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PheKB: a catalog and workflow for creating electronic phenotype algorithms for transportability
Author(s) -
Jacqueline Kirby,
Peter Speltz,
Luke V. Rasmussen,
Melissa Basford,
Omri Gottesman,
Peggy Peissig,
Jennifer A. Pacheco,
Gerard Tromp,
Jyotishman Pathak,
David Carrell,
Stephen B. Ellis,
Todd Lingren,
Will K Thompson,
Guergana Savova,
Jonathan L. Haines,
Dan M. Roden,
Paul A. Harris,
Joshua C. Denny
Publication year - 2016
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocv202
Subject(s) - workflow , computer science , algorithm , electronic health record , health care , machine learning , data mining , database , economics , economic growth
Health care generated data have become an important source for clinical and genomic research. Often, investigators create and iteratively refine phenotype algorithms to achieve high positive predictive values (PPVs) or sensitivity, thereby identifying valid cases and controls. These algorithms achieve the greatest utility when validated and shared by multiple health care systems.Materials and Methods We report the current status and impact of the Phenotype KnowledgeBase (PheKB, http://phekb.org), an online environment supporting the workflow of building, sharing, and validating electronic phenotype algorithms. We analyze the most frequent components used in algorithms and their performance at authoring institutions and secondary implementation sites.

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