Health Care Quality & Disparities: Signs of Improvement

by Donna Friedsam

Wisconsin hospitals have again performed very well on measures of health care quality compared to the average of all States nationally. The federal Agency for Healthcare Research and Quality (AHRQ) in August reports that, compared to all States the performance for all Wisconsin measures falls in the strong range, as it did in the baseline year. Wisconsin also rated top among all states on the composite of all measures, an achievement widely recognized in the media.

Less recognized but perhaps of greater significance: While substantial disparities remain in performance related to various populations, care measures for Wisconsin’s Black population show improvement, moving from weak performance at baseline to average performance in the current reporting year.

The disparities in quality of care by Wisconsin’s health care providers have been a long-standing challenge and persist despite Wisconsin’s overall strong quality ranking. Beyond disparities in the quality of health care delivery, Wisconsin shows persistent disparities in health status and outcomes.

Quality improvement in general, and achievement of equity in particular, require intentional and committed effort. The AHRQ report suggests that such efforts are underway.  A promising recent development: the UW’s Dr. Maureen Smith has joined with the Wisconsin Collaborative for HealthCare Quality to measure and publicly report disparities in quality of care.

Attention to disparities have important policy implications.  The move to value-based purchasing ties payment to quality measures. As this occurs, it is important to account for the factors that allow providers to achieve their reported process and outcome measures.

Multiple factors – physical, mental, social, economic and environmental, as well as the quality and effectiveness of healthcare — contribute to health outcomes. The profile of a patient population on all these factors will affect a clinician’s or health system’s performance on a measure, such that it may or may not represent the quality care provided.

For example, a provider may serve a predominantly low-risk, highly resourced patient population, more likely to provide a healthy baseline and adhere to recommendations for screening, medications, and other measures. Such a provider will more easily rate well on standard quality measures.  On the other hand, a provider that serves a high need, low-resource population will more likely start out with a patient population’s lower baseline health status with lower ability or likelihood to adhere to screening and treatment recommendations. These starting factors, separate from the quality of care provided, will likely compromise this provider’s performance measures.

Risk-adjusting quality measures might provide a solution, but it also presents a new challenge: the potential to normalize expectations for lower quality care and outcomes for specific populations.  The National Quality Forum has explored these challenges through a national discussion on risk adjustment.  This culminated in the release of a final report in 2014 with principles and recommendations pertaining to risk-adjustment, stratification, and the relationship between performance measurement and health disparities.

Such principles help put into context the various health rankings regularly reported in the professional and popular media. Next time a headline reads that Wisconsin or a county or a health care provider ranks top or bottom of something, look at the comparative populations.