Document Detail


Determining the reasons for medication prescriptions in the EHR using knowledge and natural language processing.
MedLine Citation:
PMID:  22195134     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Knowledge of medication indications is significant for automatic applications aimed at improving patient safety, such as computerized physician order entry and clinical decision support systems. The Electronic Health Record (EHR) contains pertinent information related to patient safety such as information related to appropriate prescribing. However, the reasons for medication prescriptions are usually not explicitly documented in the patient record. This paper describes a method that determines the reasons for medication uses based on information occurring in outpatient notes. The method utilizes drug-indication knowledge that we acquired, and natural language processing. Evaluation showed the method obtained a sensitivity of 62.8%, specificity of 93.9%, precision of 90% and F-measure of 73.9%. This pilot study demonstrated that linking external drug indication knowledge to the EHR for determining the reasons for medication use was promising, but also revealed some challenges. Future work will focus on increasing the accuracy and coverage of the indication knowledge and evaluating its performance using a much larger set of drugs frequently used in the outpatient population.
Authors:
Ying Li; Hojjat Salmasian; Rave Harpaz; Herbert Chase; Carol Friedman
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2011-10-22
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  2011     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2011  
Date Detail:
Created Date:  2011-12-23     Completed Date:  2013-02-25     Revised Date:  2013-06-26    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  768-76     Citation Subset:  IM    
Affiliation:
Department of Biomedical Informatics, Columbia University, New York, NY, USA.
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MeSH Terms
Descriptor/Qualifier:
Artificial Intelligence*
Drug Prescriptions*
Electronic Health Records*
Humans
Knowledge Bases
Natural Language Processing*
Patient Safety
Physician's Practice Patterns*
Pilot Projects
Grant Support
ID/Acronym/Agency:
1R01LM010016/LM/NLM NIH HHS; 3R01LM010016-01S1/LM/NLM NIH HHS; 3R01LM010016-02S1/LM/NLM NIH HHS; 5T15-LM0070-19/LM/NLM NIH HHS; R01 LM010016/LM/NLM NIH HHS; R01 LM010016-04/LM/NLM NIH HHS; T15 LM007079/LM/NLM NIH HHS
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