title: Development of an ensemble resource linking MEDications to their Indications (MEDI).
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.
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, TN.
authors.forename: Wei-Qi
authors.initials: WQ
authors.lastname: Wei
authors.forename: Robert M
authors.initials: RM
authors.lastname: Cronin
authors.forename: Hua
authors.initials: H
authors.lastname: Xu
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Lasko
authors.forename: Lisa
authors.initials: L
authors.lastname: Bastarache
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Denny