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Development and evaluation of an ensemble resource linking medications to their indications
Abstract Objective: To create a computable MEDicatiObjective: To create a computable MEDication Indication resource (MEDI) to support primary and secondary use of electronic medical records (EMRs). Materials and methods: We processed four public medication resources, RxNorm, Side Effect Resource (SIDER) 2, MedlinePlus, and Wikipedia, to create MEDI. We applied natural language processing and ontology relationships to extract indications for prescribable, single-ingredient medication concepts and all ingredient concepts as defined by RxNorm. Indications were coded as Unified Medical Language System (UMLS) concepts and International Classification of Diseases, 9th edition (ICD9) codes. A total of 689 extracted indications were randomly selected for manual review for accuracy using dual-physician review. We identified a subset of medication-indication pairs that optimizes recall while maintaining high precision. Results: MEDI contains 3112 medications and 63 343 medication-indication pairs. Wikipedia was the largest resource, with 2608 medications and 34 911 pairs. For each resource, estimated precision and recall, respectively, were 94% and 20% for RxNorm, 75% and 33% for MedlinePlus, 67% and 31% for SIDER 2, and 56% and 51% for Wikipedia. The MEDI high-precision subset (MEDI-HPS) includes indications found within either RxNorm or at least two of the three other resources. MEDI-HPS contains 13 304 unique indication pairs regarding 2136 medications. The mean±SD number of indications for each medication in MEDI-HPS is 6.22±6.09. The estimated precision of MEDI-HPS is 92%. Conclusions: MEDI is a publicly available, computable resource that links medications with their indications as represented by concepts and billing codes. MEDI may benefit clinical EMR applications and reuse of EMR data for research.ations and reuse of EMR data for research.
Abstractsub Objective: To create a computable MEDicatiObjective: To create a computable MEDication Indication resource (MEDI) to support primary and secondary use of electronic medical records (EMRs). Materials and methods: We processed four public medication resources, RxNorm, Side Effect Resource (SIDER) 2, MedlinePlus, and Wikipedia, to create MEDI. We applied natural language processing and ontology relationships to extract indications for prescribable, single-ingredient medication concepts and all ingredient concepts as defined by RxNorm. Indications were coded as Unified Medical Language System (UMLS) concepts and International Classification of Diseases, 9th edition (ICD9) codes. A total of 689 extracted indications were randomly selected for manual review for accuracy using dual-physician review. We identified a subset of medication-indication pairs that optimizes recall while maintaining high precision. Results: MEDI contains 3112 medications and 63 343 medication-indication pairs. Wikipedia was the largest resource, with 2608 medications and 34 911 pairs. For each resource, estimated precision and recall, respectively, were 94% and 20% for RxNorm, 75% and 33% for MedlinePlus, 67% and 31% for SIDER 2, and 56% and 51% for Wikipedia. The MEDI high-precision subset (MEDI-HPS) includes indications found within either RxNorm or at least two of the three other resources. MEDI-HPS contains 13 304 unique indication pairs regarding 2136 medications. The mean±SD number of indications for each medication in MEDI-HPS is 6.22±6.09. The estimated precision of MEDI-HPS is 92%. Conclusions: MEDI is a publicly available, computable resource that links medications with their indications as represented by concepts and billing codes. MEDI may benefit clinical EMR applications and reuse of EMR data for research.ations and reuse of EMR data for research.
Bibtextype article  +
Doi 10.1136/amiajnl-2012-001431  +
Has author Wei W.-Q. + , Cronin R.M. + , Xu H. + , Lasko T.A. + , Bastarache L. + , Denny J.C. +
Has extra keyword Captopril + , Ciprofloxacin + , Dexmethylphenidate + , Dobutamine + , Ephedrine + , Guaifenesin + , Isosorbide + , Sildenafil + , Accuracy + , Adverse drug reaction + , Article + , Asthma + , Consumer health information + , Cystic fibrosis + , Drug indication + , Drug recall + , Electronic medical record + , Fatigue + , Food and drug administration + , Full text database + , Gastroesophageal reflux + , Heart atrium fibrillation + , Human + , Hypertension + , ICD-9 + , Knowledge base + , Malaise + , Medical error + , Medication indication resource + , Medline + , Natural Language Processing + , Reference database + , Rheumatoid arthritis + , RxNorm + , Side effect resource 2 + , Systematized Nomenclature of Medicine + , Treatment outcome + , Unified Medical Language System + , Visual disorder + , Wikipedia + , Electronic medical records + , International Classification of Diseases + , Medication indications + , Ontology + , Terminology + , Dictionaries as Topic + , Drug Therapy + , Electronic Health Records + , Internet + , MedlinePlus + , Pharmaceutical Preparations +
Issn 10675027  +
Issue 5  +
Language English +
Number of citations by publication 0  +
Number of references by publication 0  +
Pages 954–961  +
Published in Journal of the American Medical Informatics Association +
Pubmed 23576672  +
Title Development and evaluation of an ensemble resource linking medications to their indications +
Type journal article  +
Volume 20  +
Year 2013 +
Creation dateThis property is a special property in this wiki. 7 November 2014 18:59:35  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Journal articles  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 7 November 2014 18:59:35  +
DateThis property is a special property in this wiki. 2013  +
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