The Efficacy of Measurement-Based Care for Depressive Disorders: Systematic Review and Meta-Analysis of Randomized Controlled Trials
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Published on: August 11, 2015
Maria Zhu1, Ran Ha Hong1, Tao Yang2
1Department of Psychiatry, University of British Columbia, Vancouver, Canada.
Abstract:
To determine the efficacy of measurement-based care (MBC), defined as routinely administered outcome measures with practitioner and patient review to inform clinical decision-making, for adults with depressive disorders.
Abstract:
Embase, MEDLINE, PsycINFO, ClinicalTrials.gov, CNKI, and Wanfang Data were searched through July 1, 2020, using search terms for measurement-based care, depression, antidepressant or pharmacotherapy, and randomized controlled trials (RCTs), without language restriction.
Abstract:
Of 8,879 articles retrieved, 7 RCTs (2,019 participants) evaluating MBC for depressive disorders, all involving pharmacotherapy, were included.
Abstract:
Two independent reviewers extracted data. The primary outcome was response rate (≥ 50% improvement from baseline to endpoint on a depression scale). Secondary clinical outcomes were remission rate (endpoint score in remission range), difference in endpoint severity, and medication adherence.
Abstract:
Meta-analysis with random-effects models found no significant difference between MBC and comparison groups in response rates (3 studies; odds ratio [OR] = 1.66; 95% CI, 0.66-4.17; P = .279). MBC was associated with significantly greater remission rates (5 studies; OR = 1.83; 95% CI, 1.12-2.97; P = .015), lower endpoint severity (5 studies; standardized mean difference = 0.53; CI 0.06-0.99; P = .026), and greater medication adherence (3 studies; OR = 1.68; 95% CI, 1.22-2.30; P = .001).
Abstract:
Although benefits for clinical response are unclear, MBC is effective in decreasing depression severity, promoting remission, and improving medication adherence in patients with depressive disorders treated with pharmacotherapy. The results are limited by the small number of included trials, high risk of bias, and significant study heterogeneity.
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