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A Locally Deployable FHIR Validation Service for Federated Health Data Infrastructures - A Technical Case Report
Julian Saß1, Alexander Kiel2, Joshua Wiedekopf3
1Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Introduction:
The Medical Informatics Initiative enables the secondary use of clinical routine data in German university medicine through a federated FHIR-based infrastructure, with implementation guides defining the underlying data representation. Reliable validation of FHIR resources is required to ensure conformance with these specifications. However, validation in federated environments remains challenging due to heterogeneous infrastructures, limited terminology availability, and difficulties in establishing reproducible validation setups.
Methods:
This technical case report describes the design and implementation of a locally deployable FHIR validation service in the MII context. The system combines the HL7-maintained FHIR Validator with a configurable terminology service and a containerized deployment model. Structural and terminology validation are separated by design. Implementation guides and terminology resources are provisioned in a reproducible manner. The system supports both local terminology deployment and integration with existing institutional terminology services.
Results:
The proposed solution enables automated conformance testing of FHIR resource instances against MII implementation guides in local and federated environments. The service is provided as a reusable containerized validation component that can be integrated into development and data processing workflows, improving reproducibility, and reducing configuration effort across sites.
Discussion:
The results demonstrate that reproducible FHIR validation can be achieved through standardized deployment and controlled terminology provisioning. Remaining limitations are primarily related to incomplete or unavailable terminology content. Further work is required to evaluate the approach in production settings across data integration centers and to assess integration into data processing pipelines, including the handling and interpretation of validation results.
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