Disaggregation of Race and Ethnicity Data in Electronic Health Records: Opportunities and Challenges

Oregon Convention Center 

There have been numerous calls in the medical and health policy fields for "data disaggregation" (i.e., breaking out data by more granular key characteristics) when studying minority populations, including Latinos, in order to better understand health and healthcare inequity. The broad racial and ethnic categories whose capture is currently required by the Office of Management and Budget for all federally collected data can mask significant variation within Latino categories, limiting the ability to target resources where they are needed most. For example, country of birth and nativity information may be crucial to understanding health equity in Latino populations, as people's lived experiences and environments differ. However, such information is not collected at a large scale in multiple administrative data sources (e.g., insurance claims, electronic health records). This presentation will discuss opportunities and challenges for data disaggregation of race and ethnicity data using a case study of cardiovascular disease risk among Latinos. This study includes EHR data from 914,495 Latino patients across 22 US states in the OCHIN network, a linked multi-state EHR network of CHCs.