Integrating electronic health record genotype and phenotype datasets to transform patient care.
- Authors
- Roden, D M; Denny, J C
- Year
- 2016
- Journal
- Clinical pharmacology and therapeutics
- PMID
- 26667791
- DOI
- 10.1002/cpt.321
- PMCID
- PMC4760864
The Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 mandates the development and implementation of electronic health record (EHR) systems across the country. While a primary goal is to improve the care of individual patients, EHRs are also key enabling resources for a vision of individualized (or personalized or precision) medicine: the aggregation of multiple EHRs within or across healthcare systems should allow discovery of patient subsets that have unusual and definable clinical trajectories that deviate importantly from the expected response in a "typical" patient. The spectrum of such personalized care can then extend from prevention to choice of medication to intensity or nature of follow-up.
General approach to EHR-based phenotyping adopted in the electronic Medical Records and Genomics (eMERGE) network. PPV: Positive predictive value
Creation of a structured deidentified dataset from the EHR. Identifiers are removed, biomedical concepts are identified and structured, medications are extracted and structured, and custom classifiers (such as case or control definitions, or algorithms to define smoking status) are applied. Over time, the structured dataset can thus become more useful as a research discovery tool than to original EHR.
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