Opportunities and Challenges of Claims-Based Quality Assessment: The Case of Postdischarge β-Blocker Treatment in Patients With Heart Failure With Reduced Ejection Fraction

Supplemental Digital Content is available in the text. Background: To combat the high cost and increasing burden of quality reporting, the Medicare Payment Advisory (MedPAC) has recommended using claims data wherever possible to measure clinical quality. In this article, we use a cohort of Medicare beneficiaries with heart failure with reduced ejection fraction and existing quality metrics to explore the impact of changes in quality metric methodology on measured quality performance, the association with patient outcomes, and hospital rankings. Methods and Results: We used 100% Medicare Parts A and B and a random 40% sample of Part D from 2008 to 2015 to create (1) a cohort of 295 494 fee-for-service beneficiaries with ≥1 hospitalization for heart failure with reduced ejection fraction and (2) a cohort of 1079 hospitals with ≥11 heart failure with reduced ejection fraction admissions in 2014 and 2015. We used Part D data to calculate β-blocker use after discharge and β-blocker use over time. We then varied the quality metric methodologies to explore the impact on measured performance. We then used multivariable time-to-event analyses to explore the impact of metric methodology on the association between quality performance and patient outcomes and Kendall’s Tau to describe impact of quality metric methodology on hospital rankings. We found that quality metric methodology had a significant impact on measured quality performance. The association between quality performance and readmissions was sensitive to changes in methodology but the association with 1-year mortality was not. Changes in quality metric methodology also had a substantial impact on hospital quality rankings. Conclusions: This article highlights how small changes in quality metric methodology can have a significant impact on measured quality performance, the association between quality performance and utilization-based outcomes, and hospital rankings. These findings highlight the need for standardized quality metric methodologies, better case-mix adjustment and cast further doubt on the use of utilization-based outcomes as quality metrics in chronic diseases.

[1]  S. Solomon,et al.  Health-Related Quality of Life in Heart Failure With Preserved Ejection Fraction: The PARAGON-HF Trial. , 2019, JACC. Heart failure.

[2]  P. Heidenreich Patient-Reported Outcomes: The Future of Heart Failure Care. , 2019, JACC. Heart failure.

[3]  Christina A Nguyen,et al.  Association Between Clinical Practice Group Adherence to Quality Measures and Adverse Outcomes Among Adult Patients With Diabetes , 2019, JAMA network open.

[4]  S. Haneuse,et al.  Association of the Hospital Readmissions Reduction Program With Mortality Among Medicare Beneficiaries Hospitalized for Heart Failure, Acute Myocardial Infarction, and Pneumonia , 2018, JAMA.

[5]  P. Groeneveld,et al.  Trends in Platelet Adenosine Diphosphate P2Y12 Receptor Inhibitor Use and Adherence Among Antiplatelet-Naive Patients After Percutaneous Coronary Intervention, 2008-2016 , 2018, JAMA internal medicine.

[6]  Deepak L. Bhatt,et al.  Association of the Hospital Readmissions Reduction Program Implementation With Readmission and Mortality Outcomes in Heart Failure , 2017, JAMA cardiology.

[7]  MEDICARE ADVANTAGE Benefits and Challenges of Payment Adjustments Based on Beneficiaries ’ Ability to Perform Daily Tasks Report to Congressional Committees , 2018 .

[8]  S. Hewitt,et al.  2017 , 2017, Les 25 ans de l’OMC: Une rétrospective en photos.

[9]  B. Landon,et al.  Medicare ACO Program Savings Not Tied To Preventable Hospitalizations Or Concentrated Among High-Risk Patients. , 2017, Health affairs.

[10]  Christoph Werner,et al.  Trust in the health care professional and health outcome: A meta-analysis , 2017, PloS one.

[11]  T. Brown,et al.  Comparison of Length of Stay, 30-Day Mortality, and 30-Day Readmission Rates in Medicare Patients With Heart Failure and With Reduced Versus Preserved Ejection Fraction. , 2016, The American journal of cardiology.

[12]  L. Casalino,et al.  US Physician Practices Spend More Than $15.4 Billion Annually To Report Quality Measures. , 2016, Health affairs.

[13]  I. Piña,et al.  Forecasting the Impact of Heart Failure in the United States: A Policy Statement From the American Heart Association , 2013, Circulation. Heart failure.

[14]  Biykem Bozkurt,et al.  2013 ACCF/AHA guideline for the management of heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on practice guidelines. , 2013, Circulation.

[15]  E. DeLong,et al.  ACCF/AHA/AMA-PCPI 2011 performance measures for adults with heart failure: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Performance Measures and the American Medical Association-Physician Consortium for Performance Improvement. , 2012, Journal of the American College of Cardiology.

[16]  Jun Liu,et al.  Validity of claims‐based definitions of left ventricular systolic dysfunction in Medicare patients , 2011, Pharmacoepidemiology and drug safety.

[17]  Samy Suissa,et al.  Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes , 2010, BMJ : British Medical Journal.

[18]  R. Patton American Nurses Association , 2007, Disaster Medicine and Public Health Preparedness.

[19]  J. Ross,et al.  The importance of population-based performance measures. , 2007, Health services research.