Learn from Our Race and Ethnicity Stratification Learning Network
May 2, 2023 · Andy Reynolds
To cap National Minority Health Month in April, at the end of the month we launched our Race and Ethnicity Stratification Learning Network.
The network is a free, interactive, online tool that offers data and best practices to help health plans improve how they collect race and ethnicity data on enrollees.
Improving data collection of race and ethnicity data is vital to improving health equity.
The data available in this new resource summarize the care of 20 million people enrolled in 14 health plans that reported results on 5 HEDIS measures, stratified by race and ethnicity.
Best practices we identify come from NCQA’s qualitative interviews of key staff at plans in the learning network.
A report groups our findings in three areas:
Status of race and ethnicity data collection and data management.
Learning Network participants highlighted best practices for improving collection, management and use of race/ethnicity data. Although some plans struggle to report direct (member reported) data, many have been able to accomplish this. Key takeaways focus on tips for assessing strengths and weaknesses of data sources, prioritizing between sources and investing resources in receiving direct data. These findings highlight that plans are discovering ways to report quality metrics, despite challenges to collecting data
How plans link race/ethnicity information to quality performance.
Plans described their experiences linking race/ethnicity data to quality performance measurement. Highlights include changes to how data are used and opportunities for plan departments to work together to support data connection and reportability, particularly for direct data. Learning Network information stressed that by linking race/ethnicity data to quality performance, plans can visualize where inequities exist in a measure and organize resources to close gaps in treatment and outcomes.
How health plans are leveraging stratified data for quality improvement.
Organizations shared success stories about linking race, ethnicity and quality data to target outreach, services and partnerships. They highlighted the importance of evaluating race and ethnicity as other social drivers of health. Using these data to improve quality will be important to closing disparities. In line with other reports, both fixed and relative differences between racial and ethnic groups were observed across all quality measures in Learning Network data. This highlights the importance of understanding data and acting to achieve equitable health care and outcomes for all.
Readers can use the report to increase their knowledge of best practices for collecting, managing and using race/ethnicity data, and to improve their understanding of the practical considerations for using the data in quality improvement and reporting. Findings can be of value to a wide audience, including health plans, data and quality vendors, quality improvement organizations and policymakers.
Check out the Race and Ethnicity Stratification Learning Network.
