AI Article Synopsis
- A large portion of data in Electronic Health Records exists as unstructured text, like clinical notes and discharge summaries, which requires natural language processing (NLP) tools to convert it into a structured format for further use.
- To facilitate data exchange between different healthcare systems, harmonization is essential, with HL7 FHIR providing an emerging standard for structured healthcare data.
- Averbis Health Discovery (AHD) is a German-language medical NLP tool that offers a REST interface for text analysis, and a new service has been created to connect this interface with FHIR communication, available as open source.
Article Abstract
A significant portion of data in Electronic Health Records is only available as unstructured text, such as surgical or finding reports, 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.
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| http://dx.doi.org/10.3233/SHTI220026 | DOI Listing |
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