Dalton-Locke, C; Attard, R; Killaspy, H; White, S
(2018)
Predictors of quality of care in mental health supported accommodation services in England: a multiple regression modelling study.
BMC Psychiatry, 18 (1).
p. 344.
ISSN 1471-244X
https://doi.org/10.1186/s12888-018-1912-7
SGUL Authors: White, Sarah Jane
|
PDF
Published Version
Available under License Creative Commons Attribution. Download (591kB) | Preview |
|
|
PDF
Accepted Version
Available under License Creative Commons Attribution. Download (1MB) | Preview |
Abstract
BACKGROUND: Specialist mental health supported accommodation services are a key component to a graduated level of care from hospital to independently living in the community for people with complex, longer term mental health problems. However, they come at a high cost and there has been a lack of research on the quality of these services. The QuEST (Quality and Effectiveness of Supported tenancies) study, a five-year programme of research funded by the National Institute for Health Research, aimed to address this. It included the development of the first standardised quality assessment tool for supported accommodation services, the QuIRC-SA (Quality Indicator for Rehabilitative Care - Supported Accommodation). Using data collected from the QuIRC-SA, we aimed to identify potential service characteristics that were associated with quality of care. METHODS: Data collected from QuIRC-SAs with 150 individual services in England (28 residential care, 87 supported housing and 35 floating outreach) from four different sources were analysed using multiple regression modelling to investigate associations between service characteristics (local authority area index score, total beds/spaces, staffing intensity, percentage of male service users and service user ability) and areas of quality of care (Living Environment, Therapeutic Environment, Treatments and Interventions, Self-Management and Autonomy, Social Interface, Human Rights and Recovery Based Practice). RESULTS: The local authority area in which the service is located, the service size (number of beds/places) and the usual expected length of stay were each negatively associated with up to six of the seven QuIRC-SA domains. Staffing intensity was positively associated with two domains (Therapeutic Environment and Treatments and Interventions) and negatively associated with one (Human Rights). The percentage of male service users was positively associated with one domain (Treatments and Interventions) and service user ability was not associated with any of the domains. CONCLUSIONS: This study identified service characteristics associated with quality of care in specialist mental health supported accommodation services that can be used in the design and specification of services.
Item Type: | Article | ||||||
---|---|---|---|---|---|---|---|
Additional Information: | © The Author(s). 2018 Open Access This 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. | ||||||
Keywords: | Mental health, Multiple regression, Predictors of quality, Quality assessment, Quality of care, Supported accommodation, Mental health, Supported accommodation, Quality assessment, Quality of care, Predictors of quality, Multiple regression, 1103 Clinical Sciences, Psychiatry | ||||||
SGUL Research Institute / Research Centre: | Academic Structure > Population Health Research Institute (INPH) | ||||||
Journal or Publication Title: | BMC Psychiatry | ||||||
ISSN: | 1471-244X | ||||||
Language: | eng | ||||||
Dates: |
|
||||||
Publisher License: | Creative Commons: Attribution 4.0 | ||||||
PubMed ID: | 30342501 | ||||||
Web of Science ID: | WOS:000447778600001 | ||||||
Go to PubMed abstract | |||||||
URI: | https://openaccess.sgul.ac.uk/id/eprint/110295 | ||||||
Publisher's version: | https://doi.org/10.1186/s12888-018-1912-7 |
Statistics
Actions (login required)
Edit Item |