Initializing the VA medication reference terminology using UMLS metathesaurus co-occurrences.
We developed and evaluated a UMLS Metathesaurus Co-occurrence mining algorithm to connect medications and diseases they may treat. Based on 16 years of co-occurrence data, we created 977 candidate drug-disease pairs for a sample of 100 ingredients (50 commonly prescribed and 50 selected at random). Our evaluation showed that more than 80% of the candidate drug-disease pairs were rated "APPROPRIATE" by physician raters. Additionally, there was a highly significant correlation between the overall frequency of citation and the likelihood that the connection was rated "APPROPRIATE." The drug-disease pairs were used to initialize term definitions in an ongoing effort to build a medication reference terminology for the Veterans Health Administration. Co-occurrence mining is a valuable technique for initializing term definitions in a large-scale reference terminology creation project.
Carter
John S
JS
University of Utah, USA.
Brown
Steven H
SH
Erlbaum
Mark S
MS
Gregg
William
W
Elkin
Peter L
PL
Speroff
Ted
T
Tuttle
Mark S
MS
D000465:Algorithms; D004358:Drug Therapy; D004364:Pharmaceutical Preparations / Q000145:classification*; D013358:Subject Headings; D017432:Unified Medical Language System; D014481:United States; D014493:United States Department of Veterans Affairs; D018875:Vocabulary, Controlled
D004364:Pharmaceutical Preparations