Open AccessUsing natural language processing to classify social work interventions
Author(s) -
Abdulaziz T Bako,
H Taylor,
Kevin Wiley,
Jiaping Zheng,
Heather A. Walter-McCabe,
Suranga Nath Kasthurirathne,
Joshua R. Vest
Publication year - 2021
Publication title -
the american journal of managed care
Language(s) - English
Resource type - Journals
eISSN - 1936-2692
pISSN - 1088-0224
DOI - 10.37765/ajmc.2021.88580
Subject(s) - medicine , psychological intervention , work (physics) , natural language processing , nursing , mechanical engineering , engineering , computer science
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.