Document Detail


Using text-mining techniques in electronic patient records to identify ADRs from medicine use.
MedLine Citation:
PMID:  22122057     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
This literature review included studies that use text-mining techniques in narrative documents stored in electronic patient records (EPRs) to investigate ADRs. We searched PubMed, Embase, Web of Science and International Pharmaceutical Abstracts without restrictions from origin until July 2011. We included empirically based studies on text mining of electronic patient records (EPRs) that focused on detecting ADRs, excluding those that investigated adverse events not related to medicine use. We extracted information on study populations, EPR data sources, frequencies and types of the identified ADRs, medicines associated with ADRs, text-mining algorithms used and their performance. Seven studies, all from the United States, were eligible for inclusion in the review. Studies were published from 2001, the majority between 2009 and 2010. Text-mining techniques varied over time from simple free text searching of outpatient visit notes and inpatient discharge summaries to more advanced techniques involving natural language processing (NLP) of inpatient discharge summaries. Performance appeared to increase with the use of NLP, although many ADRs were still missed. Due to differences in study design and populations, various types of ADRs were identified and thus we could not make comparisons across studies. The review underscores the feasibility and potential of text mining to investigate narrative documents in EPRs for ADRs. However, more empirical studies are needed to evaluate whether text mining of EPRs can be used systematically to collect new information about ADRs.
Authors:
Pernille Warrer; Ebba Holme Hansen; Lars Juhl-Jensen; Lise Aagaard
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Review    
Journal Detail:
Title:  British journal of clinical pharmacology     Volume:  73     ISSN:  1365-2125     ISO Abbreviation:  Br J Clin Pharmacol     Publication Date:  2012 May 
Date Detail:
Created Date:  2012-04-10     Completed Date:  2012-08-02     Revised Date:  2013-06-27    
Medline Journal Info:
Nlm Unique ID:  7503323     Medline TA:  Br J Clin Pharmacol     Country:  England    
Other Details:
Languages:  eng     Pagination:  674-84     Citation Subset:  IM    
Copyright Information:
© 2011 The Authors. British Journal of Clinical Pharmacology © 2011 The British Pharmacological Society.
Affiliation:
Department of Pharmacology and Pharmacotherapy, Section for Social Pharmacy, Faculty of Pharmaceutical Sciences, University of Copenhagen, Copenhagen, Denmark. pwa@farma.ku.dk
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MeSH Terms
Descriptor/Qualifier:
Adverse Drug Reaction Reporting Systems / statistics & numerical data*
Algorithms
Data Mining / methods*
Humans
Medical Records Systems, Computerized / statistics & numerical data*
Natural Language Processing*
Pharmaceutical Preparations / adverse effects*
Pharmacovigilance*
Chemical
Reg. No./Substance:
0/Pharmaceutical Preparations
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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