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      Long-term clinical and cost-effectiveness of collaborative care (versus usual care) for people with mental–physical multimorbidity: cluster-randomised trial

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          Abstract

          Background

          Collaborative care can support the treatment of depression in people with long-term conditions, but long-term benefits and costs are unknown.

          Aims

          To explore the long-term (24-month) effectiveness and cost-effectiveness of collaborative care in people with mental-physical multimorbidity.

          Method

          A cluster randomised trial compared collaborative care (integrated physical and mental healthcare) with usual care for depression alongside diabetes and/or coronary heart disease. Depression symptoms were measured by the symptom checklist-depression scale (SCL-D13). The economic evaluation was from the perspective of the English National Health Service.

          Results

          191 participants were allocated to collaborative care and 196 to usual care. At 24 months, the mean SCL-D13 score was 0.27 (95% CI, −0.48 to −0.06) lower in the collaborative care group alongside a gain of 0.14 (95% CI, 0.06-0.21) quality-adjusted life-years (QALYs). The cost per QALY gained was £13 069.

          Conclusions

          In the long term, collaborative care reduces depression and is potentially cost-effective at internationally accepted willingness-to-pay thresholds.

          Declaration of interest

          None.

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          Most cited references12

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          Confirmation of the dimensional structure of the scl-90: A study in construct validation

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            Minimization--reducing predictability for multi-centre trials whilst retaining balance within centre.

            Minimization is often used to assign patients to treatment groups to ensure good balance in patient numbers within centre and other prognostic factors. Balance within centre is preferable since large imbalances between treatment arms may have logistical implications for centres, such as cost and resource implications. However, recent concern over high predictability of treatment allocation by centres when using minimization has caused this method to be questioned. We used data from current clinical trials to assess predictability and summarize subsequent within-centre imbalances with the aim of finding the most effective minimization method for reducing predictability whilst still retaining sufficient balance within centre, when randomization is to one of two treatments. We compared prediction rates and imbalances for deterministic minimization, and minimization incorporating various random elements, p (p=0.95,0.90,0.80,0.75,0.70). We also compared prediction rates and imbalance when centre was and was not included as a stratification factor. Incorporating a random element proved successful in reducing prediction rates whilst minimizing the inevitable increase in within-centre imbalance, whereas excluding centre as a stratification factor incurred major within-centre imbalance. We therefore suggest that minimization can still be used, and that centre can be included as a stratification factor, but a random element has to be incorporated into the minimization algorithm. Minimization incorporating a random element of 0.80 is the most efficient method to use based upon the simulations undertaken in this study of real clinical trial data using different probabilities of allocation. Copyright 2005 John Wiley & Sons, Ltd.
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              Does depression predict the use of urgent and unscheduled care by people with long term conditions? A systematic review with meta-analysis.

              Factors that drive the use of urgent healthcare among people with chronic physical illness (i.e. long term conditions-LTCs) are poorly understood. We conducted a systematic review with meta analysis to examine the strength of association between depression and subsequent use of urgent healthcare among people with LTCs. Electronic searches of MEDLINE, EMBASE, PSYCINFO, CINAHL, the British Nursing Library and the Cochrane Library 2011 were conducted, supplemented by hand-searching bibliographies, citation tracing eligible studies and asking experts about relevant studies. Studies were eligible for inclusion if they: i)used prospective cohort design, ii)included patients with diabetes, asthma, chronic obstructive pulmonary disease or coronary heart disease, iii)used a standardised measure of depression, and iv)assessed urgent healthcare utilisation prospectively. Data on the subjects recruited, methods used and the association between depression and subsequent urgent healthcare utilisation were extracted from eligible studies. Odds ratios (ORs) were calculated for each study and pooled using random effects models. 16 independent studies were identified. Pooled effects indicated that depression was associated with a 49% increase in the odds of urgent healthcare utilisation (OR=1.49, p<.0005). This effect was not significantly affected by publication bias or inclusion of studies of low quality. Effects were much smaller and non-significant among the 3 studies that controlled for other covariates, including severity of illness (OR=1.13, p=.31). Depression was associated with increased urgent healthcare use, but not in the minority of studies that controlled for other covariates. This possibly suggests confounding, but the severity measures may themselves have been influenced by depression. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Br J Psychiatry
                Br J Psychiatry
                BJP
                The British Journal of Psychiatry
                Cambridge University Press (Cambridge, UK )
                0007-1250
                1472-1465
                August 2018
                August 2018
                : 213
                : 2
                : 456-463
                Affiliations
                [1 ]Division of Population Health, Health Services Research, and Primary Care, The University of Manchester , UK
                [2 ]NIHR School for Primary Care Research, The University of Manchester , Manchester Academic Health Science Centre, UK
                [3 ]Primary Care & Health Sciences, University of Keele , UK, Division of Population Health, Health Services Research, and Primary Care, The University of Manchester , UK and NIHR Collaboration for Leadership in Applied Health Research and Care West Midlands, UK
                [4 ]NHS Health Education North West , Manchester, UK
                [5 ]Division of Population Health, Health Services Research, and Primary Care, The University of Manchester , UK
                [6 ]Mental Health Research Group, University of Exeter , UK
                [7 ]Division of Nursing, Midwifery and Social Work, The University of Manchester , Manchester Academic Health Science Centre, UK
                [8 ]Division of Population Health, Health Services Research, and Primary Care, The University of Manchester , UK
                [9 ]The Psychometrics Centre, University of Cambridge , UK and Division of Population Health, Health Services Research, and Primary Care, The University of Manchester , UK
                [10 ]Department of Health Sciences, University of York , UK and Centre for Reviews and Dissemination, University of York , UK.
                Author notes
                Correspondence: Elizabeth M. Camacho, PhD, Centre for Health Economics, Division of Population Health, Health Services Research, and Primary Care, School of Health Sciences, The University of Manchester , Jean McFarlane Building, Oxford Road, Manchester, M13 9PL, UK. Email: elizabeth.camacho@ 123456manchester.ac.uk
                Author information
                https://orcid.org/0000-0003-0625-3829
                Article
                S0007125018000703 00070
                10.1192/bjp.2018.70
                6429252
                29761751
                87d9d0b2-d90b-44f9-94bb-4dac96474de8
                © The Royal College of Psychiatrists 2018

                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 in any medium, provided the original work is properly cited.

                History
                : 23 January 2018
                : 23 February 2018
                : 14 March 2018
                Page count
                Figures: 1, Tables: 3, References: 28, Pages: 8
                Categories
                Paper

                Clinical Psychology & Psychiatry
                Clinical Psychology & Psychiatry

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