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Oncology on FHIR: A Data Model for Distributed Cancer Research.

Mohamed Lambarki1, Jori Kern1, David Croft1

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This summary is machine-generated.

Integrating cancer research and patient care requires standardized data. This study shows how a harmonized FHIR-based data model can bridge the gap for secondary data use in translational oncology research.

Keywords:
DKTKFHIRInteroperabilityOncologybiobankingcomprehensive cancer center

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Area of Science:

  • Oncology
  • Health Informatics
  • Bioinformatics

Background:

  • Effective cancer research demands seamless integration between patient care and research.
  • Germany has data exchange but lacks international health data standards.
  • Translational cancer research requires standardized secondary data use.

Purpose of the Study:

  • To demonstrate closing the gap in health data standardization for translational cancer research.
  • To present a harmonized FHIR-based data model.
  • To apply this model to an existing federated data platform using German Cancer Consortium use cases.

Main Methods:

  • Utilizing use cases from the German Cancer Consortium (DKTK).
  • Developing and applying a harmonized Fast Healthcare Interoperability Resources (FHIR)-based data model.
  • Integrating the model into a federated data platform.

Main Results:

  • Successfully demonstrated a method to harmonize health data using FHIR.
  • Showcased the application of the FHIR-based model within a federated data platform.
  • Addressed the need for internationally coordinated health data standards in oncology.

Conclusions:

  • A harmonized FHIR-based data model can effectively bridge the gap in health data standardization.
  • This approach facilitates secondary data use for translational cancer research.
  • Implementation within existing federated platforms is feasible and beneficial.