JMIR Publications

ABSTRACT

Public health is undergoing profound transformation driven by data from the global health sector and related fields. To address systemic health disparities, scholars and practitioners are increasingly applying a data equity lens, themes particularly important in the current context of public health data in the United States. 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), healthcare, and private industry. The convening included keynote presentations and roundtables regarding the depiction of social determinants of health (SDOH) in data; effects of AI on health data equity; and community-based models for data, providing a framework for cross-cutting discussions. Themes were identified and synthesized from systematically gathered information from presentations and roundtables. This iterative process ensured actionable, cross-cutting findings and recommendations for policymakers, public health professionals, and health innovators for inclusive, impactful data practices across diverse contexts: 1. Enable big data and interoperability connecting SDOH and health outcomes. 2. Include diverse, non-technical voices in AI and health discussions. 3. Fund research on data equity and AI in health sciences. 4. Modernize Health Insurance Portability and Accountability Act (HIPAA) with new guidelines for AI and big data. 5. Research and conceptual frameworks are needed to elucidate interconnections between data equity and health equity.