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PMID: 30516347 Published · ppublish English Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Using Electronic Health Records To Generate Phenotypes For Research.

Current protocols in human genetics ·Vol. 100 ·No. 1 ·2019-00-00 ·Pages e80

Pendergrass SA, Crawford DC

Abstract

Electronic health records contain patient-level data collected during and for clinical care. Data within the electronic health record include diagnostic billing codes, procedure codes, vital signs, laboratory test results, clinical imaging, and physician notes. With repeated clinic visits, these data are longitudinal, providing important information on disease development, progression, and response to treatment or intervention strategies. The near universal adoption of electronic health records nationally has the potential to provide population-scale real-world clinical data accessible for biomedical research, including genetic association studies. For this research potential to be realized, high-quality research-grade variables must be extracted from these clinical data warehouses. We describe here common and emerging electronic phenotyping approaches applied to electronic health records, as well as current limitations of both the approaches and the biases associated with these clinically collected data that impact their use in research. © 2018 by John Wiley & Sons, Inc.

Keywords
computable phenotyping electronic health records electronic medical records electronic phenotyping precision medicine
MeSH Terms
Algorithms Data Mining Electronic Health Records Humans Phenotype
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Pendergrass Sarah A
Biomedical and Translational Informatics Institute, Geisinger Research, Rockville, Maryland.
Crawford Dana C
Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio.
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Article Info
Journal
Current protocols in human genetics
Abbr.
Curr Protoc Hum Genet
ISSN
1934-8258
DOI
10.1002/cphg.80
Published
2019-00-00
Epub
2018-00-05
Pages
e80
Language
English
Region
United States
NLM ID
101287858
PMCID
PMC6318047
Subset
IM
Grants
NCATS NIH HHS · UL1 TR002548 · United States
NIGMS NIH HHS · R01 GM126249 · United States
NCATS NIH HHS · UL1 TR000439 · United States
External Links
PubMed source DOI: 10.1002/cphg.80 PMC Full Text
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