Enhancing adverse drug reaction data quality in Canada: A high-precision pipeline for medication name standardization and enrichment.

backgroundThe Canada Vigilance Adverse Reaction database is a vital pharmacovigilance tool, but its utility is severely limited by heterogeneity in medication nomenclature. A substantial portion (∼36.8%) of unique drug name variants in the database lack any mapping to an active ingredient, representing a critical data quality gap that can mask important adverse drug reaction (ADR) signals.

methodsWe developed, validated, and publicly released a high-precision, automated pipeline to standardize and enrich medication names. The pipeline employs a cascaded matching strategy that leverages the RxNorm and Observational Health Data Sciences and Informatics (OHDSI) vocabularies. Standardized names are assigned a RxNorm Concept Unique Identifier (RxCUI) and enriched with active ingredient data and Anatomical Therapeutic Chemical (ATC) classifications via RxNav APIs. The pipeline's accuracy was rigorously assessed by two independent experts on a balanced validation set of 200 cases.

resultsThe final pipeline successfully standardized 94.5% of the 46,585 unique drug names. A blinded expert validation confirmed high reliability, demonstrating a precision of 98.02% (95% CI: 0.9307-0.9946) and specificity of 97.22% (95% CI: 0.9043-0.9923). Case studies showed that standardization and aggregation of reports revealed known safety signals (e.g., mesalamine and asthenia) that were statistically undetectable in the raw data.

conclusionOur transparent and reproducible pipeline effectively resolves medication name heterogeneity in Canada's national ADR database. By transforming variable text into standardized concepts, it significantly enhances data quality, improves the sensitivity of safety signal detection, and facilitates interoperability with global health datasets. The publicly available tool provides a valuable resource for strengthening drug safety surveillance in Canada and beyond.