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BackgroundCollaborative care is a complex intervention based on chronic disease management models and is effective in the management of depression. However, there is still uncertainty about which components of collaborative care are effective. We used meta-regression to identify factors in collaborative care associated with improvement in patient outcomes (depressive symptoms) and the process of care (use of anti-depressant medication).Methods and FindingsSystematic review with meta-regression. The Cochrane Collaboration Depression, Anxiety and Neurosis Group trials registers were searched from inception to 9th February 2012. An update was run in the CENTRAL trials database on 29th December 2013. Inclusion criteria were: randomised controlled trials of collaborative care for adults ≥18 years with a primary diagnosis of depression or mixed anxiety and depressive disorder. Random effects meta-regression was used to estimate regression coefficients with 95% confidence intervals (CIs) between study level covariates and depressive symptoms and relative risk (95% CI) and anti-depressant use. The association between anti-depressant use and improvement in depression was also explored. Seventy four trials were identified (85 comparisons, across 21,345 participants). Collaborative care that included psychological interventions predicted improvement in depression (β coefficient −0.11, 95% CI −0.20 to −0.01, p = 0.03). Systematic identification of patients (relative risk 1.43, 95% CI 1.12 to 1.81, p = 0.004) and the presence of a chronic physical condition (relative risk 1.32, 95% CI 1.05 to 1.65, p = 0.02) predicted use of anti-depressant medication.ConclusionTrials of collaborative care that included psychological treatment, with or without anti-depressant medication, appeared to improve depression more than those without psychological treatment. Trials that used systematic methods to identify patients with depression and also trials that included patients with a chronic physical condition reported improved use of anti-depressant medication. However, these findings are limited by the observational nature of meta-regression, incomplete data reporting, and the use of study aggregates.

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BackgroundThere is a considerable evidence base for 'collaborative care' as a method to improve quality of care for depression, but an acknowledged gap between efficacy and implementation. This study utilises the Normalisation Process Model (NPM) to inform the process of implementation of collaborative care in both a future full-scale trial, and the wider health economy.MethodsApplication of the NPM to qualitative data collected in both focus groups and one-to-one interviews before and after an exploratory randomised controlled trial of a collaborative model of care for depression.ResultsFindings are presented as they relate to the four factors of the NPM (interactional workability, relational integration, skill-set workability, and contextual integration) and a number of necessary tasks are identified. Using the model, it was possible to observe that predictions about necessary work to implement collaborative care that could be made from analysis of the pre-trial data relating to the four different factors of the NPM were indeed borne out in the post-trial data. However, additional insights were gained from the post-trial interview participants who, unlike those interviewed before the trial, had direct experience of a novel intervention. The professional freedom enjoyed by more senior mental health workers may work both for and against normalisation of collaborative care as those who wish to adopt new ways of working have the freedom to change their practice but are not obliged to do so.ConclusionsThe NPM provides a useful structure for both guiding and analysing the process by which an intervention is optimized for testing in a larger scale trial or for subsequent full-scale implementation.