Automated Identification of Patients' Unmet Social Needs in Clinical Text Using Natural Language Processing.

ABSTRACT:

Objective

To develop natural language processing (NLP) solutions for identifying patients' unmet social needs to enable timely intervention.

Patients and methods

Design: A retrospective cohort study with review and annotation of clinical notes to identify unmet social needs, followed by using the annotations to develop and evaluate NLP solutions.

Participants

A total of 1103 primary care patients seen at a large academic medical center from June 1, 2019, to May 31, 2021 and referred to a community health worker (CHW) program. Clinical notes and portal messages of 200 age and sex-stratified patients were sampled for annotation of unmet social needs.

Systems

Two NLP solutions were developed and compared. The first solution employed similarity-based classification

SUBMITTER: Moon S 

PROVIDER: S-EPMC11423779 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature