Document Detail


Electronic medical records for genetic research: results of the eMERGE consortium.
MedLine Citation:
PMID:  21508311     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
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.
Authors:
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:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Science translational medicine     Volume:  3     ISSN:  1946-6242     ISO Abbreviation:  Sci Transl Med     Publication Date:  2011 Apr 
Date Detail:
Created Date:  2011-04-21     Completed Date:  2011-08-05     Revised Date:  2012-02-08    
Medline Journal Info:
Nlm Unique ID:  101505086     Medline TA:  Sci Transl Med     Country:  United States    
Other Details:
Languages:  eng     Pagination:  79re1     Citation Subset:  IM    
Affiliation:
Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA. a-kho@northwestern.edu
Export Citation:
APA/MLA Format     Download EndNote     Download BibTex
MeSH Terms
Descriptor/Qualifier:
Clinical Trials as Topic
Data Collection / methods
Electronic Health Records*
Genetic Research*
Genome-Wide Association Study
Genomics
Humans
Phenotype
Grant Support
ID/Acronym/Agency:
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


Previous Document:  The fate and toxicity of Raman-active silica-gold nanoparticles in mice.
Next Document:  GRB2 Couples RhoU to EGFR Signaling and Cell Migration.