Abstract
To achieve universal health coverage, health system strengthening (HSS) is required to support the of delivery of high-quality care. The aim of the National Institute for Health Research Global Research Unit on HeAlth System StrEngThening in Sub-Saharan Africa (ASSET) is to address this need in a four-year programme, with three healthcare platforms involving eight work-packages. Key to effective health system strengthening (HSS) is the pre-implementation phase of research where efforts focus on applying participatory methods to embed the research programme within the existing health system. To conceptualise the approach, we provide an overview of the key methods applied across work-package to address this important phase of research conducted between 2017 and 2021.Work-packages are being undertaken in publicly funded health systems in rural and urban areas in Ethiopia, Sierra Leone, South Africa, and Zimbabwe. Stakeholders including patients and their caregivers, community representatives, clinicians, managers, administrators, and policymakers are the main research participants.In each work-package, initial activities engage stakeholders and build relationships to ensure co-production and ownership of HSSIs. A mixed-methods approach is then applied to understand and address determinants of high-quality care delivery. Methods such as situation analysis, cross-sectional surveys, interviews and focus group discussions are adopted to each work-package aim and context. At the end of the pre-implementation phase, findings are disseminated using focus group discussions and participatory Theory of Change workshops where stakeholders from each work package use findings to select HSSIs and develop a programme theory.ASSET places a strong emphasis of the pre-implementation phase in order to provide an in-depth and systematic diagnosis of the existing heath system functioning, needs for strengthening and stakeholder engagement. This common approach will inform the design and evaluation of the HSSIs to increase effectiveness across work packages and contexts, to better understand what works, for whom, and how.