The effectiveness of enhanced evidence-based care for depressive disorders: a meta-analysis of randomized controlled trials
Le Xiao, Han Qi, Wei Zheng, Yu‐Tao Xiang, Thomas Carmody, Taryn L. Mayes, Madhukar H. Trivedi, Gang Wang
Abstract
Abstract Several care models have been developed to improve treatment for depression, all of which provide “enhanced” evidence-based care (EEC). The essential component of these approaches is Measurement-Based Care (MBC). Specifically, Collaborative Care (CC), and Algorithm-guided Treatment (AGT), and Integrated Care (IC) all use varying forms of rigorous MBC assessment, care management, and/or treatment algorithms as key instruments to optimize treatment delivery and outcomes for depression. This meta-analysis systematically examined the effectiveness of EEC versus usual care for depressive disorders based on cluster-randomized studies or randomized controlled trials (RCTs). 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. A total of 29 studies with 15,255 participants were analyzed. EEC showed better effectiveness with the pooled RR for response of 1.30 (95%CI: 1.13–1.50, I 2 = 81.9%, P < 0.001, 18 studies), remission of 1.35 (95%CI: 1.11–1.64, I 2 = 85.5%, P < 0.001, 18 studies) and symptom reduction with a pooled SMD of −0.42 (95%CI: −0.61–(−0.23), I 2 = 94.3%, P < 0.001, 19 studies). All-cause discontinuations were similar between EEC and usual care with the pooled RR of 1.08 (95%CI: 0.94–1.23, I 2 = 68.0%, P = 0.303, 27 studies). This meta-analysis supported EEC as an evidence-based framework to improve the treatment outcome of depressive disorders. Review registration: PROSPERO: CRD42020163668