Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

Journal: Acta psychiatrica Scandinavica

PMID: 31209866

Abstract

OBJECTIVE: Mechanical restraint (MR) is used to prevent patients from harming themselves or others during inpatient treatment. The objective of this study was to investigate whether incident MR occurring in the first 3 days following admission could be predicted based on analysis of electronic health data available after the first hour of admission.

Authors

A A Danielsen

Psychosis Research Unit, Department for Psychosis, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.
M H J Fenger

Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark.
S D Østergaard

The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark.
K L Nielbo

Department of History, University of Southern Denmark, Odense, Denmark.
O Mors

Psychosis Research Unit, Department for Psychosis, Aarhus University Hospital - Psychiatry, Aarhus, Denmark.

Keywords

Case-Control Studies Denmark Early Warning Score Electronic Health Records Female Hospitalization Humans Inpatients Machine Learning Male Mental Disorders Predictive Value of Tests Restraint, Physical Self-Injurious Behavior Sensitivity and Specificity Time Factors

External Resources

View on PubMed Access via DOI PubMed (31209866)

Predicting mechanical restraint of psychiatric inpatients by applying machine learning on electronic health data.

Abstract

Authors

Keywords

External Resources

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