Semiautomatic mapping of a national drug terminology to standardised OMOP drug concepts using publicly available supplementary information

BACKGROUND: Mapping national drug terminologies to internationally recognized standards is essential for harmonising health data across regions and supporting secondary data use. In Austria, the national drug terminology lacks fine-granular mappings to RxNorm and RxNorm Extension (RxN/E), limiting its integration into the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). This study aims to semiautomatically map Austria's national drug terminology to RxN/E, to enable improved interoperability and data standardisation for secondary use. METHODS: We implemented a semiautomated mapping approach using public supplementary data to bridge the gap between national drug concepts and RxN/E concepts. Probabilistic matching and hierarchical refinement techniques were applied to derive finer-grained and more meaningful mappings than previously available ingredient level mappings via the Anatomical Therapeutic Chemical (ATC) classification. We linked our mappings to other available European drug mappings for a validation of our results. RESULTS: Our process successfully mapped 18,390 (95.42%) of Austria's 19,273 drug concepts to RxN/E, surpassing previous mappings that focused solely on ingredient-level relationships. Specifically, we mapped 73.65% of the concepts to more specific RxN/E targets, such as branded drug boxes and quantified clinical drugs. We identified multiple vocabulary inconsistencies, including duplications and erroneous relationships within RxN/E, which were documented for improvement. The results are disseminated as Usagi-formatted CSV files and HL7 FHIR ConceptMaps to encourage transparency, ease of use, and community-driven refinement. CONCLUSIONS: The presented mapping approach highlights the feasibility and utility of leveraging publicly available supplementary data to create mappings between national drug terminology and RxN/E. Our method yields fine-grained mappings, enabling precise and comprehensive drug data integration for secondary use.