"background": "Community health centres (CHCs) are a cornerstone of primary healthcare delivery in many African nations, yet rigorous, longitudinal assessments of their cost-effectiveness remain scarce. Rwanda's nationally scaled CHC system, developed over recent decades, provides a critical case for methodological evaluation to inform health systems policy across the continent. ", "purpose and objectives": "This review aims to critically evaluate methodological approaches for assessing CHC cost-effectiveness using panel-data techniques, synthesise existing evidence on the Rwandan system's performance, and identify optimal analytical frameworks for future research and policy analysis. ", "methodology": "We conducted a systematic review of peer-reviewed literature, government reports, and grey literature. Methodological appraisal focused on the application of panel-data models, such as the two-way fixed effects estimator: Y{it = \ + \ Xit + \ + \ +, where Yit is a health outcome for CHC i at time t. We assessed model specification, handling of unobserved heterogeneity, and robustness checks, including cluster-robust standard errors. ", "findings": "The review finds a predominant theme of improved maternal and child health outcomes associated with CHC scale-up, with one synthesis indicating a statistically significant reduction in under-five mortality (point estimate: 22%, 95% CI: 18 to 26). However, methodological limitations, particularly in accounting for time-varying confounders and selection bias, constrain causal inference on cost-effectiveness. ", "conclusion": "Panel-data methods offer a powerful but underutilised toolkit for evaluating CHC systems. While existing evidence suggests positive health impacts from Rwanda's network, the evidence base for definitive cost-effectiveness conclusions is methodologically heterogeneous and requires more rigorous, standardised application of longitudinal econometric techniques. ", "recommendations": "Future studies should employ difference-in-differences or synthetic control designs with careful attention to parallel trends assumptions. National health management information systems must be strengthened to routinely capture standardised
Uwimana et al. (Sun,) studied this question.