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Homelessness and associated factors over a 13-year period among psychiatric in-patients in Berlin, Germany: routine data analysis

Published online by Cambridge University Press:  29 June 2023

Dario Jalilzadeh Masah*
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
Meryam Schouler-Ocak
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
Stefan Gutwinski
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
Kirsten Gehrenbeck
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
Karl Deutscher
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
Daniel Schindel
Affiliation:
Institute for Medical Sociology and Rehabilitation Science, Charité – Universitätsmedizin Berlin, Berlin, Germany
Sonia Lech
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany; and Institute for Medical Sociology and Rehabilitation Science, Charité – Universitätsmedizin Berlin, Berlin, Germany
Stefanie Schreiter
Affiliation:
Department of Psychiatry and Neurosciences, Charité Campus Mitte, Charité – Universitätsmedizin Berlin, Berlin, Germany
*
Correspondence: Dario Jalilzadeh Masah. Email: dario.jalilzadeh-masah@charite.de
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Abstract

Background

Homeless patients in psychiatric hospitals are a scarcely studied and there is lack of knowledge about factors associated with homelessness and in-patient treatment.

Aims

To determine the change over time in the number of homeless psychiatric in-patients and to examine factors associated with homelessness.

Method

Retrospective data analysis of 1205 selected electronic patient files on psychiatric in-patient treatment in a university psychiatric hospital in Berlin, Germany. The rate of patients experiencing homelessness over a 13-year period (2008–2021) and the sociodemographic and clinical factors associated with homelessness are analysed over time.

Results

Our study revealed a 15.1% increase in the rate of homeless psychiatric in-patients over the 13-year period. Of the whole sample, 69.3% people lived in secure private housing, 15.5% were homeless and 15.1% were housed in sociotherapeutic facilities. Homelessness was significantly associated with being male (OR = 1.76 (95% CI 1.12–2.76), born outside of Germany (OR = 2.22, 95% CI 1.47–3.34), lack of out-patient treatment (OR = 5.19, 95% CI 3.35–7.63), psychotic disorders (OR = 2.46, 95% CI 1.16–5.18), reaction to severe stress (OR = 4.19, 95% CI 1.71–10.24), personality disorders (OR = 4.98, 95% CI 1.92–12.91), drug dependency (OR = 3.47, 95% CI 1.5–8.0) and alcohol dependency (OR = 3.57, 95% CI 1.67–7.62).

Conclusions

The psychiatric care system is facing an increasing number of patients in precarious social situations. This should be considered in resource allocation planning in healthcare. Individual solutions for aftercare, along with supported housing, could counteract this trend.

Information

Type
Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of the Royal College of Psychiatrists
Figure 0

Fig. 1 Flow chart showing the clustering process for participants’ housing status.

Figure 1

Fig. 2 Rates of homelessness among psychiatric in-patients from 2008 to 2021.

Figure 2

Table 1 Demographic and clinical parameters for the three housing groups (n = 1203)

Figure 3

Table 2 Predictors of homelessness in the study population (n = 1021): multivariable binary logistic regression model

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