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A retrospective analysis of determinants of involuntary psychiatric in-patient treatment

BACKGROUND: The purpose of our study was to identify predictors of a high risk of involuntary psychiatric in-patient treatment. METHODS: We carried out a detailed analysis of the 1773 mental health records of all the persons treated as in-patients under the PsychKG NRW (Mental Health Act for the sta...

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Autores principales: Schmitz-Buhl, Mario, Gairing, Stefanie Kristiane, Rietz, Christian, Häussermann, Peter, Zielasek, Jürgen, Gouzoulis-Mayfrank, Euphrosyne
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489329/
https://www.ncbi.nlm.nih.gov/pubmed/31035963
http://dx.doi.org/10.1186/s12888-019-2096-5
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author Schmitz-Buhl, Mario
Gairing, Stefanie Kristiane
Rietz, Christian
Häussermann, Peter
Zielasek, Jürgen
Gouzoulis-Mayfrank, Euphrosyne
author_facet Schmitz-Buhl, Mario
Gairing, Stefanie Kristiane
Rietz, Christian
Häussermann, Peter
Zielasek, Jürgen
Gouzoulis-Mayfrank, Euphrosyne
author_sort Schmitz-Buhl, Mario
collection PubMed
description BACKGROUND: The purpose of our study was to identify predictors of a high risk of involuntary psychiatric in-patient treatment. METHODS: We carried out a detailed analysis of the 1773 mental health records of all the persons treated as in-patients under the PsychKG NRW (Mental Health Act for the state of North Rhine-Westphalia, Germany) in a metropolitan region of Germany (the City of Cologne) in 2011. 3991 mental health records of voluntary in-patients from the same hospitals served as a control group. We extracted medical, sociodemographic and socioeconomic data from these records. Apart from descriptive statistics, we used a prediction model employing chi-squared automatic interaction detection (CHAID). RESULTS: Among involuntary patients, organic mental disorders (ICD10: F0) and schizophrenia and other psychotic disorders (ICD10: F2) were overrepresented. Patients treated as in-patients against their will were on average older, they were more often retired and had a migratory background. The Exhaustive CHAID analysis confirmed the main diagnosis to be the strongest predictor of involuntary in-patient psychiatric treatment. Other predictors were the absence of outpatient treatment prior to admission, admission outside of regular service hours and migratory background. The highest risk of involuntary treatment was associated with patients with organic mental disorders (ICD 10: F0) who were married or widowed and patients with non-organic psychotic disorders (ICD10: F2) or mental retardation (ICD10: F7) in combination with a migratory background. Also, referrals from general hospitals were frequently encountered. CONCLUSIONS: We identified modifiable risk factors for involuntary psychiatric in-patient treatment. This implies that preventive measures may be feasible and should be implemented to reduce the rate of involuntary psychiatric in-patient treatment. This may include efforts to establish crisis resolution teams to improve out-patient treatment, train general hospital staff in deescalation techniques, and develop special programs for patients with a migratory background.
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spelling pubmed-64893292019-06-04 A retrospective analysis of determinants of involuntary psychiatric in-patient treatment Schmitz-Buhl, Mario Gairing, Stefanie Kristiane Rietz, Christian Häussermann, Peter Zielasek, Jürgen Gouzoulis-Mayfrank, Euphrosyne BMC Psychiatry Research Article BACKGROUND: The purpose of our study was to identify predictors of a high risk of involuntary psychiatric in-patient treatment. METHODS: We carried out a detailed analysis of the 1773 mental health records of all the persons treated as in-patients under the PsychKG NRW (Mental Health Act for the state of North Rhine-Westphalia, Germany) in a metropolitan region of Germany (the City of Cologne) in 2011. 3991 mental health records of voluntary in-patients from the same hospitals served as a control group. We extracted medical, sociodemographic and socioeconomic data from these records. Apart from descriptive statistics, we used a prediction model employing chi-squared automatic interaction detection (CHAID). RESULTS: Among involuntary patients, organic mental disorders (ICD10: F0) and schizophrenia and other psychotic disorders (ICD10: F2) were overrepresented. Patients treated as in-patients against their will were on average older, they were more often retired and had a migratory background. The Exhaustive CHAID analysis confirmed the main diagnosis to be the strongest predictor of involuntary in-patient psychiatric treatment. Other predictors were the absence of outpatient treatment prior to admission, admission outside of regular service hours and migratory background. The highest risk of involuntary treatment was associated with patients with organic mental disorders (ICD 10: F0) who were married or widowed and patients with non-organic psychotic disorders (ICD10: F2) or mental retardation (ICD10: F7) in combination with a migratory background. Also, referrals from general hospitals were frequently encountered. CONCLUSIONS: We identified modifiable risk factors for involuntary psychiatric in-patient treatment. This implies that preventive measures may be feasible and should be implemented to reduce the rate of involuntary psychiatric in-patient treatment. This may include efforts to establish crisis resolution teams to improve out-patient treatment, train general hospital staff in deescalation techniques, and develop special programs for patients with a migratory background. BioMed Central 2019-04-29 /pmc/articles/PMC6489329/ /pubmed/31035963 http://dx.doi.org/10.1186/s12888-019-2096-5 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Schmitz-Buhl, Mario
Gairing, Stefanie Kristiane
Rietz, Christian
Häussermann, Peter
Zielasek, Jürgen
Gouzoulis-Mayfrank, Euphrosyne
A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title_full A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title_fullStr A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title_full_unstemmed A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title_short A retrospective analysis of determinants of involuntary psychiatric in-patient treatment
title_sort retrospective analysis of determinants of involuntary psychiatric in-patient treatment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6489329/
https://www.ncbi.nlm.nih.gov/pubmed/31035963
http://dx.doi.org/10.1186/s12888-019-2096-5
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