Using machine learning to predict suicide in the 30 days after discharge from psychiatric hospital in Denmark.

ABSTRACT:

Background

Suicide risk is high in the 30 days after discharge from psychiatric hospital, but knowledge of the profiles of high-risk patients remains limited.

Aims

To examine sex-specific risk profiles for suicide in the 30 days after discharge from psychiatric hospital, using machine learning and Danish registry data.

Method

We conducted a case-cohort study capturing all suicide cases occurring in the 30 days after psychiatric hospital discharge in Denmark from 1 January 1995 to 31 December 2015 (n = 1205). The comparison subcohort was a 5% random sample of all persons born or residing in Denmark on 1 January 1995, and who had a first psychiatric hospital admission between 1995 and 2015 (n = 24 559). Predictors included diagnoses, surgeries, prescribed medications an

SUBMITTER: Jiang T 

PROVIDER: S-EPMC8457342 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature