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Updated: Jul 4, 2026
07:50
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
CAS2FHIR: Transforming UIMA CAS Annotations to FHIR Bundles.
Nektarios Ladas1,2, Stefan Franz1, Sarah Ballout1
1Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Germany.
Studies in Health Technology and Informatics
|July 3, 2026
Summary
We developed a tool to convert unstructured clinical data into the interoperable Fast Healthcare Interoperability Resources (FHIR) standard. This process enables better data utilization for research by transforming extracted information into FHIR resources and bundles.
Area of Science:
- Health Informatics
- Clinical Data Management
- Interoperability Standards
Background:
- Clinical data exists in diverse, often unstructured or semi-structured formats.
- Valuable insights within this data are difficult to access for research due to lack of standardization.
- Interoperability is crucial for effective data sharing and analysis in healthcare.
Purpose of the Study:
- To develop a tool for converting varied clinical data formats into a standardized, interoperable format.
- To facilitate the use of unstructured and semi-structured clinical data for research purposes.
- To create Fast Healthcare Interoperability Resources (FHIR) directly from information extraction pipelines.
Main Methods:
- Development of a custom tool leveraging a scripting language.
- Dynamic invocation of runtime API methods for FHIR resource creation.
- Mapping of extracted information to FHIR resources and bundles.
Main Results:
- Successful transformation of 13,240 clinical data instances into FHIR resources.
- Creation of FHIR bundles directly from the information extraction pipeline output.
- Demonstrated feasibility of automated FHIR data generation from diverse data sources.
Conclusions:
- The developed tool effectively converts unstructured/semi-structured clinical data into FHIR format.
- This facilitates enhanced data interoperability and research accessibility.
- Automated FHIR resource generation is a viable approach for modern healthcare data management.
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