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Prevalence and predictors of involuntary psychiatric hospital admissions in Ontario, Canada: a population-based linked administrative database study

Published online by Cambridge University Press:  22 February 2018

Michael Lebenbaum*
Affiliation:
Epidemiologist, Mental Health and Addictions Program, ICES, and PhD student, IHPME, University of Toronto, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5
Maria Chiu
Affiliation:
Staff Scientist, Mental Health and Addictions Program, ICES, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5
Simone Vigod
Affiliation:
Scientist, Women's College Research Institute, Assistant Professor, IHPME, University of Toronto
Paul Kurdyak
Affiliation:
Director of Health Outcomes and Performance Evaluation (HOPE), CAMH, 250 College Street, Toronto, ON M5T 1R8, Program Lead, Mental Health & Addictions Research Program, ICES, Associate Professor, IHPME, University of Toronto.
*
Correspondence: Michael Lebenbaum, Mental Health and Addictions Program, ICES, G-106, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada. Email: michael.lebenbaum@ices.on.ca
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Abstract

Background

Involuntary admissions to psychiatric hospitals are common; however, research examining the trends in prevalence over time and predictors is limited.

Aims

To examine trends in prevalence and risk factors for involuntary admissions in Ontario, Canada.

Method

We conducted an analysis of all mental health bed admissions from 2009 to 2013 and assessed the association between patient sociodemographics, service utilisation, pathway to care and severity characteristics for involuntary admissions using a modified Poisson regression.

Results

We found a high and increasing prevalence of involuntary admissions (70.7% in 2009, 77.1% in 2013, 74.1% overall). Individuals with police contact in the prior week (risk ratio (RR) = 1.20) and immigrants both experienced greater likelihood of being involuntarily admitted, regardless of control for other characteristics (RR = 1.07) (both P < 0.0001).

Conclusions

We identified numerous modifiable and non-modifiable risk factors for involuntary admissions. The prevalence of involuntary admissions was high, linearly increasing over time.

Declaration of interest

The authors have completed the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported. This study was conducted using funding entirely from public sources. P.K. has received operational support via an Ontario Ministry of Health and Long-Term Care (MOHLTC) Health Services Research Fund Capacity Award to support this project. The Institute for Clinical Evaluative Sciences (ICES) is funded by the Ontario MOHLTC. The study results and conclusions are those of the authors, and should not be attributed to any of the funding agencies or sponsoring agencies. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. All decisions regarding study design, publication, and data analysis were made independent of the funding agencies.

Information

Type
Papers
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
Copyright © The Royal College of Psychiatrists 2018
Figure 0

Fig. 1 Trends over time in the prevalence of involuntary admissions within Ontario, Canada.

Figure 1

Table 1 Descriptive characteristics for patients who are involuntary or voluntary at admission

Figure 2

Table 2 Breakdown of patient characteristics by involuntary status, and unadjusted and multivariable logistic regression of association between each characteristics and involuntary status

Figure 3

Fig. 2 Forest plot of unadjusted and fully adjusted associations between clinical rating scales and involuntary admissions (all included continuously).

a. Risk ratios, RR (95% confidence intervals) are from Poisson regression models without adjustment for other risk factors. b. Risk ratios, RR (95% confidence intervals) are from Poisson regression models with adjustment for all other risk factors.
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