Using natural language processing to classify social work interventions.

ABSTRACT:

Objectives

Health care organizations are increasingly employing social workers to address patients' social needs. However, social work (SW) activities in health care settings are largely captured as text data within electronic health records (EHRs), making measurement and analysis difficult. This study aims to extract and classify, from EHR notes, interventions intended to address patients' social needs using natural language processing (NLP) and machine learning (ML) algorithms.

Study design

Secondary data analysis of a longitudinal cohort.

Methods

We extracted 815 SW encounter notes from the EHR system of a federally qualified health center. We reviewed the literature to derive a 10-category classification scheme for SW interventions. We applied NLP and ML algorithm

SUBMITTER: Bako AT 

PROVIDER: S-EPMC8005360 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature