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Article Abstract

Objectives: Type 2 diabetes (T2D) is a growing public health burden with persistent racial and ethnic disparities. . This study assessed the completeness of social determinants of health (SdoH) data for patients with T2D in Epic Cosmos, a nationwide, cross-institutional electronic health recors (EHR) database.

Materials And Methods: The study included adults with T2D (ICD-10: E11.*) with encounters between 2022 and 2024. We analyzed 11 individual-level SDoH data elements across 5 domains-financial strain, food insecurity, housing instability, intimate partner violence, and transportation needs-and 4 components of the Social Vulnerability Index (SVI), representing neighborhood-level SDoH. Data completeness for each data element (ie, the proportion of individuals with non-missing values) was evaluated using generalized linear models, adjusting for source healthcare organization, sex, and age.

Results: Among 12 031 927 individuals with T2D, adjusted completeness for individual-level SDoH data elements ranged from 11.2% to 31.5%, varying by data element and racial/ethnic group. American Indian or Alaska Native, Asian, Hispanic, and Native Hawaiian or Other Pacific Islander individuals had lower completeness for all individual-level SDoH compared to White individuals. In contrast, SVI data elements were available for nearly all patients since they are derived from patient addresses routinely collected in EHRs.

Discussion: While SVI data elements were widely available, individual-level SDoH data elements had significant missingness, limiting their usability for secondary analyses. Racial/ethnic disparities in SDoH completeness further complicate their use.

Conclusion: Standardized, equitable SDoH collection is critical to close documentation gaps, reduce disparities, and enable accurate, bias-resistant analyses in T2D care.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12410986PMC
http://dx.doi.org/10.1093/jamiaopen/ooaf095DOI Listing

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