Fourteen years ago the Institutes of Medicine published Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Among their recommendations was the observation that to find disparities in care, health systems must first collect Race, Ethnicity, and Language (REAL) data at registration. Many health systems across the country began to make this effort. But then in 2008 the economy collapsed and health systems found themselves launching a rearguard effort to shore up their IT and EMR departments as budgets were cut and IT work forces downsized.Since then, the Affordable Care Act was passed and equity became a pillar of care. Electronic medical records were enhanced and since have evolved to facilitate the sharing of medical information.
At UW Medicine this REAL data effort was reinvigorated in 2015 when our CEO was approached by the American Hospital Association and asked to lead an effort to collect and use REAL data and make this a priority for public hospitals. An effort followed to refine our system for collecting and using race, ethnicity and language data from patients at registration. The effort was remarkable and now we have usable data for 98% of our patients. This allows us to drill down to a granular level and assess health processes and outcomes in the hospital by race, ethnicity, and language spoken. Two examples of how this data can be used are included in a presentation I recorded.
Briefly, by linking REAL data to health outcomes we can not only find disparities in disease burden, but also focus limited resources to address the neediest populations served by the health system. For example, we identified poorer rates of diabetes control in Latino and Somali communities when compared to 10 other language groups. We could then use limited resources to marshal a focused effort in diabetic management for selected diabetics in these communities to lower their HgbA1c and thereby gain better control of their diabetes. In this way, the collection and use of REAL data accomplishes several goals:
- REAL data helps to find disease disparities in ethnic communities.
- REAL data can help identify differences in care delivery and outcomes for these diseases in these communities.
- Identifying disparities helps us to decide which populations are most in need of limited resources to address those identified disparities.
- Once identified, the interventions and materials needed to address these disparities in care can be developed in a linguistically and culturally appropriate manner.
- The impact of these efforts can be tracked to analyze the relative cost and benefit of the efforts made.
REAL data limits unnecessary effort in communities that are not suffering as much as others, and redirects the resources and effort to those suffering the most. This not only saves money, but also reduces morbidity for disproportionately affected communities. The REAL data process then allows us to track the impact of our efforts. For small language communities, such as those recently arriving refugee groups, the collection of language data is very important. It makes a potentially invisible community visible to administrators and health services delivery systems. This allows health system not only to address health disparities, but to track the health status of refugee communities.
I encourage you to think about both mundane and innovative uses for REAL data and make use of this powerful tool for equity and to address unmet pain and suffering.