Identifying heart failure using EMR-based algorithms.

ABSTRACT:

Background

Heart failure (HF) is a major clinical and public health problem, the management of which will benefit from large-scale pragmatic research that leverages electronic medical records (EMR). Requisite to using EMRs for HF research is the development of reliable algorithms to identify HF patients. We aimed to develop and validate computable phenotype algorithms to identify patients with HF using standardized data elements defined by the Patient Centered Outcomes Research Network (PCORnet) Common Data Model (CDM).

Methods

We built HF computable phenotypes utilizing the data domains of HF diagnosis codes, prescribed HF-related medications and N-terminal B-type natriuretic peptide (NT-proBNP). Algorithms were validated in a cohort (n = 76,254) drawn from Olmsted County,

SUBMITTER: Tison GH 

PROVIDER: S-EPMC6233734 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature