Moving data is only the first requirement
Interoperability requires that receiving systems can use information appropriately, not merely transport it. A successful connection can still deliver ambiguous units, mismatched identities, or incomplete context. Document what data means, where it originated, and how it relates to the care workflow. This matters when AI systems consume records from several sources: a model cannot reliably compensate for missing or incorrectly mapped clinical information simply because the network delivering it is faster.
Understand what FHIR provides
HealthIT.gov describes HL7 FHIR as an API-focused standard for representing and exchanging health information. Its modular resources provide building blocks for clinical and administrative data. Implementation still requires agreement on supported resources, profiles, terminology, and operations. Ask vendors to specify versions and tested capabilities rather than accepting a broad claim of compatibility. A product exposing an interface does not automatically exchange every required data element or fit every organization’s workflow without additional work.
Verify identity, permissions, and provenance
Map patient and encounter identifiers carefully, and define who can read or modify information. Preserve source and timestamp information where needed for interpretation. Authentication proves which caller is connecting; authorization determines what that caller may do. Both must match the deployment. For AI integrations, distinguish read access from permission to create or change a clinical record. A proposed write should be validated through the appropriate application and human controls rather than accepted because the generated content looks plausible.
Test the handoff with actual users
Build representative exchange scenarios covering ordinary records, missing values, duplicates, corrections, and unavailable systems. Verify that users can understand and act on the results in the intended setting. Monitor integration failures after launch and assign responsibility across suppliers. Interoperability is a continuing operational commitment, not a one-time checkbox. Strong interfaces can support future connectivity and AI changes, but meaningful information exchange still depends on consistent semantics, appropriate access, and workflow-aware implementation.