Authors: Ahmad Alkasir, Dr.P.H., M.P.H., Gabriel Seidman, Dr.P.H., Jolie Ritzo, M.P.H., Lisa Bari, M.B.A., M.P.H., and Anjum Khurshid, M.D., Ph.D.
New developments in AI hold enormous promise for improving clinical delivery, health care administration, and public health, all of which contribute to better health outcomes. However, the ability to capture tangible improvements in health outcomes from the paradigm shift in AI capabilities will remain constrained unless health information systems, regulations, and governance structures are modernized for the AI era in a manner that enables effective development, rigorous validation, and ongoing monitoring of models for safety and efficacy (e.g., AI assurance). In this article, we summarize the role that health information exchanges (HIEs) have played in establishing the existing technical infrastructure and governance for collecting, sharing, and reusing health data, mostly for primary use cases (e.g., care coordination) and less so for secondary use cases (e.g., public health, research). We highlight the opportunity to modernize HIEs into health data utilities (HDUs) — statewide entities with diverse stakeholder governance structures that support the informatic needs of a variety of users in a state or region. Moreover, we regard health AI development as a secondary use of data and note how establishing state-designated HDUs would support AI advancements through their enhanced capabilities and authority as aggregators and stewards of validated, high-quality, multisource health data. Furthermore, while HIE networks are widely acknowledged as critical infrastructure for data exchange, we explain why and how these networks — as they transition to HDUs — could support AI assurance policy for a subset of health AI models by promoting AI regulatory guidance, standards, and best practices; enabling robust model evaluations and transparent reporting; and supporting prospective monitoring of deployed applications.