Cargando…
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...
Autores principales: | , , , , , |
---|---|
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 |
_version_ | 1783414803485687808 |
---|---|
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. |
format | Online Article Text |
id | pubmed-6489329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT schmitzbuhlmario aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT gairingstefaniekristiane aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT rietzchristian aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT haussermannpeter aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT zielasekjurgen aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT gouzoulismayfrankeuphrosyne aretrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT schmitzbuhlmario retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT gairingstefaniekristiane retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT rietzchristian retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT haussermannpeter retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT zielasekjurgen retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment AT gouzoulismayfrankeuphrosyne retrospectiveanalysisofdeterminantsofinvoluntarypsychiatricinpatienttreatment |