The Department of Health and Human Services has awarded $1.5 million to fund agentic AI and laboratory interoperability projects, with MedStar Health Research Institute and the Regenstrief Institute tapped to build tools supporting patient-controlled AI workflows and improved laboratory data exchange between health systems.
What the Grants Fund
MedStar Health Research Institute’s portion of the award will go toward developing patient-controlled AI workflow tools — systems designed to let patients decide how and when AI agents can access or act on their health data, rather than giving providers or vendors unilateral control. Regenstrief Institute, a longtime leader in health informatics research based in Indianapolis, will focus its share on laboratory data interoperability, addressing a persistent problem in American healthcare where lab results generated at one facility often cannot be easily and automatically shared with another.
Why Interoperability Still Matters in 2026
Despite more than a decade of federal push toward electronic health record interoperability, laboratory data exchange remains a stubborn bottleneck, with many health systems relying on fax machines, manual data entry, or proprietary formats that don’t translate cleanly across different EHR vendors. Agentic AI systems that could automatically reconcile, request, or route lab data promise to reduce this friction, but only if the underlying data formats and permission structures are standardized enough for AI agents to act reliably across institutional boundaries.
The Patient Control Angle
MedStar’s focus on patient-controlled workflows reflects a growing emphasis in federal health AI policy on giving patients agency over how AI interacts with their records, a response partly to concerns raised by physicians this year about the need for risk-based review and clear stop rules for clinical AI agents operating with minimal oversight. Patient groups have pushed for similar control mechanisms as AI increasingly mediates everything from appointment scheduling to clinical documentation.
A Modest Sum for an Ambitious Goal
At $1.5 million combined, the grant is small relative to the scale of the interoperability and agentic-AI governance challenges it aims to address, and HHS has not indicated whether additional funding rounds will follow depending on early results. Health IT researchers note that federal interoperability initiatives have historically required sustained, multi-year investment to produce infrastructure changes that stick, making a single modest grant more of a pilot signal than a comprehensive fix.
Part of a Broader Federal AI Health Push
The award comes alongside separate HHS announcements of four ARPA-H initiatives aimed at AI-assisted clinical trial design, suggesting the department is pursuing parallel tracks: one focused on trial acceleration, another on the more foundational plumbing of data interoperability and patient control that underlies nearly every other health AI application. Both reflect a recognition that AI’s usefulness in healthcare is often constrained less by model capability than by data access and governance structures.
What’s Next
MedStar and Regenstrief have not published detailed timelines for their respective projects, and HHS has not specified metrics by which the grants’ success will be evaluated. Health informatics researchers will be watching whether the resulting tools gain adoption beyond the funded institutions, since interoperability solutions that don’t scale across multiple health systems tend to have limited real-world impact regardless of their technical merit.
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