Why self-reported data are important and barriers to getting them
Race and ethnicity (R&E) data are important metrics to understand discrepancies in health outcomes within certain populations. While examining these discrepancies can help providers, payers and life sciences organizations develop solutions that address disparities, R&E data are generally considered inadequate across the industry.
This is largely due to gaps or imputed methodologies that attempt to identify race and ethnicity from proxy sources. These issues have plagued the industry to the point that even understanding racial inequities in health is challenging. As a result, stakeholders across the healthcare industry are seeking more accurate sources of ethnicity and race data, either through their own novel collection efforts, or by combining many sources.
To that end, Optum Life Sciences recently added self-reported race and ethnicity data to our real-world claims data set, Clinformatics® Data Mart (CDM). The incorporation of these data in CDM presents an opportunity for life sciences researchers to do work that’ll help lead to better care and better solutions for all types of populations.