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

ABSTRACT:

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 and controls and provide a portable module for implementation at other sites.

Materials and methods

We reviewed the EHRs of 631 individuals followed at Vanderbilt for hypertension status. We developed features and phenotyping algorithms of increasing complexity. Input categories included International Classification of Diseases, Ninth Revision (ICD9) codes, medications

SUBMITTER: Teixeira PL 

PROVIDER: S-EPMC5201185 | biostudies-literature | 2017 Jan

REPOSITORIES: biostudies-literature