place, hospitals can more reliably assess harm reduction efforts and modify their improvement efforts in near real-time (Falciglia et al., 2009).
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure addresses the Meaningful Measure Area of preventable healthcare harm and making care safer by reducing harm caused in the delivery of care. Currently, IQR does not include measures of preventable harm related to diabetes management.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? Yes. This is an outcome measures that assesses the proportion of hospital days with a severe hyperglycemic event for hospitalized patients with a diagnosis of diabetes mellitus. Hyperglycemia can be considered a marker of poor quality care and is largely avoidable with proper glycemic management. The developer cites several peer reviewed articles to support the link between hospital initiated interventions and property glycemic management.
  
  
• Does the measure address a quality challenge? Yes. The rate of severe hyperglycemia varies across hospitals, suggesting opportunities for improvement in inpatient glycemic management. One study analyzed 1.13 million patient-days from 94 hospitals and reported the rate of severe hyperglycemia (glucose >299 mg/dL) among hospitalized non-critical care patients at 10.2% (range: 1.8% to 17.7%) of patient days.
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? Yes. The Hospital Inpatient Quality Reporting program does not currently include any measures assessing hyperglycemia events.
  
  
• Can the measure can be feasibly reported? Yes. This a new eCQM outcome measure that has never been used in a federal quality program.This measure is based on data elements that are in structured fields and easily extractable from the electronic health record (EHR). The developer has conducted feasibility testing and states the testing confirms the feasibility of the measure.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? Yes. The measure is specified and tested at the facility level of analysis in the hospital/acute care facility setting. This measure has been submitted for endorsement review by the NQF Patient Safety Standing Committee in CDP Fall Cycle 2019.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? N/A. This measure is not currently in use. The developer noted measuring hospital harm based on EHR data may cause a shift in a hospital’s resources to support EHR data infrastructure and the routine harm data extraction and away from other functions. Hospitals may potentially focus on harms captured in the measure, while dismissing other important harms not currently measured. The developer noted that stakeholders raised concerns of a possible increase in frequency of hypoglycemia events, in efforts to reduce rates of hyperglycemia. This measure will be paired with the Hospital Harm - Severe Hypoglycemia eCQM to avoid any unintended consequences. MAP conditionally supported Hospital Harm - Severe Hypoglycemia eCQM during the MAP 2018-2019 cycle for IQR pending NQF review and re-endorsement once the revised measure is fully tested. The NQF Patient Safety Standing Committee endorsed NQF #3503 Hospital Harm – Severe Hypoglycemia in the CDP Spring 2019 Cycle.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: Diabetes rates are high in rural settings, and the measure addresses a preventable patient safety issue that is relevant for rural populations.
  • Data collection issues: If glucose levels are derived from laboratory data (rather than at point of care), they may be more difficult to obtain and/or incorporate into EHR systems in rural hospitals.
  • Calculation issues:EHR systems in rural hospitals may not be as robust or current, making it more difficult to compute the measure (e.g., using RxNORM).
  • Unintended consequences: None.
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 3.9
  • Vote Counts: (1 – 0 votes; 2 – 1 vote; 3 – 2 votes; 4 – 8 votes; 5 – 3 votes)
  • Program gap areas:The Workgroup noted need for measures that assess the efficacy of transfers and coordination of care.
  
  
  

Rationale for measure provided by HHS
Severe hyperglycemia - an extremely elevated blood glucose level - is significantly associated with a range of harms, including increased in-hospital mortality, infection rates, and hospital length of stay.5-9 Moreover, the rate of severe hyperglycemia varies across hospitals, suggesting opportunities for improvement in inpatient glycemic management.10 The rate of inpatient hyperglycemia can be considered a marker for quality of hospital care, since inpatient hyperglycemia is largely avoidable with proper glycemic management. The use of evidence-based standardized protocols and insulin management protocols have been shown to improve glycemic control and safety.11-12References:5. Falciglia M, Freyberg RW, Almenoff PL, D'Alessio DA, Render ML. Hyperglycemia-Related Mortality in Critically Ill Patients Varies with Admission Diagnosis. Crit Care Med. 2009;37(12):3001-3009. 6. King JT, Jr., Goulet JL, Perkal MF, Rosenthal RA. Glycemic Control and Infections in Patients with Diabetes Undergoing Noncardiac Surgery. Ann Surg. 2011;253(1):158-165. 7. Pasquel FJ, Spiegelman R, McCauley M, et al. Hyperglycemia During Total Parenteral Nutrition: An Important Marker of PoorOutcome and Mortality in Hospitalized Patients. Diabetes Care. 2010;33(4):739-741. 8. Rady MY, Johnson DJ, Patel BM, Larson JS, Helmers RA. Influence of Individual Characteristics on Outcome of Glycemic Control in Intensive Care Unit Patients With or Without Diabetes Mellitus. Mayo Clin Proc. 2005;80(12):1558-1567. 9. Umpierrez GE, Isaacs SD, Bazargan N, You X, Thaler LM, Kitabchi AE. Hyperglycemia: An Independent Marker of In-Hospital Mortality in Patients with Undiagnosed Diabetes. J Clin Endocrinol Metab. 2002;87(3):978-982. 10. Swanson CM, Potter DJ, Kongable GL, Cook CB. Update on Inpatient Glycemic Control in Hospitals in the United States. Endocr Pract. 2011;17(6):853-861. 11. Donihi AC, DiNardo MM, DeVita MA, Korytkowski MT. Use of a Standardized Protocol to Decrease Medication Errors and Adverse Events Related to Sliding Scale Insulin. Qual Saf Health Care. 2006;15(2):89-91. 12. Maynard G, Kulasa K, Ramos P, et al. Impact of a Hypoglycemia Reduction Bundle and a Systems Approach to Inpatient Glycemic Management. Endocr Pract. 2015;21(4):355-367.

Measure Specifications

• NQF Number (if applicable): 0
  
  
• Description: The Follow-Up After Psychiatric Hospitalization measure assesses the percentage of inpatient discharges with principal diagnoses of select mental illness or substance use disorders (SUD) for which the patient received a follow-up visit for treatment of mental illness or SUD. Two rates are reported:1. Percentage of discharges for which the patient received follow-up within 7 days of discharge2. Percentage of discharges for which the patient received follow-up within 30 days of dischargeThe performance period used to identify denominator cases is 12 months. Data from the performance period and 30 days after are used to identify follow-up visits in the numerator.
  
  
• Numerator: The numerator includes discharges from a psychiatric facility that are followed by an outpatient visit for treatment of mental illness or SUD within 7 and 30 days. Outpatient visits are defined as outpatient visits, intensive outpatient encounters, or partial hospitalization. For additional information, see HSAG. Draft Methodology Report: Follow-Up After Psychiatric Hospitalization, Version 1.0. Prepared for CMS by Health Services Advisory Group, Inc., Contract HHSM-500-2013-13007I, Task Order HHSM-500-T0004, 37 pages (7 January 2019).
  
  
• Denominator: The denominator includes discharges paid under the inpatient psychiatric facility (IPF) prospective payment system (PPS) during the performance period for Medicare fee-for-service (FFS) patients with a principal diagnosis of mental illness or substance use disorder. For additional information, see HSAG. Draft Methodology Report: Follow-Up After Psychiatric Hospitalization, Version 1.0. Prepared for CMS by Health Services Advisory Group, Inc., Contract HHSM-500-2013-13007I, Task Order HHSM-500-T0004, 37 pages (7 January 2019).
  
  
• Exclusions: Medicare files are used to identify all exclusions. The denominator excludes inpatient psychiatric facility (IPF) discharges for patients:
  • Admitted or transferred to acute and non-acute inpatient facilities within the 30-day follow-up period because admission or transfer to other institutions may prevent an outpatient follow-up visit from taking place.
  • Who were discharged against medical advice (AMA) because the IPF may have limited opportunity to complete treatment and prepare for discharge.
  • Who died during the 30-day follow-up period because patients who expire may not have the opportunity for an outpatient follow-up visit.
  • Who use hospice services or elect to use a hospice benefit any time during the measurement year, regardless of when the services began because patients in hospice may require different follow-up services.
  
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: Claims
  
  
• Measure Type: Process
  
  
• Steward: Centers for Medicare & Medicaid Services
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Prevention, treatment, and management of mental health
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Conditional Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:The Follow-Up After Psychiatric Hospitalization (FAPH) measure is an expansion of the existing Inpatient Psychiatric Facility Quality Reporting program Follow-Up After Hospitalization for Mental Illness (IPFQR FUH) measure that was adapted from the NQF #0576. During the 2017 comprehensive review of NQF #0576, the NQF Behavioral Health Standing Committee (BHSC) recommended expanding the measure population to include patients hospitalized for drug and alcohol disorders because those patients also require follow-up care post-discharge. This fully tested and specified claims-based process measure should be submitted to NQF for endorsement review.
  • Impact on quality of care for patients:The Follow-Up After Psychiatric Hospitalization measure can enhance compliance with clinical guidelines as facilities will receive better scores by conducting follow-up visits with discharged patients, thus improving the continuity of care and monitoring of patients.
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure aims to primarily address the Meaningful Measure Area of prevention, treatment, and management of mental health. The measure also addresses the Meaningful Measure Area of promote effective communication and care coordination. IPFQR aims to incorporate measures that address preventable health care harm.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? Yes. This is a process measures that assesses the percentage of inpatient discharges with principal diagnoses of select mental illness or substance use disorders (SUD) for which the patient received a follow-up visit for treatment of mental illness or SUD.The American Psychiatric Association’s evidence-based guidelines for the treatment of patients with schizophrenia, guidelines for the treatment of patients with bipolar disorder, guidelines for the treatment of patients with major depressive disorder, and guidelines for the treatment of patients with substance use disorders emphasize the importance of continuity of care between settings for patients with mental illness and SUD. For patients with SUD, the guidelines note the importance of intensifying monitoring during periods when the patient is at a high risk of relapsing, including times of care transition.A 2017 study found that receipt of a follow-up visit within 30 days of hospital discharge lowered the readmission risk during days 31 to 120 for patients with schizophrenia and for patients with bipolar disorder (Marcus et al., 2017). Similarly, a 2018 study observed that among patients discharged with schizophrenia, psychiatric readmission rates on days 31-180 were lower if the patient saw a primary care physician or psychiatrist within 30 days of discharge (Kurdyak et al., 2018).
  
  
• Does the measure address a quality challenge? Yes. The developer analyzed a total of 1,432 facilities. The minimum 7-day rate of follow-up was 0.7 percent, and the maximum was 94.7 percent. The mean 30-day rate of follow-up was 61.3 percent.The developer notes that the the wide variation in performance across facilities and large numbers of discharges that would be impacted if facilities met the benchmark 7 and 30-day follow-up rates indicates that there is ample opportunity for improvement on the measure.
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? Yes. There is an exisiting measure in IPRQR, Follow-Up After Hospitalization for Mental Illness (IPFQR FUH), that is similar to this measure. The developer held a call for public comments on this measure. In the call, the developer notes that the measure is primarily an expanded and enhanced version of the Follow-Up After Hospitalization for Mental Illness (IPFQR FUH) measure, and is a replacement for that measure (the Follow-Up After Hospitalization for Mental Illness [HEDIS® FUH] and the Follow-Up After Emergency Department Visit for Alcohol and Other Drug Abuse or Dependence [HEDIS FUA] measures (Mathematica Policy Research, 2019).
  
  
• Can the measure can be feasibly reported? Yes. The measure is calculated using Medicare Part A and Part B claims data. The developer reports that no action is required by facilities to collect and submit data for the measure.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? Yes. The measure is specified and tested at the facility level of analysis in the inpatient psychiatric facility setting.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? N/A. This measure is not in current use. The developer does not anticipate unintended negative consequences.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: Issues of SUD and mental illness impact many rural residents. Rural areas often have psych beds, but fewer psych hospitals, so the Workgroup was uncertain how many rural providers would be affected by this measure.
  • Data collection issues: None.
  • Calculation issues: None.
  • Unintended consequences: The Workgroup noted the shortage of mental/behavioral health providers in rural areas and questioned the availability/access to follow-up care for rural patients and the potential for not admitting rural patients. Similarly, the Workgroup noted that distance from the patient’s home to the facility could be a concern if the admitting hospital is in an urban/suburban area and the follow-up is scheduled near that facility. The Workgroup suggested telehealth as an option for follow-up.
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 3.5
  • Vote Counts: (1 – 0 vote; 2 – 4 votes; 3 – 4 votes; 4 – 4 votes; 5 – 4 votes)
  • Program gap areas: The Workgroup recommended that IPFQR also include measures of access to care.
  
  
  

Rationale for measure provided by HHS
Studies have found that readmission rates for those with psychiatric diagnoses are lower if patients receive follow-up visits within 30 days of discharge. A 2017 study found that receipt of a follow-up visit within 30 days of hospital discharge lowered the readmission risk during days 31 to 120 for patients with schizophrenia and for patients with bipolar disorder. Similarly, a 2018 study observed that among patients discharged with schizophrenia, psychiatric readmission rates on days 31-180 were lower if the patient saw a primary care physician or psychiatrist within 30 days of discharge.Inpatient psychiatric facilities can influence rates of follow-up care for patients hospitalized for mental illness or SUD. Interventions that have been shown effective in the literature include following up with letters or telephone calls, discussing barriers to attending the first outpatient post-discharge appointment with the patient, and serving as a contact for questions or concerns between discharge and the first outpatient appointment. Three studies reported that with certain interventions facilities achieved follow-up rates of 88 percent or more, compared to the national 30-day follow-up rate of approximately 54 percent observed in the current Inpatient Psychiatric Facility Quality Reporting program's Follow-Up After Hospitalization for Mental Illness measure for Medicare FFS discharges between July 1, 2015 and June 30, 2016.

Measure Specifications

• NQF Number (if applicable): 138
  
  
• Description: Standardized Infection Ratio (SIR) of healthcare-associated, catheter-associated urinary tract infections (UTI) will be calculated among patients in bedded inpatient care locations, except level II or level III neonatal intensive care units (NICU). This includes acute care general hospitals, long-term acute care hospitals, rehabilitation hospitals, oncology hospitals, and behavior health hospitals.
  
  
• Numerator: Total number of observed healthcare-associated CAUTI among patients in bedded inpatient care locations (excluding patients in Level II or III neonatal ICUs).
  
  
• Denominator: Total number of predicted healthcare-associated CAUTI among inpatient care locations under surveillance for CAUTI during the data period, based on the national CAUTI baseline (denominator count excludes information about Level II Nursery or NICU locations)
  
  
• Exclusions: Denominator Exclusions: The following are not considered indwelling catheters by NHSN definitions:1.Suprapubic catheters 2.Condom catheters 3."In and out" catheterizations4. Nephrostomy tubesNote, that if a patient has either a nephrostomy tube or a suprapubic catheter and also has an indwelling urinary catheter, the indwelling urinary catheter will be included in the CAUTI surveillance.
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: National Healthcare Safety Network
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Disease Control and Prevention
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Healthcare-associated infections
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This NQF endorsed measure is currently included in PCHQR and addresses the Meaningful Measure Area of healthcare-associated infections not currently included in PCHQR. The risk-adjustment model for this measure was updated and the measure was submitted and re-endorsed by the NQF Patient Safety Standing Committee in the CDP Spring 2019 Cycle. The measure is otherwise identical to the existing measure in PCHQR.
  • Impact on quality of care for patients:This measure enourages the measurement and prevention of a serious adverse outcome caused by CAUTIs for patients in cancer hospitals.CAUTI is the most common type of healthcare-associated infection, accounting for more than 30% of acute care hospital infections. 13,000 deaths are associated with UTIs each year. There are estimated to be 449,334 CAUTI events per year. Each CAUTI is associated with the medical cost of $758. A total of over $340 million spent in health care is attributable to the incident of CAUTI in the U.S. each year (Klevens et al., 2007).
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure addresses the Meaningful Measure Area of healthcare-associated infections. This measure is an updated version of the existing measure, NQF #0138, in PCHQR. The risk-adjustment model for this measure was updated and the measure was submitted and re-endorsed by the NQF Patient Safety Standing Committee in the CDP Spring 2019 Cycle.The measure is otherwise identical to the existing measure in PCHQR.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? Yes. This is an outcome measures that calculates the Standardized Infection Ratio (SIR) of healthcare-associated, catheter-associated urinary tract infections (UTI) among patients in bedded inpatient care locations. A substantial body of peer-reviewed studies demonstrate that infections can be minimized through improvement in central line insertion and maintenance practices. (Patel et al., 2018).
  
  
• Does the measure address a quality challenge? Yes. CAUTI is the most common type of healthcare-associated infection, accounting for more than 30% of acute care hospital infections. 13,000 deaths are associated with UTIs each year. There are estimated to be 449,334 CAUTI events per year. Each CAUTI is associated with the medical cost of $758. A total of over $340 million spent in health care is attributable to the incident of CAUTI in the U.S. each year (Klevens et al., 2007).In 2017, among the 2,589 hospitals in U.S. with enough CAUTI data to calculate a standardized infection ratio (SIR), 11% had an SIR significantly higher (worse) than 0.88, the value of the national SIR.
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? Yes. This measure is currently in multiple CMS programs. The PCHQR program does not currently include any other measures that assess catheter-associated urinary tract infections (UTI) among patients in bedded inpatient care locations.
  
  
• Can the measure can be feasibly reported? Yes. This is an EHR and chart abstracted measure that is currently used in multiple CMS programs, state HAI programs, with collection, analysis, and reporting of measure data by CDC's National Healthcare Safety Network (NHSN) since 2005.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? Yes. The measure is specified and tested at the facility level of analysis.NQF endorsement for this measure was renewed in the CDP Spring 2019 Cycle by the NQF Patient Safety Standing Committee.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? No. The developer does not identify unintended negative consequences. During endorsement review in the CDP Spring 2019 Cycle, NQF received public comments from the Spinal Cord Injury (SCI) physician community, raising concerns that unintended negative consequences could emerge by encouraging bladder management practices that are not consistent with appropriate SCI care and have led to patient harm in this population. The Patient Safety Standing Committee ultimately voted to endorse the measure.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: This measure is not relevant to rural providers, given that the 11 cancer hospitals are located in urban areas. However, cancer hospitals have a wide referral base and therefore care for patients from rural areas.
  • Data collection issues: None.
  • Calculation issues: None.
  • Unintended consequences: The Workgroup suggested that comparisons between cancer hospitals and other hospitals would not be fair because of the higher rates of immunocompromise in patients with cancer.
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 4.0
  • Vote Counts: (1 – 1 vote; 2 – 1 vote; 3 – 0 votes; 4 – 8 votes; 5 – 5 votes)
  • Program gap areas: The Workgroup suggested the addition of PRO-PMs as well as a measure documenting advance care planning.
  
  
  

Rationale for measure provided by HHS
Evidence that this measure promotes CAUTI prevention activities that will lead to improved patient outcomes including reduction of avoidable medical costs, and patient morbidity and mortality through reduced need for antimicrobials and reduced length of stay.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2019
  
  
• Project for Most Recent Endorsement Review: Patient Safety
  
  
• Review for Importance: 1a. Evidence: Pass-20; No Pass-0; 1b. Performance Gap: H-1; M-19; L-0; I-0Rationale:•The Committee agreed that there are preventive activities that can reduce the incidence of CAUTI. These include:oAppropriate catheter useoProper techniques for urinary catheter insertionoProper techniques for urinary catheter maintenance•To support these practices, the developer cites a guideline from the Healthcare Infection Control Practices Advisory Committee (HICPAC): Guideline for Prevention of Catheter-Associated Urinary Tract Infections (2009) revised February 15, 2017.•The developer provided national Standardized Infection Ratios (SIRs) for CAUTI in 2015, 2016, and 2017:oNational Catheter-associated UTI SIR in 2015 is 0.993 = 28,712 observed / 28,910.634 predictedoNational Catheter-associated UTI SIR in 2016 is 0.930 = 26,983 observed / 29,002.430 predictedoNational catheter-associated UTI SIR in 2017 is 0.880 = 24,865 observed / 28,241.960 predicted•The developer also reports that there was a 6% decrease in CAUTI between 2015 and 2016, and a 5% decrease between 2016 and 2017.•The Committee agreed that there is a performance gap warranting measurement in this area; Committee members suggested that the developer analyze and provide data related to performance across different types of institutions (e.g., rehabilitation, acute care, long-term care, etc.).•The Committee also discussed performance gaps on this measure with respect to variation across ethnic groups, rural vs. urban areas, hospital size, and other factors.
  
  
• Review for Scientific Acceptability: 2a. Reliability: M-14; L-4; I-0; 2b. Validity: M-10; L-8; I-2•This measure is deemed as complex and was evaluated by the NQF Scientific Methods Panel.The Standing Committee chose to vote on this measure for, both, reliability and validity.Rationale:•This measure was reviewed for Scientific Acceptability by NQF’s Scientific Methods Panel (SMP).•Data element validity testing was conducted, which NQF accepts as a demonstration of data element reliability.•There was some question from SMP reviewers about the appropriateness of using data element validity testing to stand in for reliability testing. NQF reminded the group that NQF allows this substitution.•The developer notes that the critical data elements of this measure have been validated by several state health departments that require mandatory reporting of CAUTI through the NHSN.•Data validation is conducted by trained auditors, who review medical records and determine whether facilities’ identification of patients meeting CAUTI criteria were accurate.•Sensitivity, specificity, positive predicted value, and negative predicted value are calculated.•Validation results from 10 states are provided—the developer reports that these validations indicated a pooled mean sensitivity of 88.1% (range: 50%-95.6%), specificity of 99.1% (range: 91.4% - 100%), positive predictive value of 94.4% (range: 84.6% - 100%) and negative predictive value of 97.9% (range: 91.4% - 99.8%).•Some SMP reviewers expressed concern about the lack of measure score testing, given that this is a maintenance measure. NQF clarified that either empirical data element or score-level testing are acceptable validity testing methods for maintenance measures.•The measure uses a statistical risk model with risk factors relevant to the facility type. No social risk factors are applied in the modeling.•There was some concern that no statistical results (e.g., c-statistic) of model power were reported.•The Patient Safety Standing Committee discussed the definition of UTIs and the timeframe for determining whether or not a CAUTI is present but focused its discussion largely on the issue of appropriate exclusions, particularly for spinal cord injury (SCI) patients.•A number of representatives of the SCI physician community submitted comments and/or attended the Committee meeting in person to voice their concerns about the measure. These commenters suggested that the measure could be causing unintended adverse consequences by encouraging bladder management practices that are inconsistent with appropriate SCI care and have led to harm for SCI patients.•Representatives of the developer organization (CDC) maintained that there was not enough rigorous evidence supporting exclusion of SCI patients, adding that SCI patients are at high risk for CAUTI and should not be removed from the measure.•Committee members expressed their desire to find a resolution to this issue, noting their general support for the measure and their appreciation of the need for evidence to support exclusions, while also acknowledging that the SCI community had brought forth compelling information suggesting that harm to SCI patients could be an unintended consequence of this measure.•The Committee voted to pass the measure on the Reliability criterion, but consensus was not reached on the Validity criterion.
  
  
• Review for Feasibility: 3. Feasibility: H-2; M-18; 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:•Data for the measure are collected through the National Healthcare Safety Network (NHSN) using a set of standardized forms.•The developer reports that CAUTI and catheter days (the numerator and denominator) must be collected by trained hospital staff from information available in clinical data sources.•The developer notes that some of the data used in the measure can be mined from electronic sources, adding that NHSN is moving towards an electronically captured CAUTI measure for future use. However, development and testing is not complete at this time; barriers include a lack of consistency in the use of electronic records across different platforms and facility types.•The Committee noted that this measure does require manual abstraction of clinical information, but agreed that measuring CAUTI rates is worth the effort.
  
  
• Review for Usability: 4. Use and Usability4a. Use; 4a1. Accountability and transparency; 4a2. Feedback on the measure by those being measured and others; 4b. Usability; 4b1. Improvement; 4b2. The benefits to patients outweigh evidence of unintended negative consequences to patients)4a. Use: Pass-20; No Pass-0 4b. Usability: H-0; M-18; L-0; I-0Rationale:•The measure is used in several accountability programs, including:oHospital Inpatient Quality Reporting Program (HIQR)oHospital Value-Based PurchasingoHospital-Acquired Condition Reduction Program (HACRP)•The developer notes that SIR results are available to NHSN users at any time, based on their current data entry. Data provided within the analysis report includes numerator, denominator, SIR, p-value, and 95% confidence interval. Educational materials are available on the NHSN website that explain each data element.•Based on results from a polling survey, hospitals have indicated that they are running SIR analysis reports within NHSN on a monthly basis, and that they use SIRs for prevention activities in their hospital. State health departments are using the SIR for public reporting purposes and to help target facilities for additional prevention. Feedback was received via email regarding the extent of risk adjustment and the limitations.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Committee Recommendation: Consensus Not Reached
  
  

Measure Specifications

• NQF Number (if applicable): 139
  
  
• Description: Standardized Infection Ratio (SIR) and Adjusted Ranking Metric (ARM) of healthcare-associated, central line-associated bloodstream infections (CLABSI) will be calculated among patients in bedded inpatient care locations.
  
  
• Numerator: Total number of observed healthcare-associated CLABSIs among patients in bedded inpatient care locations.
  
  
• Denominator: Total number of predicted healthcare-associated CLABSI among patients in bedded inpatient care locations, calculated using the facility’s number of central line days and the following significant risk factors:
  • Acute Care Hospitals: CDC location, facility bed size, medical school affiliation, facility type, birthweight category (NICU locations only)
  • Critical Access Hospitals: no significant risk factors, calculation based intercept only model
  • Inpatient Rehabilitation Facilities: Proportion of admissions with stroke, proportion of admissions in other non-specific diagnostic categories
  • Long Term Acute Care Hospitals: CDC location type , facility bed size, average length of stay, proportion of admissions on a ventilator, proportion of admissions on hemodialysis
  
  
  
• Exclusions: S.8. Denominator Exclusions: The following devices are excluded as central lines: oNon-lumened pacemaker wires and other non-lumened devices inserted into central blood vessels or the heart oArterial cathetersoArteriovenous fistulaoArteriovenous graftoExtracorporeal membrane oxygenation (ECMO)oHemodialysis reliable outflow (HERO) dialysis cathetersoIntra-aortic balloon pump (IABP) devicesoAtrial catheters (also known as transthoracic intra-cardiac catheters, those catheters inserted directly into the right or left atrium via the heart wall)oPeripheral IV or MidlinesoVentricular Assist Device (VAD)
  
  
• HHS NQS Priority: Communication and Care Coordination
  
  
• HHS Data Source: National Healthcare Safety Network
  
  
• Measure Type: Outcome
  
  
• Steward: Centers for Disease Control and Prevention
  
  
• Endorsement Status:
  
  
• Meaningful Measure Area: Healthcare-associated infections
  
  
• Changes to Endorsed Measure Specifications?: The MUC list indicates the measure has been modified from its endorsed version.
  
  
• Is the measure specified as an electronic clinical quality measure? No
  
  

Preliminary Analysis of Measure

• Preliminary analysis result: Support for Rulemaking
  
  
• Preliminary analysis summary
  • Contribution to program measure set:This NQF endorsed measure is currently included in PCHQR and addresses the Meaningful Measure Area of healthcare-associated infections. The risk-adjustment model for this measure was updated and the measure was submitted and re-endorsed by the NQF Patient Safety Standing Committee in the CDP Spring 2019 Cycle. The measure is otherwise identical to the existing measure in PCHQR.
  • Impact on quality of care for patients:This measure enourages the measurement and prevention of a serious adverse outcome caused by CLASBIs for patients in cancer hospitals.Central line-associated bloodstream infections (CLABSI) are associated with significant morbidity, mortality, and costs. Patients in intensive care units (ICUs) are at an increased risk for CLABSI, because 48 percent of ICU patients have indwelling central venous catheters, accounting for 15 million central line days per year in U.S. ICUs. Assuming an average CLABSI rate of 5.3 per 1,000 catheter days and an attributable mortality of 18 percent (0-35 percent), as many as 28,000 patients die from CLABSI annually in U.S. ICUs (AHRQ, 2018).
  
  
  
• Does the measure address a critical quality objective not currently adequately addressed by the measures in the program set? Yes. This measure addresses the Meaningful Measure Area of healthcare-associated infections. This measure is an updated version of the existing measure, NQF #0139, in PCHQR. The risk-adjustment model for this measure was updated and the measure was submitted and re-endorsed by the NQF Patient Safety Standing Committee in the CDP Spring 2019 Cycle.The measure is otherwise identical to the existing measure in PCHQR.
  
  
• Is the measure evidence-based and either strongly linked to outcomes or an outcome measure? Yes. This is an outcome measures that calculates the Standardized Infection Ratio (SIR) and Adjusted Ranking Metric (ARM) of healthcare-associated, central-line-associated bloodstream infections (CLABSI) among patients in bedded inpatient care locations.Central line-associated bloodstream infections (CLABSI) are associated with significant morbidity, mortality, and costs. Patients in intensive care units (ICUs) are at an increased risk for CLABSI, because 48 percent of ICU patients have indwelling central venous catheters, accounting for 15 million central line days per year in U.S. ICUs. Assuming an average CLABSI rate of 5.3 per 1,000 catheter days and an attributable mortality of 18 percent (0-35 percent), as many as 28,000 patients die from CLABSI annually in U.S. ICUs (AHRQ, 2018).AHRQ has developed a toolkit to reduce CLABSI which resulted in a 41% reduction in CLABSI rates over 1,000 ICUs, suggesting there are interventions to improve on the outcome.
  
  
• Does the measure address a quality challenge? Yes. The developer states that among the 2,337 hospitals in U.S. with enough CLASBI data to calculate a standardized infection ratio (SIR), 9% had an SIR significantly higher (worse) than 0.81, the value of the national SIR.
  
  
• Does the measure contribute to efficient use of measurement resources and/or support alignment of measurement across programs? Yes. This measure is currently in multiple CMS programs. The PCHQR program does not currently include any other measures that assess healthcare-associated, central-line-associated bloodstream infections (CLABSI) among patients in bedded inpatient care locations.
  
  
• Can the measure can be feasibly reported? Yes. This is an EHR and chart abstracted measure that is currently used in multiple CMS programs, with collection, analysis, and reporting of measure data via CDC's National Healthcare Safety Network (NHSN) surveillance system.
  
  
• Is the measure applicable to and appropriately specified for the program's intended care setting(s), level(s) of analysis, and population(s)? Yes. The measure is specified and tested at the facility level of analysis in the community hospitals, hospital/acute care facility, hospital inpatient, inpatient rehabilitation facility, IP units within acute care hospitals, long-term care hospital, PPS-exempt cancer hospital setting.NQF endorsement for this measure was renewed in the CDP Spring 2019 Cycle by the NQF Patient Safety Standing Committee.
  
  
• Measure development status: Fully Developed
  
  
• If the measure is in current use, have negative unintended issues to the patient been identified? No. The developer does not identify unintended negative consequences.
  
  
• MAP Rural Health Workgroup Input:
  • Relative priority/utility: This measure is not relevant to rural providers, given that the 11 cancer hospitals are located in urban areas. However, cancer hospitals have a wide referral base and therefore care for patients from rural areas.
  • Data collection issues: None.
  • Calculation issues: None.
  • Unintended consequences: The Workgroup suggested that comparisons between cancer hospitals and other hospitals would not be fair because of the higher rates of immunocompromise in patients with cancer.
  • Votes: Range is 1 – 5, where higher reflects more agreement regarding suitability for the program
  • Average agreement= 4.0
  • Vote Counts: (1 – 1 vote; 2 – 1 vote; 3 – 0 votes; 4 – 8 votes; 5 – 5 votes)
  • Program gap areas: The Workgroup suggested the addition of PRO-PMs as well as a measure documenting advance care planning.
  
  
  

Rationale for measure provided by HHS
A substantial body of peer-reviewed studies and reviews document that CLABSI can be minimized through proper management of the central line. Efforts to improve central line insertion and maintenance practices, with early discontinuance of lines are recommended. These efforts result in decreased morbidity and mortality and reduced healthcare costs.Use of this measure to track CLABSIs through a nationalized standard for HAI monitoring, leads to improved patient outcomes and provides a mechanism for identifying improvements and evaluating prevention efforts.

Summary of NQF Endorsement Review

• Year of Most Recent Endorsement Review: 2019
  
  
• Project for Most Recent Endorsement Review: Patient Safety
  
  
• Review for Importance: 1a. Evidence: Pass-20; No Pass-0; 1b. Performance Gap: H-5; M-15; L-0; I-0Rationale:•The Committee agreed that there are preventive activities that can reduce the incidence of CLABSI; these include:oAppropriate central line use: promptly removing non-essential intravascular catheters,oHand hygiene and aseptic techniqueoThe use of maximal barrier equipment including a large patient drape, inserter mask, sterile gloves, cap, and sterile gown during aseptic insertion of the central lineoAppropriate insertion site decontamination before central line insertionoChlorhexidine-impregnated dressings (in patients = 18 years), and (vi) implementing surveillance strategies•To support these practices, the developer cites a guideline:oO'Grady NP, Alexander M, Burns LA, Dellinger PE, Garland J, et al. Guidelines for the prevention of intravascular catheter-related infections. Available at http://www.cdc.gov/hicpac/pdf/guidelines/bsi-guidelines-2011.pdf.•The developer provided national Standardized Infection Ratios (SIRs) for CAUTI in 2015, 2016, and 2017:oNational CLABSI SIR in 2015 is 0.994 = 26,029 observed / 26,183.537 predictedoNational CLABSI SIR in 2016 is 0.891 = 23,591 observed / 26,472.710 predictedoNational CLABSI SIR in 2017 is 0.814 = 21,173 observed / 25,993.180 predicted•The developer also reports that there was a 10% decrease in CLABSI between 2015 and 2016, and a 9% decrease between 2016 and 2017.•The Committee discussed performance gaps on this measure with respect to variation across ethnic groups, rural vs. urban areas, hospital size, and other factors.
  
  
• Review for Scientific Acceptability: 2a. Reliability precise specifications, testing; 2b. Validity testing, threats to validity•This measure is deemed as complex and was evaluated by the NQF Scientific2a. NQF Scientific Methods Panel Ratings for Reliability: H-0; M-4; L-0; I-02b. NQF Scientific Methods Panel Ratings for Validity: H-0; M-3 L-1; I-0(The Committee accepted the NQF Scientific Methods Panel’s Moderate rating, unanimously.)Rationale:•Data element validity testing was conducted, which NQF allows to serve as a demonstration of data element reliability.•The developer notes that the critical data elements of this measure have been validated by a number of state health departments that require mandatory reporting of CLABSI through the NHSN.•Data validation is conducted by trained auditors, who review medical records and determine whether facilities’ identification of patients meeting or not meeting CLABSI criteria was accurate.•Sensitivity, specificity, positive predicted value, and negative predicted value were calculated.•Validation results from 5 states are provided—the developer reports that these validations indicated a pooled mean sensitivity of 87.5% (range: 80.3%-100%), specificity of 99.3% (range: 98.7% - 100%), positive predictive value of 96.9% (range: 94.2% - 100%) and negative predictive value of 96.9% (range: 93.7% - 100%).•Committee members discussed the relationship between ‘catheter days’ and infections, noting that CLABSI risk likely increases the longer a line is left in.oThe developer noted that CDC is exploring ways of incorporating this and other factors into measurement calculations.•This measure was reviewed against the Scientific Acceptability criteria by NQF’s Scientific Methods Panel (SMP); the SMP judged it to have met NQF’s standards for reliability and validity.•The Patient Safety Standing Committee accepted the SMP’s ratings.
  
  
• Review for Feasibility: Feasibility: H-1; M-19; L-0; I-0 Rationale:•Data for the measure are collected through the National Healthcare Safety Network (NHSN) using a set of standardized forms.•The developer reports that CLABSI and central line days (the numerator and denominator) must be collected by trained hospital staff from information available in clinical data sources.•The developer noted that some of the data used in the measure can be mined from electronic sources, adding that NHSN is moving towards an electronically captured CAUTI measure for future use. However, development and testing are not complete at this time.
  
  
• Review for Usability: 4a. Use: Pass-20; No Pass-0 4b. Usability: H-7; M-13; L-0; I-0Rationale:•The measure is used in several accountability programs, including:oHospital Inpatient Quality Reporting Program (HIQR)oHospital Value-Based PurchasingoHospital-Acquired Condition Reduction Program (HACRP)•The Committee agreed that this measure meets the Use & Usability criteria, noting that it is used in federal payment and public reporting programs.•Committee members did raise caution about potential ‘gaming’ of the measure, suggesting that the developer should be watchful for these issues and find ways of addressing them.
  
  
• Review for Related and Competing Measures: No related or competing measures noted.
  
  
• Endorsement Committee Recommendation: Standing Committee Recommendation for Endorsement: Y-20; N-0
  
  

Program Index

• Ambulatory Surgical Center Quality Reporting Program 
  
  
• End-Stage Renal Disease Quality Incentive Program 
  
  
• Hospital Acquired Condition Reduction Program 
  
  
• Hospital Inpatient Quality Reporting (IQR) Program and Medicare and Medicaid Promoting Interoperability Program for Eligible Hospitals and Critical Access Hospitals (CAHs) 
  
  
• Hospital Outpatient Quality Reporting Program 
  
  
• Hospital Readmissions Reduction Program 
  
  
• Hospital Value-Based Purchasing Program 
  
  
• Inpatient Psychiatric Facility Quality Reporting Program 
  
  
• Prospective Payment System-Exempt Cancer Hospital Quality Reporting Program 
  
  

Full Program Summaries

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

High Priority Domains for Future Measure Consideration:

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

1. Making Care Safer
2. Person and Family Engagement
3. Best Practice of Healthy Living
4. Effective Prevention and Treatment a. Surgical outcome measures
5. Making Care Affordable
6. Communication/Care Coordination

Measure Requirements:

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

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

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

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

High Priority Domains for Future Measure Consideration:

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

1. Care Coordination: ESRD patients constitute a vulnerable population that depends on a large quantity and variety medication and frequent utilization of multiple providers, suggesting medication reconciliation is a critical issue. Dialysis facilities also play a substantial role in preparing dialysis patients for kidney transplants, and coordination of dialysis-related services among transient patients has consequences for a non-trivial proportion of the ESRD dialysis population.
2. Safety: ESRD patients are frequently immune-compromised, and experience high rates of blood stream infections, vascular access-related infections, and mortality. Additionally, some medications provided to treat ESRD patients may cause harmful side effects such as heart disease and a dynamic bone disease. Recently, oral-only medications were excluded from the bundle payment, increasing need for quality measures that protect against overutilization of oral-only medications.
3. Patient- and Caregiver-Centered Experience of Care: Sustaining and recovering patient quality of life was among the original goals of the Medicare ESRD QIP. This includes such issues as physical function, independence, and cognition. Quality of Life measures should also consider the life goals of the particular patient where feasible, to the point of including Patient-Reported Outcomes.

Measure Requirements:

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

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

Program History and Structure: Section 3008 of the Patient Protection and Affordable Care Act of 2010 (ACA) established the Hospital- Acquired Condition Reduction Program (HACRP). Created under Section 1886(p) of the Social Security Act (the Act), the HACRP provides an incentive for hospitals to reduce the number of HACs. Effective Fiscal Year (FY) 2014 and beyond, the HACRP requires the Secretary to make payment adjustments to applicable hospitals that rank in the top quartile of all subsection (d) hospitals relative to a national average of HACs acquired during an applicable hospital stay. HACs include a condition identified in subsection 1886(d)(4)(D)(iv) of the Act and any other condition determined appropriate by the Secretary. Section 1886(p)(6)(C) of the Act requires the HAC information be posted on the Hospital Compare website. CMS finalized in the FY 2019 IPPS/LTCH PPS final rule a scoring methodology change that removed domains and assigns equal weighting to each measure for which a hospital has a measure beginning with the FY 2020 HACRP. The program currently uses the CMS Patient Safety Indicator 90 (CMS PSI 90) and five Healthcare-Associated Infections (HAI) as collected by the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN). The measures in HACRP are categorized under the Meaningful Measure area of “Make Care Safer by Reducing Harm Caused in the Delivery of Care.” The Total HAC Score is the sum of the equally weighted average of the hospital’s measure scores.

High Priority Domains for Future Measure Consideration:

For FY 2018 federal rulemaking, CMS may propose the adoption, removal, and/or suspensionof measures for fiscal years 2019 and beyond of the HACRP. CMS identified the following topics as areas within the NQS priority of “Making Care Safer” for future measure consideration:

Making Care Safer:

1. Measures that meet the Measure Requirements below that are electronic Clinical Quality Measures (eCQMs)
2. Measures that address adverse drug events during the inpatient stay
3. Measures that address ventilator-associated events
4. Additional surgical site infection locations that are not already covered within an existing measure in the program
5. Outcome risk-adjusted measures that capture outcomes from hospital-acquired conditions and are risk-adjusted to account for patient and/or facility differences (e.g., multiple comorbidities, patient care location)
6. Measures that address diagnostic errors such as harm from receiving improper tests or treatment, harm from not receiving proper tests or treatment, harm from failure to diagnose, or harm from improper diagnosis
7. Measure that address causes of hospital harm such as an all-cause harm measure or a measure that encompasses multiple harms
8. Measures that demonstrate safety and/or high reliability practices and outcomes

Measure Requirements:

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

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

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

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

High Priority Domains for Future Measure Consideration:

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

1. Strengthen Person and Family Engagement as Partners in their Care:
   1. Functional Outcomes
   2. Care is Personalized and Aligned with Patient's Goals
2. Promote Effective Communication and Coordination of Care:
   1. Seamless Transfer of Health Information
3. Promote Effective Prevention and Treatment of Chronic Disease:
   1. Prevention and Treatment of Opioid and Substance Use Disorders
   2. Make Care Safer by Reducing Harm Caused in the Delivery of Care:
      1. Preventable Healthcare Harm

Measure Requirements:

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

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

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

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

High Priority Domains for Future Measure Consideration:

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

1. Making Care Safer
2. Person and Family Engagement
3. Best Practice of Healthy Living
4. Effective Prevention and Treatment a. Surgical outcome measures
5. Making Care Affordable
6. Communication/Care Coordination

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

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

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

Program History and Structure: Section 3025 of the Patient Protection and Affordable Care Act of 2010 (ACA) established the Hospital Readmissions Reduction Program (HRRP). Codified under Section 1886(q) of the Social Security Act (the Act), the HRRP provides an incentive for hospitals to reduce the number of excess readmissions that occur in their settings. Effective Fiscal Year (FY) 2012 and beyond, the HRRP requires the Secretaryto establish readmission measures for applicable conditions and to calculate an excess readmissionratio for each applicable condition, which will be used to determine a payment adjustment to those hospitals with excess readmissions. A readmission is defined as an admission to an acute care hospital within 30 days of a discharge from the same or another acute care hospital. A hospital’s excess readmission ratio measures a hospital’s readmission performance compared to the national average for the hospital’s set of patients with that applicable condition. Applicable conditions in the HRRP program currently include measures for acute myocardial infarction, heart failure, pneumonia, chronic obstructive pulmonary disease, elective total knee and total hip arthroplasty, and coronary artery bypass graft surgery. Planned readmissions are excluded from the excess readmission calculation. In the (FY) 2018 IPPS final rule, CMS changed the methodology to calculate the payment adjustment factor in accordance with the 21st Century Cures Act to assess penalties based on a hospital’s performance relative to other hospitals treating a similar proportion of Medicare patients who are also eligible for full Medicaid benefits (i.e. dual eligible) beginning with the (FY) 2019 program.

High Priority Domains for Future Measure Consideration:

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

• Promote Effective Communication and Coordination of Care:
  • Admissions and Readmissions to Hospitals

Measure Requirements:

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

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

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

Program History and Structure: The Hospital Value-Based Purchasing (HVBP) Program was established by Section 3001(a) of the Affordable Care Act, under which value-based incentive payments are made each fiscal year to hospitals meeting performance standards established for a performance period for such fiscal year. The Secretary shall select measures, other than measures of readmissions, for purposes of the Program. In addition, a measure of Medicare Spending Per Beneficiary must be included. Measures are eligible for adoption in the HVBP Program based on the statutory requirements, including specification under the Hospital Inpatient Quality Reporting (IQR) Program and posting dates on the Hospital Compare website.

High Priority Domains for Future Measure Consideration:

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

1. Strengthen Person and Family Engagement as Partners in their Care:
   1. Functional Outcomes
2. Promote Effective Prevention and Treatment of Chronic Disease:
1. Prevention and Treatment of Opioid and Substance Use Disorders
2. Risk Adjusted Mortality

Measure Requirements:

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

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

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

Program History and Structure: The Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program was established by Section 1886(s)(4) of the Social Security Act, as added by sections 3401(f)(4) and 10322(a) of the Patient Protection and Affordable Care Act (the Affordable Care Act). Under current regulations, the program requires participating inpatient psychiatric facilities (IPFs) to report on 13 quality measures or face a 2.0 percentage point reduction to their annual update. Reporting on these measures apply to payment determinations for Fiscal Year (FY) 2020 and beyond.

High Priority Domains for Future Measure Consideration:

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

1. Strengthen Person and Family Engagement as Partners in their Care
   1. Patient Experience and Functional Outcomes
   2. Depression Measure
   3. Patient's Experience of Care
2. Make Care Safer by Reducing Harm Caused in the Delivery of Care
   1. Preventable Healthcare Harm

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

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

Program History and Structure: Section 3005 of the Affordable Care Act added new subsections (a)(1)(W) and (k) to section 1866 of the Social Security Act (the Act). Section 1866(k) of the Act establishes a quality reporting program for hospitals described in section 1886(d)(1)(B)(v) of the Act (referred to as a “PPS-Exempt Cancer Hospital” or PCHQR). Section 1866(k)(1) of the Act states that, for FY 2014 and each subsequent fiscal year, a PCH shall submit data to the Secretary in accordance with section 1866(k)(2) of the Act with respect to such a fiscal year. In FY 2014 and each subsequent fiscal year, each hospital described in section 1886(d)(1)(B)(v) of the Act shall submit data to the Secretary on quality measures (QMs) specified under section 1866(k)(3) of the Act in a form and manner, and at a time, specified by the Secretary. The program requires PCHs to submit data for selected QMs to CMS. PCHQR is a voluntary quality reporting program, in which data will be publicly reported on a CMS website. In the FY 2012 IPPS rule, five NQF endorsed measures were adopted and finalized for the FY 2014 reporting period, which was the first year of the PCHQR. In the FY 2013 IPPS rule, one additional measure was adopted. Twelve new measures were adopted in the FY 2014 IPPS rule and one measure was adopted in theFY 2015 IPPS rule. Three new measures were adopted and six were removed in the FY 2016 IPPS rule. One measure was adopted in the FY 2017 IPPS rule. In the FY 2018 IPPS rule, four measures were adopted and three measures were removed. One measure was adopted and four measures were removed in the FY 2019 IPPS rule.

High Priority Domains for Future Measure Consideration:

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

1. Communication and Care Coordination
   • Measures regarding care coordination with other facilities and outpatient settings, such as hospice care.
   • Measures of the patient’s functional status, quality of life, and end of life.
2. Making Care Affordable
   • Measures related to efficiency, appropriateness, and utilization (over/under-utilization) of cancer treatment modalities such as chemotherapy, radiation therapy, and imaging treatments.
3. Person and Family Engagement
   • Measures related to patient-centered care planning, shared decision-making, and quality of life outcomes.
4. Promote Effective Prevention and Treatment of Chronic Disease
   • Measures related to appropriate opioid prescribing and pain management best practices for cancer patients

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

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

Index of Measures (by Program)

General Comments

• General comments
  
  

• Standardized Transfusion Ratio for Dialysis Facilities (Public comments received:1; MUC ID: MUC2019-64)
  
  

• Maternal Morbidity (Public comments received:4; MUC ID: MUC2019-114)
  
  
• Hospital Harm - Severe Hyperglycemia (Public comments received:5; MUC ID: MUC2019-26)
  
  

• Follow-Up After Psychiatric Hospitalization (Public comments received:2; MUC ID: MUC2019-22)
  
  

• National Healthcare Safety Network (NHSN) Catheter-Associated Urinary Tract Infection Outcome Measure (No public comments received; MUC ID: MUC2019-18)
  
  
• National Healthcare Safety Network (NHSN) Central Line Associated Bloodstream Infection Outcome Measure (No public comments received; MUC ID: MUC2019-19)
  
  

Full Comments (Listed by Measure)

• In general we support these measures. The measure listing is comprehensive encompassing all of the major areas of concern such as: MUC2019-018 and 019 hospital acquired infections (UTIs and central blood lines), Measure 021 on transitions of care, 022 mental health follow-up, 027 preventable readmissions, and 114 maternal morbidity and mortality are all important key areas. (Submitted by: Family Voices NJ)
  
  

• The American Medical Association (AMA) remains committed to addressing the existing disparities and decreasing maternal morbidity and mortality. There needs to be additional evidence to demonstrate what is a high performing collaborative in this area. Any measure on this topic should be in alignment with the Centers for Disease Control and Prevention metrics and the Alliance for Innovation on Maternal Health (AIM) bundles, since they are well vetted and have buy-in from multiple stakeholders (including the new Joint Commission standards announced in August 2019). Several states are currently committed to monitoring maternal morbidity in all hospitals and using the AIM bundles. We believe that there is significant risk that this structural measure will only add to reporting burden for hospitals with no known benefit unless it is aligned with current national activities and additional information is needed to understand what is intended. (Submitted by: American Medical Association)
  
  
• The Joint Commission supports this structural measure as a first phase to help increase awareness for the importance of improving maternal care. As an interim step a structural measure such as this would signal to the field the importance of focusing improvement efforts on maternal care. A structural measure that requires only attestation of participation or non-participation in a quality improvement collaborative to help prevent and manage SMM would be low burden. This measure could help drive hospitals who haven’t already done so to think about joining a collaborative and quality improvement efforts that are needed to improve maternal care. The Joint Commission is actively working with fellow stakeholders on the development of a maternal morbidity electronic clinical quality measure (eCQM). (Submitted by: The Joint Commission)
  
  
• The Federation of American Hospitals (FAH) strongly supports efforts to address pregnancy-related morbidity and mortality, particularly in light of the recent analyses by the Centers for Disease Control and Prevention highlighting that many are preventable and there are significant disparities in care (Peterson, 2019). Because of the importance of this issue, the FAH regrets that we cannot support consideration of this measure at this time due to the limited information provided and lack of clear linkages that participation in any time of quality improvement collaborative can improve outcomes in this area. The FAH encourages the Centers for Medicare and Medicaid Services to explore other measures that are more directly linked to quality improvement and accountability while also minimizing reporting burden for hospitals. As a result, the FAH requests that the highest level of MAP recommendation be “Do Not Support”. Reference: Petersen EE, Davis NL, Goodman D, et al. Vital Signs: Pregnancy-Related Deaths, United States, 2011–2015, and Strategies for Prevention, 13 States, 2013–2017. MMWR Morb Mortal Wkly Rep 2019;68:423–429. DOI: http://dx.doi.org/10.15585/mmwr.mm6818e1 (Submitted by: Federation of American Hospitals)
  
  
• The measure aligns with national efforts to identify the causes of maternal mortality and morbidity, reduce disparities in maternal health outcomes and advance best practices for improving care for new mothers and their infants. However, without additional specifications it is not clear if this measure is in alignment with the CDC Severe Maternal Morbidity Measure (SMM) or if this is a newly developed metric. Premier has spent over a decade working with our members across the country and aggregating data from 8.9 million births to understand where these challenges exist. Premier’s nationally representative analysis showed that severe maternal morbidity (SMM) increased by 36 percent, and in particular, black women had a 79 percent higher rate of SMM factors than white women. While the analysis found that the increase in SMM is likely being influenced by several factors, including the transition from ICD-9 to ICD-10, maternal age, payer and hospital type, increased incidence of substance use and other factors, there are clear opportunities for improvement. These insights underscore the needed focus on maternal morbidity to understand these complications through enhanced reviews, standardized data and coordinated care delivery to decrease the nation’s SMM and mortality rates. We look forward to the opportunity to work with CMS as it continues to develop this measure. (Submitted by: Premier)
  
  

• The Joint Commission supports this measure as it addresses a gap in care management of mental health and substance use disorders. This measure would enhance an existing IPFQR measure: Follow-up after Hospitalization for Mental Illness (FUH). This measure adds substance use disorder patients which addresses an NQF recommendation to include these patients whenever possible. Additionally, the measure expands follow-up care to include the day of discharge which is considered important for high risk patients. It is felt that facilities may have greater influence on same-day follow-up visits as opposed to later follow-up visits. Studies have shown that readmission rates are lower for those with psychiatric diagnoses in patients who receive follow-up visits within 30 days of discharge. There is no burden of data collection as this is a claims-based measure. Additionally, this measure would replace an existing measure. (Submitted by: The Joint Commission)
  
  
• The Federation of American Hospitals (FAH) strongly advocates that any measure that is proposed for use in payment programs should be evidence-based, appropriate for accountability purposes at the designated level of attribution, and demonstrated to be reliable and valid. On our review of the HSAG Draft Methodology Report referenced in the measure information, we do not believe that sufficient evidence to support attribution of the measure to hospitals was demonstrated. Two of the studies referenced could not establish that follow-up efforts led to decreased readmissions or emergency department visits and a third study only included 15 patients and did not explicitly examine whether the follow-up visit were associated with desired outcome such as acute care utilizations. In addition, testing is needed to determine whether risk adjustment due to social risk factors that are outside of a hospital’s control should be potentially considered. While the FAH supports efforts to ensure that individuals with mental illness and substance use disorders are connected to a clinician for follow-up at the time of discharge, we do not believe that it is appropriate for accountability and should not be recommended for use in this program. As a result, the FAH requests that the highest level of MAP recommendation be “Do Not Support with Potential for Mitigation”. (Submitted by: Federation of American Hospitals)
  
  

• The American Medical Association (AMA) believes that there is sufficient evidence to support this measure but we are unable to provide our complete support for this measure until information is provided on whether the measures yield scores that are reliable, valid and useable for a payment program. In addition, testing must be conducted across multiple electronic health record systems across hospitals of various sizes and geographic regions to understand whether the required data elements can be captured in a feasible and valid manner and if either of the measures yields performance scores that are generally low and/or with minimal variation across hospitals, making the measure less useful for accountability uses. The AMA recommends that the highest level of MAP recommendation be “Do Not Support with Potential for Mitigation”. (Submitted by: American Medical Association)
  
  
• I am opposed to the adoption of this measure as it is currently written. Rationale: 1. Results can contain Duplicate results corresponding to the same hyperglycemic episode: When blood glucose is “High” as measured on a Point of Care device, hospital protocol usually requires that a serum glucose level be sent for confirmation to the lab. This results in a minimum of two reported values corresponding to the same episode of hyperglycemia. 2. It is unsafe to precipitously lower glucose levels in patients admitted with significant hyperglycemia. Ex: DKA. The measure currently carries no exclusions for patients with this as a principle or secondary diagnosis present on admission. Other admission or secondary POA diagnoses with high blood glucose that should be considered for exclusion include: Hyperglycemic hyperosmolar nonketotic syndrome pancreatitis Post pacreatectomy septicemia esp in diabetic patients pheochromocytoma patients receiving ritonavir, HCTZ phenytoin toxicity wolframs disease Isonizide toxicity amlodipine toxicity myotonic dystrophy lipodystrophy nifedipine toxicity cushing syndrome cystic fibrosis adrenal cortex diseases megaloblastic anemia patients receiving glucocorticosteroids patients with cirrhosis pituitary tumor Arizona Bark Scorpion poisoning 3. There is no exclusion for patient non-compliance with therapy either medication related or dietary related. Please include exclusions for documented non-compliance. 4. There are no exclusions for patients treated with IV steroids (esp Diabetics with sepsis receiving steroids). Please include exclusions for this. 5. Please include exclusions for postpancreatectomy patients (at least for the initial episode of care for the pancreatectomy). 6. Please include exclusions for patients on comfort measures. 7. There needs to be a Length of stay exclusion that relates to the measure for a day without any measurement of blood glucose level and not preceeded by two consecutive days where blood glucose levels were measured…etc. Additionally, patient non-compliance or refusal for measurement of blood glucose needs to be an exclusion. 8. The measure does not specify that the patient should have a diagnosis of Diabetes. It also does not exclude errant results (ex: if lab was errant due to comingling with IV fluids). Caring for hyperglycemic patients is extremely complex and outcomes cannot be reduced to simply measuring frequency of elevated blood glucose results. There are nuances behind that measure and patient diagnoses and non-compliance that impact the efficacy of the health care team to reduce blood glucoses. This is especially true if that visit is for DKA, HHNK, Diabets+sepsis or a pancreatectomy. Thank-you for the opportunity to comment Sincerely, Theresa Mulherin MSN RNCNS CEN (Submitted by: Sentara CarePlex Hospital)
  
  
• The Federation of American Hospitals (FAH) recognizes the need to address this important patient safety event but encourages the MAP to conditionally recommend this measure until it receives NQF endorsement. Specifically, the FAH is concerned that the differences in performance scores may be minimal and may not yield reliable and valid representations of performance across the hospitals. In addition, the FAH also strongly encourages CMS to assess the feasibility of collecting the required data elements from electronic health record systems (EHRs) and determine if the measure is reliable and valid. The FAH is concerned that the complexity of the measure and, particularly the complexity of the numerator, may significantly impact an individual hospital’s ability to successfully collect and report on the measure. The FAH recommends that this measure be reported together with the Hospital Harm – Severe Hypoglycemia measure, which was recently endorsed by NQF. This pairing will minimize the risk of increasing either event, which might occur if the focus is solely on one or the other outcome. The FAH notes that while the cut-off of >200 mg/dL is not identical to the American Diabetes Association guideline recommendation of >180 mg/dL, it allows room for clinical judgment and the ability to address the event prior to it impacting a hospital’s performance. We support the continued use of this cut-off. With respect to the numerator, the FAH is concerned that a blood glucose value of greater than 300 mg/DL may be high to determine a severe hyperglycemic event which may be more accurately identified at values greater than 240 mg/dL (at the risk of increasing the number of fall outs for the measure). In addition, the FAH would like to point out that the measure is missing the group of patients who have undiagnosed DM, no A1C test in the hospitals and who remains hyperglycemic throughout their hospital stay without being treated with insulin. (Submitted by: Federation of American Hospitals)
  
  
• The measure should be submitted for NQF endorsement. Endorsement review should consider whether the specified measure can be readily measured through existing data and if any exclusions might be necessary. (Submitted by: Premier)
  
  
• We are concerned about the difficulty in measuring severe hyperglycemia and the complexity of the measure. In addition, we have some concerns the measure may result in a significant increase in the incidence rate of hypoglycemia, which is a condition that has a well-established higher mortality rate. Significant hypoglycemia can cause significant acute harm including brain injury, seizures and death in hospitalized patients. Hyperglycemia does not have as established a risk-benefits analysis in non-critically ill, non-surgical hospitalized patients. We also wonder how this may interact with measures of severe hypoglycemia (<40). Supporting evidence: • Nasraway SA Jr. Sitting on the horns of a dilemma: avoiding severe hypoglycemia while practicing tight glycemic control. Crit Care Med 2007; 35:2435. (Submitted by: Society of Hospital Medicine)
  
  

• Kidney Care Partners (KCP) is a coalition of members of the kidney care community that includes the full spectrum of stakeholders related to dialysis care—patient advocates, health care professionals, dialysis providers, researchers, and manufacturers and suppliers—organized to advance policies that improve the quality of care for individuals with both chronic kidney disease and end stage renal disease (ESRD). We appreciate the opportunity to provide comments to the Measures Application Partnership on MUC19-64, Standardized Transfusion Ratio for Dialysis Facilities (STrR, NQF 2979). We note that the MAP materials currently identify the STrR as endorsed. We note however, that the specifications of the endorsed measure now differ from a newly proposed version. As it deliberates, we ask the Hospital Workgroup to be mindful that, due to an ad hoc review request by KCP, the measure developer (CMS/KECC) has had to re-specify the measure. Specifically, merely as a result of the ICD-9 to ICD-10 transition, KCP demonstrated that 12% of hospitals seemingly had an estimated reduction in transfusion (coding) by >80% and nearly 22% had an estimated reduction >50%. CMS acknowledged the threat to the STrR’s validity that the conversion had presented and agreed to review the information and propose new specifications. This revised measure is currently beginning its review by the Renal Standing Committee. We strongly recommend any recommendation from MAP on the STrR not be unqualified, but that it be conditioned on NQF endorsement of the new specifications. (Submitted by: Kidney Care Partners)
  
  

Navigating the Discussion Guide

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

Content

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

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