Citation

Chattopadhyay I. JAMA Netw. Open 2023; 6(3): e233086.

Copyright

(Copyright © 2023, American Medical Association)

DOI

10.1001/jamanetworkopen.2023.3086

PMID

36920398

Abstract

The article by Mitra et al1 provides a novel approach for measuring social determinants of health (SDOHs) in the context of determining risk factors for suicidality among US military veterans. The authors found that SDOHs extracted automatically from clinical notes included in the electronic health record (EHR) of past medical encounters via a natural language processing (NLP) algorithm can efficiently capture the association with death by suicides and can measurably enhance SDOHs obtained from structured EHR data. Importantly, the results show that the NLP-extracted SDOHs have a higher degree of association compared with those obtained from structured data, suggesting that we might be able to efficiently identify at-risk individuals even when structured data on the relevant variables are missing or incomplete. ...

Language: en

Keywords

*Suicide; *Veterans; Humans; Social Determinants of Health; Social Factors; Suicidal Ideation