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Development of an ensemble resource linking MEDications to their Indications (MEDI).

Authors :
Wei WQ
Cronin RM
Xu H
Lasko TA
Bastarache L
Denny JC
Source :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science [AMIA Jt Summits Transl Sci Proc] 2013 Mar 18; Vol. 2013, pp. 172. Date of Electronic Publication: 2013 Mar 18 (Print Publication: 2013).
Publication Year :
2013

Abstract

Understanding of medications-disease relationships is critical to distinguish indications from adverse effects, and medication exposures serve as important markers of disease and severity in electronic medical records (EMR). We created a computable medication-indication (MEDI) resource by applying natural language processing and ontology relationships to four public medication resources. Physicians evaluated accuracy of medication-indication relationships. MEDI contained 3,112 medications and 63,343 medication-indication pairs derived from the four resources, whose precisions varied from 56-94%. The MEDI high precision subset (MEDI-HPS) includes indications found within either RxNorm or ≥2 resources and had an estimated precision of 92%. MEDI-HPS contains 13,304 unique indication pairs for 2,136 medications. MEDI is a free, computable resource that links medications with their indications as represented by formal concepts and may assist clinical and research uses of EMR data.

Details

Language :
English
ISSN :
2153-4063
Volume :
2013
Database :
MEDLINE
Journal :
AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science
Publication Type :
Academic Journal
Accession number :
24303333