Using machine learning to mine mental health diagnostic groups from emergency department presentations before and during the COVID-19 pandemic.

ABSTRACT:

Purpose

The COVID-19 pandemic had a profound negative effect on mental health worldwide. The hospital emergency department plays a pivotal role in responding to mental health crises. Understanding data trends relating to hospital emergency department usage is beneficial for service planning, particularly around preparing for future pandemics. Machine learning has been used to mine large volumes of unstructured data to extract meaningful data in relation to mental health presentations. This study aims to analyse trends in five mental health-related presentations to an emergency department before and during, the COVID-19 pandemic.

Methods

Data from 690,514 presentations to two Australian, public hospital emergency departments between April 2019 to February 2022 were assessed.

SUBMITTER: Hudson C 

PROVIDER: S-EPMC10628018 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature