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Article

Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals.

Journal of the American Medical Informatics Association : JAMIA - 1 Jan 2017

Teixeira Pedro L, Wei Wei-Qi, Cronin Robert M, Mo Huan, VanHouten Jacob P, Carroll Robert J, LaRose Eric, Bastarache Lisa A, Rosenbloom S Trent, Edwards Todd L, Roden Dan M, Lasko Thomas A, Dart Richard A, Nikolai Anne M, Peissig Peggy L, Denny Joshua C

Abstract excerpt

OBJECTIVE: Phenotyping algorithms applied to electronic health record (EHR) data enable investigators to identify large cohorts for clinical and genomic research. Algorithm development is often iterative, depends on fallible investigator intuition, and is time- and labor-intensive. We developed and evaluated 4 types of phenotyping algorithms and categories of EHR information to identify hypertensive individuals...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 27497800
DOI: 10.1093/jamia/ocw071
PMCID: PMC5201185

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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