Predictors of nonfatal suicide attempts within 30 days of discharge from psychiatric hospitalization: Sex-specific models developed using population-based registries

• Published in: Journal of affective disorders Vol. 306; pp. 260 - 268
• Main Authors: Zelkowitz, Rachel L., Jiang, Tammy, Horváth-Puhó, Erzsébet, Street, Amy E., Lash, Timothy L., Sørensen, Henrik T., Rosellini, Anthony J., Gradus, Jaimie L.
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.06.2022
• Subjects: Administrative health records; Case-cohort study; Depressive Disorder, Major - epidemiology; Female; Hospitalization; Humans; Machine learning; Male; Mental Disorders - epidemiology; Mental Disorders - psychology; Patient Discharge; Psychiatric hospitalization; Psychiatric/Mental Health; Registries; Risk Factors; Substance-Related Disorders - epidemiology; Suicide attempt; Suicide, Attempted - psychology; Case-cohort study; Administrative health records; Psychiatric hospitalization; Machine learning; Suicide attempt
• ISSN: 0165-0327; 1573-2517; 1573-2517
• DOI: 10.1016/j.jad.2022.03.034

Risk for nonfatal suicide attempts is heightened in the month after psychiatric hospitalization discharge. Investigations of factors associated with such attempts are limited. We conducted a case-subcohort study using data from Danish medical, administrative, and social registries to develop sex-specific risk models using two machine learning methods: classification trees and random forests. Cases included individuals who received a diagnostic code for a nonfatal suicide attempt within 30 days of discharge following a psychiatric hospitalization between January 1, 1995 and December 31, 2015 (n = 3166, 56.5% female). The comparison subcohort consisted of a 5% random sample of individuals living in Denmark (n = 24,559, 51.3% female) on January 1, 1995 who had a psychiatric hospitalization during the study period. Histories of self-poisoning, substance-related disorders, and eating disorders were important predictors of nonfatal suicide attempt among women, with notable interactions observed between age, self-poisoning history, and other characteristics (e.g., medication use). Self-poisoning, substance-related disorders, and severe stress reactions were among the most important variables for men, with key interactions noted between self-poisoning history, age, major depressive disorder diagnosis, and prescription classes. Findings are based on Danish administrative data, which may be subject to inaccuracies, missingness, etc. It is unclear whether results would generalize to other populations. Markers of behavioral dysregulation were important predictors of nonfatal suicide attempts in the 30 days after psychiatric hospitalization discharge for both sexes. Examining risk markers for nonfatal suicide attempt following discharge is important to enhance support for this vulnerable population. •Suicide attempt risk is heightened after discharge from psychiatric hospitalization.•There has been limited research on factors associated with risk of nonfatal suicide attempts.•Sex-specific risk markers for nonfatal suicide attempts in the 30 days following psychiatric hospitalization were identified using machine learning algorithms applied to Danish population-wide administrative datasets.•Diagnoses associated with behavioral dysregulation were linked to nonfatal suicide attempts.