Ascertaining Framingham heart failure phenotype from inpatient electronic health record data using natural language processing: a multicentre Atherosclerosis Risk in Communities (ARIC) validation study.

ABSTRACT:

Objectives

Using free-text clinical notes and reports from hospitalised patients, determine the performance of natural language processing (NLP) ascertainment of Framingham heart failure (HF) criteria and phenotype.

Study design

A retrospective observational study design of patients hospitalised in 2015 from four hospitals participating in the Atherosclerosis Risk in Communities (ARIC) study was used to determine NLP performance in the ascertainment of Framingham HF criteria and phenotype.

Setting

Four ARIC study hospitals, each representing an ARIC study region in the USA.

Participants

A stratified random sample of hospitalisations identified using a broad range of International Classification of Disease, ninth revision, diagnostic codes indicative of an HF ev

SUBMITTER: Moore CR 

PROVIDER: S-EPMC8204176 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature