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 language | English (US) |
---|---|
Pages (from-to) | 477-481 |
Number of pages | 5 |
Journal | Studies in health technology and informatics |
Volume | 107 |
DOIs | |
State | Published - Jan 1 2004 |
Keywords
- Controlled
- Information Storage and Retrieval
- Information Theory
- Vocabulary
ASJC Scopus subject areas
- Biomedical Engineering
- Health Informatics
- Health Information Management