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Interoperability of Medication Classification Systems: Lessons Learned Mapping Established Pharmacologic Classes (EPCs) to SNOMED CT.

Authors :
Nelson, Scott D.
Parker, Jaqui
Lario, Robert
Winnenburg, Rainer
Erlbaum, Mark S.
Lincoln, Michael J.
Bodenreider, Olivier
Source :
Studies in Health Technology & Informatics; 2017, Vol. 245, p920-924, 5p, 1 Diagram, 1 Chart
Publication Year :
2017

Abstract

Interoperability among medication classification systems is known to be limited. We investigated the mapping of the Established Pharmacologic Classes (EPCs) to SNOMED CT. We compared lexical and instance-based methods to an expert-reviewed reference standard to evaluate contributions of these methods. Of the 543 EPCs, 284 had an equivalent SNOMED CT class, 205 were more specific, and 54 could not be mapped. Precision, recall, and F1 score were 0.416, 0.620, and 0.498 for lexical mapping and 0.616, 0.504, and 0.554 for instance-based mapping. Each automatic method has strengths, weaknesses, and unique contributions in mapping between medication classification systems. In our experience, it was beneficial to consider the mapping provided by both automated methods for identifying potential matches, gaps, inconsistencies, and opportunities for quality improvement between classifications. However, manual review by subject matter experts is still needed to select the most relevant mappings. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09269630
Volume :
245
Database :
Complementary Index
Journal :
Studies in Health Technology & Informatics
Publication Type :
Academic Journal
Accession number :
127070507
Full Text :
https://doi.org/10.3233/978-1-61499-830-3-920