Large-Scale Integration of DICOM Metadata into HL7-FHIR for Medical Research
We demonstrated the setup and test of a large-scale end-to-end data processing pipeline that transforms DICOM imaging metadata directly from clinical routine into the Health Level 7-FHIR format, pseudonymizes the resources, and stores them in an FHIR server. We showcased that the derived FHIRs offer numerous research opportunities, for example, feasibility assessments within Bavarian and Germany-wide research infrastructures. Insights from this study highlight the need to extend the "ImagingStudy" FHIR with additional attributes and refine their use within the German MII.
Authors
- Arnd Doerfler (ORCID: https://orcid.org/0000-0002-3076-3231)
- Lorenz A. Kapsner (ORCID: https://orcid.org/0000-0003-1866-860X)
- Michael Uder (ORCID: https://orcid.org/0000-0001-6238-4247)
- Matthias May (ORCID: https://orcid.org/0000-0002-2540-850X)
- Johannes Bauer (ORCID: https://orcid.org/0009-0003-4248-877X)
- Hans‐Ulrich Prokosch
- Alexa Iancu
Institutions
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Universitätsklinikum Erlangen (DE)
- Bayer (Germany) (DE)
Publication Details
- Journal
- Methods of Information in Medicine
- Published
- 2024-09-01
- DOI
- https://doi.org/10.1055/a-2521-4250
- Citations
- 8
- Primary Topic
- Digital Radiography and Breast Imaging
- Type
- article
- Field-Weighted Citation Impact
- 3.35
Funders
- Bundesministerium für Bildung und Forschung
- Universitätsklinikum Erlangen