VA national drug file reference terminology: A cross-institutional content coverage study

Steven H. Brown, Peter L. Elkin, S. Trent Rosenbloom, Casey Husser, Brent A. Bauer, Michael J. Lincoln, John Carter, Mark Erlbaum, Mark S. Tuttle

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Background: Content coverage studies provide valuable information to potential users of terminologies. We detail the VA National Drug File Reference Terminology's (NDF-RT) ability to represent dictated medication list phrases from the Mayo Clinic. NDF-RT is a description logic-based resource created to support clinical operations at one of the largest healthcare providers in the US. Methods: Medication list phrases were extracted from dictated patient notes from the Mayo Clinic. Algorithmic mappings to NDF-RT using the SmartAccess Vocabulary Server (SAVS) were presented to two non-VA physicians. The physicians used a terminology browser to determine the accuracy of the algorithmic mapping and the content coverage of NDF-RT Results: The 509 extracted documents on 300 patients contained 847 medication concepts in medication lists. NDF-RT covered 97.8% of concepts. Of the 18 phrases that NDF-RT did not represent, 10 were for OTC's and food supplements, 5 were for prescription medications, and 3 were missing synonyms. The SAVS engine properly mapped 773 of 810 phrases with an overall sensitivity (precision) was 95.4% and positive predictive value (recall) of 99.9%. Conclusions: This study demonstrates that NDF-RT has more general utility than its initial design parameters dictated.

Original languageEnglish (US)
Pages (from-to)477-481
Number of pages5
JournalStudies in health technology and informatics
Volume107
DOIs
StatePublished - Jan 1 2004

Keywords

  • Controlled
  • Information Storage and Retrieval
  • Information Theory
  • Vocabulary

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

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