AHD2FHIR

AHD2FHIR converts Averbis Health Discovery (AHD) text-analysis output from unstructured EHR documents (clinical notes, surgical reports, discharge summaries) into HL7 Fast Healthcare Interoperability Resources (FHIR) to produce structured, interoperable data for research and clinical use.

Key Features:

• RESTful Integration: Operates as a RESTful intermediary and receives AHD output via AHD's proprietary REST interface.
• NLP Integration: Consumes Averbis Health Discovery (AHD) extractions, including German-language medical text processing using advanced NLP techniques, to capture clinical entities and attributes.
• FHIR Standardization: Maps extracted entities and attributes into HL7 FHIR resources to generate standardized representations for interoperability.

Scientific Applications:

• Data Harmonization: Converts heterogeneous unstructured EHR text into FHIR-compliant resources to harmonize data across sources for large-scale studies.
• Enhanced Data Utilization: Provides structured clinical information for secondary analyses, predictive model development, and evidence-based research.
• Interoperability in Healthcare Systems: Enables sharing of structured clinical data across health information systems via FHIR.

Methodology:

AHD2FHIR receives AHD text-analysis output via AHD's proprietary REST interface, accepts clinical entities extracted by AHD's advanced NLP on German-language EHR texts (clinical notes, surgical reports, discharge summaries), and maps these extracted items into HL7 FHIR resource structures.