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Comparing Pharmacologic Classes in NDF-RT
Background: Clinical decision support systems and semantic mining require interoperable representations of pharmacologic classes across reference terminological systems. We explore two such systems: NDF-RT and SNOMED CT. Methods: We evaluate the overlap of pharmacologic classes in NDF-RT (VA Classes) and SNOMED CT. We compare classes based on the set of their members (drugs) across systems, using the Jaccard coefficientcient as a measure of overlap between two classes. Results: There is a limited overlap among the two systems. The average Jaccard value is 0.293. Only 11.5% of the VA classes have a Jaccard value of 0.75 or above. Conclusions: The analysis of discrepancies between pharmacologic classes across systems oㄦs a strategy for identifying classes in need of critical review. Due to the heterogeneity of the representation of pharmacologic classes in various terminologies, we recommend that drugs, not classes, be annotated in text for semantic mining purposes.