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.
The role of data in public health and health innovation: Perspectives on social determinants of health, community-based data approaches, and AI
Journal of Medical Internet Research, 27, e78794. doi: 10.2196/78794. PMCID: PMC12505398.