{ "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: $Y{it} = \\alpha + \\beta X{it} + \\mui + \\lambdat + \\epsilon{it}$, where $Y{it}$ 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