Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure.

ABSTRACT:

Importance

Serial functional status assessments are critical to heart failure (HF) management but are often described narratively in documentation, limiting their use in quality improvement or patient selection for clinical trials.

Objective

To develop and validate a deep learning natural language processing (NLP) strategy for extracting functional status assessments from unstructured clinical documentation.

Design, setting, and participants

This diagnostic study used electronic health record data collected from January 1, 2013, through June 30, 2022, from patients diagnosed with HF seeking outpatient care within 3 large practice networks in Connecticut (Yale New Haven Hospital [YNHH], Northeast Medical Group [NMG], and Greenwich Hospital [GH]). Expert-annotated notes

SUBMITTER: Adejumo P 

PROVIDER: S-EPMC11544492 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature