This post originally appeared on The Joint Commission Quality Data Download blog.

By Jennifer Gaudet Hefele, PhD

“If there are differences, they should be known.”Focus group participant, White female

This is what one respondent said when asked whether a nursing home’s report card should show quality performance ratings for each race/ethnicity represented among its residents. In other words, should a nursing home report show a quality measure for how well a facility does for its Black residents and, separately, how well the facility does for its White residents?

Somewhat to our surprise, the majority of our study’s participants expressed similarly supportive sentiments, suggesting mainstream consumers are ready for quality metrics stratified by race/ethnicity.

Understanding and documenting racial and ethnic health disparities has been a long and continuing journey. The National Healthcare Quality and Disparities Report issued by the Agency for Healthcare Research and Quality (AHRQ) each year gives us insight into national trends in performance metrics across racial/ethnic groups.

Some states, including Maryland and Alabama, have examined health disparity metrics at the state level, and even some cities, including Boston and New York City, have taken a more refined look at the city level. These reports allow policymakers and public health professionals to establish benchmarks and identify potential issues that may be addressed through broad campaigns.

Provider-Level Reports by Race/Ethnicity
These macro-level reports, however, provide different insights from what can be learned from provider-level reports. Indeed, the next step in the path toward health care equality is to routinely examine quality performance by race/ethnicity at the provider level. This is something that has been long discussed, including in The Joint Commission Journal on Quality and Patient Safety.

These types of reports are common practice in the public education setting, where parents and policy-makers alike have easy access to performance metrics stratified by race/ethnicity. We are starting to see movement along these lines emerge in health care, including from the Centers for Medicare & Medicaid Services (CMS):

  • In 2015, CMS sought public comment on a proposed rule that would allow for the public reporting of stratified measures on Physician Compare, a website designed to help consumers make informed choices about the health care they receive through Medicare. Although CMS has yet to make a decision regarding stratified measures, it is expected that the publicly reported measures will soon incorporate social factors, and stratification is currently recommended as best practice.
  • In 2016, CMS began to release stratified Healthcare Effectiveness Data and Information Set (HEDIS) and Consumer Assessment of Healthcare Providers and Systems (CAHPS) measures for Part C Medicare Advantage and Part D Prescription Drug plan providers. Reports are publicly available on the CMS website, as are reports on nation- and state-level stratified measures for Medicare fee-for-service beneficiaries.

Why It Matters

  • For provider-level change. When a provider wants to improve the quality of the care it delivers, it seeks a performance improvement plan tailored to its specific needs, based on gaps identified in performance reports. The same should be expected when seeking to ensure or improve the equity of care delivered.
  • For society-level change. Examining provider-level differences in quality of care across race/ethnicity allows us to better understand patterns of disparities. This helps policymakers and practitioners alike better address disparities at a broader level.
  • To meet consumer demand. Aside from reasons related to improving quality and equity, consumer preferences and demand also present as drivers for change. As noted earlier, our study found that most participants felt that presenting performance measures by race/ethnicity was a good idea, regardless of participant race/ethnicity. Between growth in online health information seeking and increased population diversity, we expect interest and demand for such stratified measures to rise.
  • To improve measurement. From a research and measurement perspective, examining stratified measures allows us to uncover potential ascertainment bias and fundamental problems with measures and data collection. This is necessary to ensure accurate future assessments.

We anticipate that stratified measures are on the horizon. There are challenges, of course, with stratification, including sample size issues and stakeholder buy-in. However, we can look to existing and emerging examples to overcome obstacles. Leading edge providers can get ahead of the curve and take initiative to understand their own performance patterns across race/ethnicity and identify areas in need of improvement.

Jennifer Gaudet Hefele is an assistant professor of gerontology at UMass Boston’s McCormack Graduate School.