Recommendations to improve race identification in health records: A rapid scoping review

Race is a critical variable in understanding health disparities, yet health databases lack consistent practices for identifying race. This rapid scoping review aimed to examine existing recommendations for identifying race in health databases and highlight gaps in current literature to guide future research. Following the Joanna Briggs Institute methodology and PRISMA-ScR guidelines, searches were conducted in MEDLINE, Embase, and Scopus for relevant literature published between January 2019 and February 2025. Articles were included if they addressed race identification in health databases, were available in English, had full-text access, and were peer-reviewed, knowledge syntheses, or grey literature. All articles were double screened in Covidence, and twenty-one articles were included. Descriptive thematic analysis identified five recommendation categories, including, self-identification and patient-centered practice, standardization across healthcare systems, data quality and completeness, algorithmic and predictive methods, and disaggregated data use and cross sector collaboration. There were common findings on the value of self-identification, cross-system consistency, and tools like natural language processing and imputation models. Some articles emphasized combining multiple strategies to improve system-wide practices, and overall, minimal conflicting evidence was observed. However, gaps remain in operationalizing these recommendations across various healthcare settings. Future directions should prioritize implementation-focused research and cross-jurisdictional comparisons to inform scalable, equity-driven improvements in race data practices. Ultimately, improving the consistency and accuracy of race data will enhance health equity monitoring, guide equitable resource distribution, and inform policies that better reflect the needs of racialized populations.