Country / Region
Americas
Tags
Collaboration, Implementation, Mapping, Tooling
SNOMED CT is playing an increasingly vital role in bridging national drug dictionaries with electronic clinical records. Several countries are aligning their drug data with the SNOMED International Clinical Drug Model, while recent enhancements to SNOMED CT—particularly in its capacity to represent non-defining associations and metadata annotations—are expanding its use as a versioned, standardized content distribution suitable for consumption by terminology servers. However, each country approaches this alignment from different starting points, with varying source formats, data models, and local priorities. In this paper, we identify recurring patterns and the challenges they present, and propose strategic approaches that combine mapping techniques, automated transformations, expert curation and revision processes, and concept model extensions to enhance representation, ensure local relevance, and maintain transparency of source data.
Description
This paper examines the challenges encountered during the implementation of three national drug extensions, each originating from distinct data sources. We present the strategies employed to align these extensions with the SNOMED International model, which vary depending on the characteristics and constraints of each source. These strategies range from fully automated transformations—applied when source alignment gaps are minimal or when maximizing source transparency is critical—to more complex approaches involving manual curation at the individual product level. In some cases, the process also required the creation of use case-specific classes to support key functions such as prescription, dispensing, and data analytics.
Scope
SNOMED CT was selected as it is emerging as the leading reference model for integrating locally marketed medicinal products with clinical data in electronic health records (EHRs). It is also evolving into a comprehensive, standards-based distribution format that defines the semantics of drug classes and incorporates relevant metadata to support their use across diverse clinical and analytical settings.
How SNOMED CT will be used
SNOMED CT serves as a bridge between medicinal product data stored in national drug dictionaries and clinical information recorded in patient health records. It enables a wide range of use cases, including clinical decision support, accurate data recording, and electronic prescribing. However, to address specific local requirements, the international drug model often requires adaptation—through localization, extension, and harmonization—ultimately evolving into a comprehensive content model tailored to each implementation context.
Why SNOMED CT will be used
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