Coronary Artery Disease Phenotype Detection in an Academic Hospital System Setting.

ABSTRACT:

Background

The United States, and especially West Virginia, have a tremendous burden of coronary artery disease (CAD). Undiagnosed familial hypercholesterolemia (FH) is an important factor for CAD in the U.S. Identification of a CAD phenotype is an initial step to find families with FH.

Objective

We hypothesized that a CAD phenotype detection algorithm that uses discrete data elements from electronic health records (EHRs) can be validated from EHR information housed in a data repository.

Methods

We developed an algorithm to detect a CAD phenotype which searched through discrete data elements, such as diagnosis, problem lists, medical history, billing, and procedure (International Classification of Diseases [ICD]-9/10 and Current Procedural Terminology [CPT]) codes. Th

SUBMITTER: Joseph A 

PROVIDER: S-EPMC7787710 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature