Mental disorders are the leading cause of disability worldwide, yet treatment gaps exceed 90% in many low- and middle-income countries (LMICs). While significant progress is being made in access to mental healthcare through task-shifting to lower-level healthcare providers, urgent gaps in quality exist between evidence-based protocols and mental health delivery systems globally. Few studies have characterized and assessed the performance of interacting care components needed for high-quality global mental healthcare delivery. Further, there are no evidence-based packages for global mental health cascade analysis and quality improvement. Previous work in Mozambique to improve the prevention of the mother-to-child HIV transmission of HIV (PMTCT) care cascade packaged systems engineering tools in a 5-step approach aimed at frontline workers, including: (1) cascade analysis to visualize PMTCT cascade drop-offs and prioritize areas for systems modifications; (2) process mapping to identify modifiable facility-level bottlenecks; (3) identification and implementation of modifications to eliminate system bottlenecks; (4) assessment of modification effects on the cascade; and (5) repeated analysis and improvement cycles. A recent cluster RCT (?Systems Analysis and Improvement Approach (SAIA)? (R01HD075057, PI: Sherr)) established that the SAIA intervention substantially increased maternal ARV initiation and early infant diagnosis across three study countries in sub-Saharan Africa, and provides an evidence-based, flexible model to optimize care cascades in LMICs. The objective of this project is to adapt the evidence-based SAIA cascade analysis and optimization tools/protocols and apply them to improving mental health care delivery in Mozambique (SAIA-MH).
Our specific aims are to: (1) adapt cascade analysis indicators and data tools to SAIA-MH, and assess their usability and feasibility among end-users; and (2) pilot-test the effectiveness, practicality, and process fidelity of the full SAIA-MH cascade analysis, process mapping, and associated task-shared mental health quality improvement approaches. The Consolidated Framework for Implementation Research will guide implementation outcome measurement to understand inner setting, intervention, and process constructs affecting SAIA-MH implementation. This project is a novel application of a systems engineering intervention ? with proven effectiveness in PMTCT ? to global mental health systems optimization. It leverages over 25 years of collaboration between the University of Washington and the Ministry of Health in Mozambique. This application meets the goals of implementation research in PAR-16-236 by testing a novel strategy to improve adoption and implementation of evidence-based interventions in clinical settings using a systems intervention to impact organizational structure, climate, culture, and processes. This project has been designed to focus on team science and the engagement of end users throughout the process. If successful, information from this award will be used to improve SAIA-MH implementation strategies in preparation for a larger cluster-controlled trial assessing SAIA-MH effectiveness.
This implementation research project aims to adapt an evidence-based Systems Analysis and Improvement Approach (SAIA) for use in global mental health systems improvement (SAIA-MH). This award will result in pilot SAIA-MH data and tools that can be more rigorously tested in a future pragmatic health systems trial with the ultimate goal of improving the delivery of high-quality evidence-based mental healthcare in low-resource settings globally.
