A significant portion of [[data]] in [[Electronic Health Record]]s is only available as unstructured [[text]], such as surgical or finding [[report]]s, clinical notes, and discharge summaries. To use this data for secondary purposes, [[natural language processing]] (NLP) tools are required to extract structured information. Furthermore, for interoperable use, [[harmonization]] of the data is necessary. HL7 Fast Healthcare Interoperability Resources (FHIR), an emerging standard for exchanging healthcare data, defines such a structured format. For German-language medical NLP, the tool Averbis Health Discovery (AHD) represents a comprehensive solution. AHD offers a proprietary REST interface for text analysis pipelines. To build a bridge between FHIR and this interface, we created a service that translates the communication around AHD from and to FHIR. The application is available under an open-source license
((Scheible R, Caliskan D, Fischer P, Thomczyk F, Zabka S, Schneider H, Boeker M, Schulz S, Prokosch HU, Gulden C. AHD2FHIR: A Tool for Mapping of Natural Language Annotations to Fast Healthcare Interoperability Resources - A Technical Case Report. Stud Health Technol Inform. 2022 Jun 6;290:32-36. doi: 10.3233/SHTI220026. PMID: 35672965.)).