The Role of Data in Public Health and Health Innovation: Perspectives on Social Determinants of Health, Community‐Based Data Approaches, and AI
Open accessAbstract
Public health is undergoing profound transformation driven by data from the global health sector and related fields. To address systemic health disparities, scholars and health practitioners are increasingly applying a data equity lens, an approach that has become even more urgent as the United States faces the erosion of public health data infrastructure. This paper summarizes insights from an April 2024 convening by the Yale School of Public Health—The Role of Data in Public Health Equity and Innovation—with intersectoral stakeholders from academia, government (local, state, and federal), health care, and private industry. The convening included keynote presentations and roundtables regarding the depiction of social determinants of health in data; effects of artificial intelligence (AI) on health data equity; and community-based models for data, providing a framework for cross-cutting discussions. Through a narrative synthesis, themes were identified and synthesized from systematically gathered information from presentations and roundtables. This process led to a set of actionable, cross-cutting recommendations to guide inclusive and impactful data practices for policymakers, public health professionals, and health innovators across diverse contexts: (1) enable big data and interoperability connecting social determinants of health and health outcomes; (2) include diverse, nontechnical voices in AI and health discussions; (3) fund research on data equity and AI in health sciences; (4) modernize the Health Insurance Portability and Accountability Act (HIPAA) with new guidelines for AI and big data; and (5) research and conceptual frameworks are needed to elucidate interconnections between data equity and health equity.
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Social determinants of health are primary drivers of health outcomes for economically disadvantaged groups in clinical settings.
“Social determinants of health (SDOH) encompass non‐medical conditions including birth, growth, work, and living environment, and are primary drivers of health outcomes for economically disadvantaged groups in clinical settings [1].”
From Artificial Intelligence and Machine Learning for Identifying Social Determinants of Health in Low‐Income Populations Within United States Health Systems: A Scoping Review (2026) · cites this paper as [1]
The Depiction of SDOH in Data section defines SDOH as nonmedical conditions where people are born, grow, live, and work, and says they account for up to 80% of health-related outcomes. It does not establish that they are primary drivers specifically for economically disadvantaged groups in clinical settings; its comparison is with the contribution of clinical care, not a finding limited to clinical settings. No page number is available in our copy. (LLM, conf=0.87)
Experimental — accuracy not yet measuredDegraded public health data infrastructure in the United States makes data equity efforts urgent.
“Degraded public health data infrastructure in the United States makes such efforts urgent [1].”
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- Authors
- Yelpaala, K., Gibbons, M. C., Vigil, I. M., Leaño, J., McCall, T., Opara, I., Zink, A., Nunez-Smith, M., Mukherjee, B., & Ranney, M.
- Affiliations
- Yale University (US)
- University of Michigan (US)
- Corresponding author
- Ranney, Megan
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2025-10-07
- Volume
- 27
- Pages
- e78794-e78794
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC12505398
- OpenAlex
- W4413176184
- Cited by
- 6
- References
- 30
- Citations by year
- 2026: 4 · 2025: 2
- FWCI
- 7.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Health Professions › General Health Professions › Public Health Policies and Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- data equity, social determinants of health, artificial intelligence in healthcare, health data infrastructure, health disparities, health equity, AI regulation, public health data, stakeholder perspectives
- MeSH terms
- Artificial Intelligence, Humans, Public Health, United States, Social Determinants of Health
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