Electronic Medical Records for Genetic Research: Results of the eMERGE Consortium

被引：231

作者：

Kho, Abel N. ^{[1
,2
]}

Pacheco, Jennifer A. ^{[1
]}

Peissig, Peggy L. ^{[3
]}

Rasmussen, Luke ^{[3
]}

Newton, Katherine M. ^{[4
,5
]}

Weston, Noah ^{[4
]}

Crane, Paul K. ^{[6
]}

Pathak, Jyotishman ^{[7
]}

Chute, Christopher G. ^{[7
]}

Bielinski, Suzette J. ^{[7
]}

Kullo, Iftikhar J. ^{[8
]}

Li, Rongling ^{[9
]}

Manolio, Teri A. ^{[9
]}

Chisholm, Rex L. ^{[1
]}

Denny, Joshua C. ^{[10
]}

机构：

[1] Northwestern Univ, Feinberg Sch Med, Chicago, IL 60611 USA

[2] Regenstrief Inst Inc, Indianapolis, IN 46202 USA

[3] Marshfield Clin Res Fdn, Marshfield, WI 54449 USA

[4] Grp Hlth Res Inst, Seattle, WA 98101 USA

[5] Univ Washington, Sch Publ Hlth, Seattle, WA 98104 USA

[6] Univ Washington, Sch Med, Seattle, WA 98104 USA

[7] Mayo Clin, Dept Hlth Sci Res, Rochester, MN 55905 USA

[8] Mayo Clin, Dept Internal Med, Rochester, MN 55905 USA

[9] NHGRI, Off Populat Genom, Bethesda, MD 20892 USA

[10] Vanderbilt Univ, Dept Biomed Informat & Med, Nashville, TN 37232 USA

来源：

SCIENCE TRANSLATIONAL MEDICINE | 2011年 / 3卷 / 79期

关键词：

HEALTH RECORDS; PERSONALIZED MEDICINE; HISTORY INFORMATION; DISCOVERY RESEARCH; AMBULATORY-CARE; QUALITY; DEMENTIA; IDENTIFICATION; NEIGHBORHOOD; ASSOCIATION;

D O I：

10.1126/scitranslmed.3001807

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

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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