THE EXPECTED POPULATION VALUE OF QUALITY INDICATOR REPORTING (EPV-QIR): A FRAMEWORK FOR PRIORITIZING HEALTHCARE PERFORMANCE MEASUREMENT

Tuesday, October 26, 2010
Sheraton Hall E/F (Sheraton Centre Toronto Hotel)
David Owen Meltzer, MD, PhD, University of Chicago, Chicago, IL and Jeanette W. Chung, PhD, The University of Chicago, Chicago, IL

Purpose: There are over 1,400 measures in the U.S. Department of Health and Human Services National Quality Measures Clearinghouse and over 250 measures in the Agency for Healthcare Research and Quality National Healthcare Quality and Disparities Reports (NHQR and NHDR).  With limited resources, it is important to understand which measures have the greatest potential to improve healthcare quality and safety. We propose a conceptual and methodological approach to help prioritize quality and safety indicators by identifying those with the greatest potential to improve population health.  

Method: Drawing upon previous work on the value of research and value of implementation, we develop a method for estimating the expected population value of quality indicator reporting (EPV-QIR).  We intend EPV-QIR to be easily implemented with minimal computational modeling and data requirements.  The EPV-QIR depends on several factors: 1) the net health benefit (NHB) of the appropriate implementation of the intervention, measured by the potential gain in quality-adjusted life years (QALYs)) net of the opportunity costs in health when the intervention is fully implemented to maximize its benefit net of costs; 2) the size of the population of persons who should receive the intervention, i.e. those with a positive NHB from the intervention; 3) the current state of implementation, which includes both utilization among parts of the population with positive NHB and utilization among those parts of the population with negative NHB (in which NHB increase by eliminating inappropriate use); and 4) the potential for quality improvement, which depends on responsiveness of providers and patient demand to information about quality. 

Result: We demonstrate the calculation of EPV-QIR for 14 NHQR measures, and find that the EPV-QIR of these 14 measures differs by over 300-fold, with the top half of NHQR measures constituting 93% of the total NHB. The top measure, control of blood pressure among patients with diabetes, constitutes nearly 40% of total NHB.

Conclusion: We conclude that EPV-QIR is a practical framework for estimating the population value of quality improvements reporting, and suggests the possibility that the vast majority of population-level NHB from quality improvement could be achieved through a much smaller number of quality indicators than is currently reported by NHRQ.  If focusing on a smaller number of measures increases their impact, focusing policy priorities using EPV-QIR might improve population health.