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. 2022 Jun 6;17(1):37.
doi: 10.1186/s13012-022-01213-8.

Systems analysis and improvement approach to optimize outpatient mental health treatment cascades in Mozambique (SAIA-MH): study protocol for a cluster randomized trial

Vasco F J Cumbe #  1   2   3 , Alberto Gabriel Muanido #  4 , Morgan Turner  5 , Isaias Ramiro  4 , Kenneth Sherr  5   6   7 , Bryan J Weiner  5 , Brian P Flaherty  8 , Monisha Sharma  5 , Flávia Faduque  9 , Ernesto Rodrigo Xerinda  10 , Bradley H Wagenaar  5   6
Affiliations

Systems analysis and improvement approach to optimize outpatient mental health treatment cascades in Mozambique (SAIA-MH): study protocol for a cluster randomized trial

Vasco F J Cumbe et al. Implement Sci. .

Abstract

Background: Significant investments are being made to close the mental health (MH) treatment gap, which often exceeds 90% in many low- and middle-income countries (LMICs). However, limited attention has been paid to patient quality of care in nascent and evolving LMIC MH systems. In system assessments across sub-Saharan Africa, MH loss-to-follow-up often exceeds 50% and sub-optimal medication adherence often exceeds 60%. This study aims to fill a gap of evidence-based implementation strategies targeting the optimization of MH treatment cascades in LMICs by testing a low-cost multicomponent implementation strategy integrated into routine government MH care in Mozambique.

Methods: Using a cluster-randomized trial design, 16 clinics (8 intervention and 8 control) providing primary MH care will be randomized to the Systems Analysis and Improvement Approach for Mental Health (SAIA-MH) or an attentional placebo control. SAIA-MH is a multicomponent implementation strategy blending external facilitation, clinical consultation, and provider team meetings with system-engineering tools in an overall continuous quality improvement framework. Following a 6-month baseline period, intervention facilities will implement the SAIA-MH strategy for a 2-year intensive implementation period, followed by a 1-year sustainment phase. Primary outcomes will be the proportion of all patients diagnosed with a MH condition and receiving pharmaceutical-based treatment who achieve functional improvement, adherence to medication, and retention in MH care. The Consolidated Framework for Implementation Research (CFIR) will be used to assess determinants of implementation success. Specific Aim 1b will include the evaluation of mechanisms of the SAIA-MH strategy using longitudinal structural equation modeling as well as specific aim 2 estimating cost and cost-effectiveness of scaling-up SAIA-MH in Mozambique to provincial and national levels.

Discussion: This study is innovative in being the first, to our knowledge, to test a multicomponent implementation strategy for MH care cascade optimization in LMICs. By design, SAIA-MH is a low-cost strategy to generate contextually relevant solutions to barriers to effective primary MH care, and thus focuses on system improvements that can be sustained over the long term. Since SAIA-MH is integrated into routine government MH service delivery, this pragmatic trial has the potential to inform potential SAIA-MH scale-up in Mozambique and other similar LMICs.

Trial registration: ClinicalTrials.gov; NCT05103033 ; 11/2/2021.

Keywords: Cluster randomized trial; Continuous quality improvement; Global mental health; Mozambique; Optimization of care cascades; Primary mental healthcare; Process mapping; Systems Analysis and Improvement Approach (SAIA); Systems engineering; Task-sharing.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Mozambique with focal provinces of Sofala and Manica outlined in red. Figure sourced from Fernandes QF et al. (2014) [19]
Fig. 2
Fig. 2
Systems Analysis and Improvement Approach for Mental Health (SAIA-MH) implementation strategy processes
Fig. 3
Fig. 3
Mental health cascade analysis tool (MHCAT)
Fig. 4
Fig. 4
Causal pathway model of hypothesized mechanisms of SAIA-MH effects
See this image and copyright information in PMC

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