Knowledge Architecture for Race and Ethnic Group Defining in Learning Health Systems

Previous work affirms access and health care challenges persist for multiple racial groups. Race and ethnicity are socially and politically constructed terms conceived to describe and categorize people hierarchically (race) and describe people from a similar national or regional background also sharing common national, cultural, historical, and social experiences (ethnicity). Definitions of race and ethnicity may vary across historical, political, and geographic contexts. This variation challenges health care organizations to reliably measure health care outcomes longitudinally within and between racial and ethnic groups. Further, suboptimal concordance between race and ethnicity self-report vs. electronic health record suggests opportunities exist to improve race and ethnicity data solicitation and capture. Learning Health Systems (LHSs) may be particularly poised to address these challenges, as LHSs commit to equitable, transparent, and accountable engagement of individuals and families in care innovation. This discussion provides a rationale, model, and practical strategy to engage individuals and families in race data defining-an essential antecedent to health equity assessment and intervention development. The discussion encourages testing to ensure the proposed theory and steps beget comprehensive and precise race definitions. Enhanced precision in defining race may subsequently inform equity evaluation and interventions in LHSs.