Evaluating the effects of Community Treatment Orders (CTOs) in England using the Mental Health Services Dataset (MHSDS): protocol for a national, population-based study
Evaluating the effects of Community Treatment Orders (CTOs) in England using the Mental Health Services Dataset (MHSDS): protocol for a national, population-based study
Introduction: supervised Community Treatment (SCT) for people with serious mental disorders has become accepted practice in many countries around the world. In England, SCT was adopted in 2008 in the form of Community Treatment Orders (CTOs). CTOs have been used more than expected, with significant variations between people and places. There is conflicting evidence about the effectiveness of SCT; studies based on randomised controlled trials (RCTs) have suggested few positive impacts, while those employing observational designs have been more favourable. Robust population-based studies are needed, because of the ethical challenges of undertaking further RCTs and because variation across previous studies may reflect the effects of socio-spatial context on SCT outcomes. We aim to examine spatial and temporal variation in the use, effectiveness and cost of CTOs in England through the analysis of routine administrative data.
Methods and analysis: four years of data from the Mental Health Services Dataset (MHSDS) will be analysed using multilevel models (MMs). Models based on all patients eligible for CTOs will be used to explore variation in their use. A subset of CTO-eligible patients comprising a treatment group (CTO-patients) and a matched control group (non-CTO patients) will be used to examine variation in the association between CTO use and study outcomes. Primary outcome will be total time in hospital. Secondary outcomes will include time to first re-admission and mortality. Outputs from these models will be used to populate predictive models of health care resource use.
Ethics and dissemination: ethical approval has been granted by the NHS Data Access and Advisory Group and Warwick University. To ensure patient confidentiality and to meet data governance requirements, analyses will be carried out in a secure micro-data laboratory using de-identified data. Study findings will be disseminated through academic channels and shared with mental health policy makers and other stakeholders.
Community treatment orders; Supervised community treatment; Community mental health
Weich, Scott
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Duncan, Craig
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Bhui, Kamaldeep
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Canaway, Alastair
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Crepaz-Keay, David
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Keown, Patrick
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Madan, Jason
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McBride, Orla
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Moon, Graham
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Parsons, Helen
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Singh, Swaran
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Twigg, Liz
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Weich, Scott
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Duncan, Craig
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Bhui, Kamaldeep
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Canaway, Alastair
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Crepaz-Keay, David
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Keown, Patrick
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Madan, Jason
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McBride, Orla
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Moon, Graham
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Parsons, Helen
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Singh, Swaran
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Twigg, Liz
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Weich, Scott, Duncan, Craig, Bhui, Kamaldeep, Canaway, Alastair, Crepaz-Keay, David, Keown, Patrick, Madan, Jason, McBride, Orla, Moon, Graham, Parsons, Helen, Singh, Swaran and Twigg, Liz
(2018)
Evaluating the effects of Community Treatment Orders (CTOs) in England using the Mental Health Services Dataset (MHSDS): protocol for a national, population-based study.
BMJ Open.
(In Press)
Abstract
Introduction: supervised Community Treatment (SCT) for people with serious mental disorders has become accepted practice in many countries around the world. In England, SCT was adopted in 2008 in the form of Community Treatment Orders (CTOs). CTOs have been used more than expected, with significant variations between people and places. There is conflicting evidence about the effectiveness of SCT; studies based on randomised controlled trials (RCTs) have suggested few positive impacts, while those employing observational designs have been more favourable. Robust population-based studies are needed, because of the ethical challenges of undertaking further RCTs and because variation across previous studies may reflect the effects of socio-spatial context on SCT outcomes. We aim to examine spatial and temporal variation in the use, effectiveness and cost of CTOs in England through the analysis of routine administrative data.
Methods and analysis: four years of data from the Mental Health Services Dataset (MHSDS) will be analysed using multilevel models (MMs). Models based on all patients eligible for CTOs will be used to explore variation in their use. A subset of CTO-eligible patients comprising a treatment group (CTO-patients) and a matched control group (non-CTO patients) will be used to examine variation in the association between CTO use and study outcomes. Primary outcome will be total time in hospital. Secondary outcomes will include time to first re-admission and mortality. Outputs from these models will be used to populate predictive models of health care resource use.
Ethics and dissemination: ethical approval has been granted by the NHS Data Access and Advisory Group and Warwick University. To ensure patient confidentiality and to meet data governance requirements, analyses will be carried out in a secure micro-data laboratory using de-identified data. Study findings will be disseminated through academic channels and shared with mental health policy makers and other stakeholders.
Text
CTO Protocol Paper - Main Text v4.0 - BMJOpenclean copy
- Accepted Manuscript
More information
Accepted/In Press date: 18 August 2018
Keywords:
Community treatment orders; Supervised community treatment; Community mental health
Identifiers
Local EPrints ID: 424206
URI: http://eprints.soton.ac.uk/id/eprint/424206
ISSN: 2044-6055
PURE UUID: d15bafc9-126c-4a36-b4e6-2167acc8244f
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Date deposited: 05 Oct 2018 11:34
Last modified: 16 Mar 2024 03:53
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Contributors
Author:
Scott Weich
Author:
Craig Duncan
Author:
Kamaldeep Bhui
Author:
Alastair Canaway
Author:
David Crepaz-Keay
Author:
Patrick Keown
Author:
Jason Madan
Author:
Orla McBride
Author:
Helen Parsons
Author:
Swaran Singh
Author:
Liz Twigg
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