An analysis of Chinese nursing electronic medical records to predict violence in psychiatric inpatients using text mining and machine learning techniques.

ABSTRACT:

Background

The prevalence of violence in acute psychiatric wards is a critical concern. According to a meta-analysis investigating violence in psychiatric inpatient units, researchers estimated that approximately 17% of inpatients commit one or more acts of violence during their stay. Inpatient violence negatively affects health-care providers and patients and may contribute to high staff turnover. Therefore, predicting which psychiatric inpatients will commit violence is of considerable clinical significance.

Objective

The present study aimed to estimate the violence rate for psychiatric inpatients and establish a predictive model for violence in psychiatric inpatients.

Methods

We collected the structured and unstructured data from Chinese nursing electronic medical

SUBMITTER: Hu YH 

PROVIDER: S-EPMC10246850 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature