Evaluating Electronic Phenotyping Algorithms

A group of clinicians and informaticians reviewed 21 eMERGE phenotype algorithms (Table 2) and several authoring tools (Measure Authoring Tool [www.emeasuretool.cms.gov], i2b2, Eureka!, PhenotypePortal, the Vanderbilt Synthetic Derivative,²⁷ (link) and the Marshfield Personalized Medicine Research Project interface⁵⁸ ) for common features. These phenotyping algorithms were of different complexity and included both disease and drug response phenotypes using algorithms from the eMERGE²² (link) and Pharmacogenomics of Very Large Populations (PGPop) networks. We also evaluated the ability to represent selected well-known diagnostic criteria (e.g., Duke criteria for infective endocarditis,⁵² (link) CHADS2 criteria for anticoagulation therapy in atrial fibrillation (AF)⁵¹ (link)) as potential phenotypes (see Supplementary Appendix Part 2). After proposal by a smaller team of investigators, the desiderata were evaluated and refined by all authors, which included investigators from eMERGE, PGRN, PGPop, SHARPn, PCORNet, and HMO Research Network.

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Mo H., Thompson W.K., Rasmussen L.V., Pacheco J.A., Jiang G., Kiefer R., Zhu Q., Xu J., Montague E., Carrell D.S., Lingren T., Mentch F.D., Ni Y., Wehbe F.H., Peissig P.L., Tromp G., Larson E.B., Chute C.G., Pathak J., Denny J.C., Speltz P., Kho A.N., Jarvik G.P., Bejan C.A., Williams M.S., Borthwick K., Kitchner T.E., Roden D.M, & Harris P.A. (2015). Desiderata for computable representations of electronic health records-driven phenotype algorithms. Journal of the American Medical Informatics Association : JAMIA, 22(6), 1220-1230.

Publication 2015

Atrial fibrillation Diagnostic Drug Infective endocarditis Phenotypes Populations Therapy

Corresponding Organization :

Other organizations : Vanderbilt University, NorthShore University HealthSystem, Northwestern University, Mayo Clinic in Florida, University of Maryland, Baltimore County, Kaiser Permanente Washington Health Research Institute, Cincinnati Children's Hospital Medical Center, Children's Hospital of Philadelphia, Marshfield Clinic, Stellenbosch University, Johns Hopkins University, Mayo Clinic in Arizona, University of Washington Medical Center, University of Washington, Geisinger Health System

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Variable analysis

independent variables

Phenotype algorithms of different complexity
Diagnostic criteria (e.g., Duke criteria for infective endocarditis, CHADS2 criteria for anticoagulation therapy in atrial fibrillation)

dependent variables

Ability to represent selected well-known diagnostic criteria as potential phenotypes

control variables

21 eMERGE phenotype algorithms
Authoring tools (Measure Authoring Tool, i2b2, Eureka!, PhenotypePortal, the Vanderbilt Synthetic Derivative, and the Marshfield Personalized Medicine Research Project interface)

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