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Executing Distributed Healthcare and Research Processes - The HiGHmed Data Sharing Framework.

Hauke Hund1, Reto Wettstein2, Christian M Heidt1

  • 1GECKO Institute, Heilbronn University of Applied Sciences, Germany.

Studies in Health Technology and Informatics
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Summary
This summary is machine-generated.

The HiGHmed Data Sharing Framework enables biomedical research by supporting complex processes like cohort estimation and pseudonymization. It uses BPMN 2.0 and FHIR R4 for interoperable data exchange across institutions.

Keywords:
BPMNBiomedical ResearchData SharingFHIRFrameworkInteroperabilityOpen SourceProcess

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Area of Science:

  • Medical Informatics
  • Health Data Interoperability
  • Biomedical Research Frameworks

Background:

  • Existing healthcare interoperability standards primarily focus on clinical data and delivery processes.
  • There is a need to support complex research processes, including cohort size estimation, proposal reviews, consent management, record linkage, and pseudonymization.
  • The HiGHmed medical informatics consortium requires a robust framework for these research-specific needs.

Purpose of the Study:

  • To introduce the open-source HiGHmed Data Sharing Framework.
  • To demonstrate its capability in executing arbitrary biomedical research and healthcare processes.
  • To facilitate secure and interoperable data exchange for research purposes.

Main Methods:

  • Implementation of a distributed business process engine.
  • Utilizing Business Process Model and Notation (BPMN) 2.0 for process modeling and execution.
  • Leveraging Fast Healthcare Interoperability Resources (FHIR) R4 for information exchange.

Main Results:

  • The framework supports a wide range of research processes beyond typical clinical data exchange.
  • It enables distributed execution of complex, cross-organizational research workflows.
  • The system is being deployed across eight German university hospitals and a trusted third party.

Conclusions:

  • The HiGHmed Data Sharing Framework provides a flexible and open-source solution for biomedical research interoperability.
  • It addresses the limitations of existing frameworks by encompassing research-specific workflows.
  • The ongoing rollout signifies its practical applicability and potential for broader adoption in health informatics.