Applying natural language processing to understand symptoms among older adult home healthcare patients with urinary incontinence.

ABSTRACT:

Introduction

Little is known about the range and frequency of symptoms among older adult home healthcare patients with urinary incontinence, as this information is predominantly contained in clinical notes. Natural language processing can uncover symptom information among older adults with urinary incontinence to promote holistic, equitable care.

Design

We conducted a secondary analysis of cross-sectional data collected between January 1, 2015, and December 31, 2017, from the largest HHC agency in the Northeastern United States. We aimed to develop and test a natural language processing algorithm to extract symptom information from clinical notes for older adults with urinary incontinence and analyze differences in symptom documentation by race or ethnicity.

Methods

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SUBMITTER: Scharp D 

PROVIDER: S-EPMC11772115 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature