The Effectiveness of Measurement-Based Care for Depressive Disorders: A Meta-Analysis of Randomized Controlled Trials

Objectives: Measurement-based care (MBC) with rigorous assessment and treatment algorithms are regarded as key instruments to optimize treatment delivery and outcomes for depression. This meta-analysis systematically examined the effectiveness of MBC for depressive disorders based on cluster randomized studies or randomized controlled trials (RCTs). Methods: Pubmed, the Cochrane Library, and PsycInfo, EMBASE, up to January 6th, 2020 were searched for this meta-analysis. The electronic search was supplemented by a manual search. Standardized mean difference (SMD), risk ratio (RR), and their 95% confidence intervals (CIs) were calculated and analyzed. Results: A total of 29 studies with 15,255 participants were analyzed. MBC showed better effectiveness with the pooled RR for response of 1.30 (95%CI: 1.13-1.50, I2=81.9%, P<0.001, 18 studies), remission of 1.35 (95%CI: 1.11-1.64, I2 =85.5%, P<0.001, 18 studies) and symptom reduction with a pooled SMD of -0.42 (95%CI: -0.61-(-0.23), I2=94.3%, P<0.001, 19 studies). All-cause discontinuations were similar between MBC and usual care with the pooled RR of 1.08 (95%CI: 0.94-1.23, I2=68.0%, P=0.303, 27 studies). Conclusion: This meta-analysis supported MBC as an evidence-based framework to improve the treatment outcome of depressive disorders. Registration: PROSPERO: CRD42020163668 Funding Statement: The study was supported by the Capital's Funds for Health Improvement and Research (No. 2018-1-2121). Declaration of Interests: All authors declare no conflicts of interest concerning this article.