ArticleJournal of the American Medical Informatics Association : JAMIA2024
Model-based estimation of individual-level social determinants of health and its applications in All of Us.
Article in Journal of the American Medical Informatics Association : JAMIA, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Association of social determinants of health and physical functioning among breast cancer survivors.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Veteran participation in the All of Us Research Program: applying an intersectionality lens to evaluate participant diversity.BMC medical research methodology · 2025Article
- Returning value to communities from the All of Us Research Program through innovative approaches for data use, analysis, dissemination, and research capacity building.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Comparing Patient-level Social Drivers of Health from Health Surveys and Electronic Health Records for Patients with Comorbid Hypertension and Uncontrolled Diabetes.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
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Authors and funding
4 authors.
Funding
Abstract
objectivesWe introduce a widely applicable model-based approach for estimating individual-level Social Determinants of Health (SDoH) and evaluate its effectiveness using the All of Us Research Program. MATERIALS AND
methodsOur approach utilizes aggregated SDoH datasets to estimate individual-level SDoH, demonstrated with examples of no high school diploma (NOHSDP) and no health insurance (UNINSUR) variables. Models are estimated using American Community Survey data and applied to derive individual-level estimates for All of Us participants. We assess concordance between model-based SDoH estimates and self-reported SDoHs in All of Us and examine associations with undiagnosed hypertension and diabetes.
resultsCompared to self-reported SDoHs, the area under the curve for NOHSDP is 0.727 (95% CI, 0.724-0.730) and for UNINSUR is 0.730 (95% CI, 0.727-0.733) among the 329 074 All of Us participants, both significantly higher than aggregated SDoHs. The association between model-based NOHSDP and undiagnosed hypertension is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.649. Similarly, the association between model-based NOHSDP and undiagnosed diabetes is concordant with those estimated using self-reported NOHSDP, with a correlation coefficient of 0.900. DISCUSSION AND
conclusionThe model-based SDoH estimation method offers a scalable and easily standardized approach for estimating individual-level SDoHs. Using the All of Us dataset, we demonstrate reasonable concordance between model-based SDoH estimates and self-reported SDoHs, along with consistent associations with health outcomes. Our findings also underscore the critical role of geographic contexts in SDoH estimation and in evaluating the association between SDoHs and health outcomes.
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