Using natural language processing to classify social work interventions | Zendy

Heather McCabe | Zendy

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Using natural language processing to classify social work interventions

Author(s) -

Heather McCabe

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) - work (physics) , psychological intervention , computer science , natural language processing , natural (archaeology) , linguistics , artificial intelligence , psychology , history , engineering , mechanical engineering , philosophy , archaeology , psychiatry

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.

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