Medicine and Health

Natural language processing of multi-hospital electronic health records for public health surveillance of suicidality

R. Bey, A. Cohen, et al.

This study by Romain Bey, Ariel Cohen, and colleagues unveils concerning trends in suicidality among youth by analyzing over 2.9 million electronic health records from Parisian hospitals. It highlights a significant post-pandemic rise in suicide attempts, particularly among adolescent girls, calling for heightened awareness and action regarding mental health.

00:00

Playback language: English

Index

Abstract

This study developed and validated suicidality surveillance indicators using NLP on electronic health records (EHRs) from 15 Parisian hospitals. Analyzing 2,911,920 records, an interrupted time-series analysis revealed a post-pandemic increase in suicide attempts, particularly among girls aged 8–17. The study demonstrates the feasibility of jointly analyzing multi-hospital EHR data for timely population-level mental health monitoring, highlighting the need for increased attention to violence against women, especially at young ages.

Publisher

npj Mental Health Research

Published On

Feb 14, 2024

Authors

Romain Bey, Ariel Cohen, Vincent Trebossen, Basile Dura, Pierre-Alexis Geoffroy, Charline Jean, Benjamin Landman, Thomas Petit-Jean, Gilles Chillet, Kanoko Sallah, Xavier Tannier, Aurelie Bourmaud, Richard Delorme

Related Publications

Explore these studies to deepen your understanding of the subject.

Computer Science

Generation and evaluation of artificial mental health records for Natural Language Processing

J. Ive, N. Viani, et al.

Medicine and Health

Natural language processing system for rapid detection and intervention of mental health crisis chat messages

A. Swaminathan, I. López, et al.

Medicine and Health

Cohort design and natural language processing to reduce bias in electronic health records research

S. Khurshid, C. Reeder, et al.

Medicine and Health

Efficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: A Comparative Analysis and Validation Study

H. Chen, M. Alfred, et al.

Listen, Learn & Level Up

Over 10,000 hours of research content in 25+ fields, available in 12+ languages.

No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.

listen to research audio papers with researchbunny