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

Overview

Journal Sci Transl Med

Specialties General Medicine
Science

Date 2011 Apr 22

PMID 21508311

Citations 218

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

Affiliations

Soon will be listed here.

Abstract

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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References

Blumenthal D, Tavenner M . The "meaningful use" regulation for electronic health records. N Engl J Med. 2010; 363(6):501-4. DOI: 10.1056/NEJMp1006114. View

Larson E, Wang L, Bowen J, McCormick W, Teri L, Crane P . Exercise is associated with reduced risk for incident dementia among persons 65 years of age and older. Ann Intern Med. 2006; 144(2):73-81. DOI: 10.7326/0003-4819-144-2-200601170-00004. View

Linder J, Ma J, Bates D, Middleton B, Stafford R . Electronic health record use and the quality of ambulatory care in the United States. Arch Intern Med. 2007; 167(13):1400-5. DOI: 10.1001/archinte.167.13.1400. View

Murphy S, Churchill S, Bry L, Chueh H, Weiss S, Lazarus R . Instrumenting the health care enterprise for discovery research in the genomic era. Genome Res. 2009; 19(9):1675-81. PMC: 2752136. DOI: 10.1101/gr.094615.109. View

Burke W, Psaty B . Personalized medicine in the era of genomics. JAMA. 2007; 298(14):1682-4. DOI: 10.1001/jama.298.14.1682. View

Xu H, Stenner S, Doan S, Johnson K, Waitman L, Denny J . MedEx: a medication information extraction system for clinical narratives. J Am Med Inform Assoc. 2010; 17(1):19-24. PMC: 2995636. DOI: 10.1197/jamia.M3378. View

DesRoches C, Campbell E, Rao S, Donelan K, Ferris T, Jha A . Electronic health records in ambulatory care--a national survey of physicians. N Engl J Med. 2008; 359(1):50-60. DOI: 10.1056/NEJMsa0802005. View

Allen R, Criqui M, Diez Roux A, Allison M, Shea S, Detrano R . Fine particulate matter air pollution, proximity to traffic, and aortic atherosclerosis. Epidemiology. 2009; 20(2):254-64. PMC: 3292428. DOI: 10.1097/EDE.0b013e31819644cc. View

Denny J, Spickard 3rd A, Johnson K, Peterson N, Peterson J, Miller R . Evaluation of a method to identify and categorize section headers in clinical documents. J Am Med Inform Assoc. 2009; 16(6):806-15. PMC: 3002123. DOI: 10.1197/jamia.M3037. View

10.

Liao K, Cai T, Gainer V, Goryachev S, Zeng-Treitler Q, Raychaudhuri S . Electronic medical records for discovery research in rheumatoid arthritis. Arthritis Care Res (Hoboken). 2010; 62(8):1120-7. PMC: 3121049. DOI: 10.1002/acr.20184. View

11.

Diez Roux A, Merkin S, Arnett D, Chambless L, Massing M, Nieto F . Neighborhood of residence and incidence of coronary heart disease. N Engl J Med. 2001; 345(2):99-106. DOI: 10.1056/NEJM200107123450205. View

12.

Breitner J, Haneuse S, Walker R, Dublin S, Crane P, Gray S . Risk of dementia and AD with prior exposure to NSAIDs in an elderly community-based cohort. Neurology. 2009; 72(22):1899-905. PMC: 2690966. DOI: 10.1212/WNL.0b013e3181a18691. View

13.

Schildcrout J, Basford M, Pulley J, Masys D, Roden D, Wang D . An analytical approach to characterize morbidity profile dissimilarity between distinct cohorts using electronic medical records. J Biomed Inform. 2010; 43(6):914-23. PMC: 2991387. DOI: 10.1016/j.jbi.2010.07.011. View

14.

Church G . Genomes for all. Sci Am. 2006; 294(1):46-54. DOI: 10.1038/scientificamerican0106-46. View

15.

Ginsburg G, Willard H . Genomic and personalized medicine: foundations and applications. Transl Res. 2009; 154(6):277-87. DOI: 10.1016/j.trsl.2009.09.005. View

16.

Friedlin J, Grannis S, Overhage J . Using natural language processing to improve accuracy of automated notifiable disease reporting. AMIA Annu Symp Proc. 2008; :207-11. PMC: 2656046. View

17.

Kullo I, Fan J, Pathak J, Savova G, Ali Z, Chute C . Leveraging informatics for genetic studies: use of the electronic medical record to enable a genome-wide association study of peripheral arterial disease. J Am Med Inform Assoc. 2010; 17(5):568-74. PMC: 2995686. DOI: 10.1136/jamia.2010.004366. View

18.

Denny J, Ritchie M, Crawford D, Schildcrout J, Ramirez A, Pulley J . Identification of genomic predictors of atrioventricular conduction: using electronic medical records as a tool for genome science. Circulation. 2010; 122(20):2016-21. PMC: 2991609. DOI: 10.1161/CIRCULATIONAHA.110.948828. View

19.

Shea S, Hripcsak G . Accelerating the use of electronic health records in physician practices. N Engl J Med. 2010; 362(3):192-5. DOI: 10.1056/NEJMp0910140. View

20.

Blumenthal D . Stimulating the adoption of health information technology. N Engl J Med. 2009; 360(15):1477-9. DOI: 10.1056/NEJMp0901592. View