| Electronic medical records for genetic research: results of the eMERGE consortium. | |
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MedLine Citation:
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PMID: 21508311 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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Clinical data in electronic medical records (EMRs) are a potential source of longitudinal clinical data for research. The Electronic Medical Records and Genomics Network (eMERGE) investigates whether data captured through routine clinical care using EMRs can identify disease phenotypes with sufficient positive and negative predictive values for use in genome-wide association studies (GWAS). Using data from five different sets of EMRs, we have identified five disease phenotypes with positive predictive values of 73 to 98% and negative predictive values of 98 to 100%. Most EMRs captured key information (diagnoses, medications, laboratory tests) used to define phenotypes in a structured format. We identified natural language processing as an important tool to improve case identification rates. Efforts and incentives to increase the implementation of interoperable EMRs will markedly improve the availability of clinical data for genomics research. |
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Authors:
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Abel N Kho; Jennifer A Pacheco; Peggy L Peissig; Luke Rasmussen; Katherine M Newton; Noah Weston; Paul K Crane; Jyotishman Pathak; Christopher G Chute; Suzette J Bielinski; Iftikhar J Kullo; Rongling Li; Teri A Manolio; Rex L Chisholm; Joshua C Denny |
Publication Detail:
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Type: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Science translational medicine Volume: 3 ISSN: 1946-6242 ISO Abbreviation: Sci Transl Med Publication Date: 2011 Apr |
Date Detail:
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Created Date: 2011-04-21 Completed Date: 2011-08-05 Revised Date: 2012-02-08 |
Medline Journal Info:
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Nlm Unique ID: 101505086 Medline TA: Sci Transl Med Country: United States |
Other Details:
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Languages: eng Pagination: 79re1 Citation Subset: IM |
Affiliation:
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Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA. a-kho@northwestern.edu |
Export Citation:
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| MeSH Terms | |
Descriptor/Qualifier:
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Clinical Trials as Topic Data Collection / methods Electronic Health Records* Genetic Research* Genome-Wide Association Study Genomics Humans Phenotype |
| Grant Support | |
ID/Acronym/Agency:
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1 UL1 RR024975/RR/NCRR NIH HHS; U01 HG004609-03/HG/NHGRI NIH HHS; U01-HG-004608/HG/NHGRI NIH HHS; U01-HG-004610/HG/NHGRI NIH HHS; U01-HG-04599/HG/NHGRI NIH HHS; U01-HG-04603/HG/NHGRI NIH HHS; U01HG004609/HG/NHGRI NIH HHS; UL1RR025741/RR/NCRR NIH HHS |
From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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