{ "background": "Evaluating the long-term efficiency of community health centre systems in low-resource settings requires robust quasi-experimental designs to isolate the impact of specific interventions from secular trends.", "purpose and objectives": "This longitudinal study aims to methodologically evaluate the application of a difference-in-differences (DiD) model for measuring sustained efficiency gains within a national network of primary care facilities.", "methodology": "We employ a panel DiD design, estimating the model $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon{it}$, where $Y{it}$ is a composite efficiency score. The analysis uses longitudinal administrative data on patient encounters, resource allocation, and outcomes. Inference is based on cluster-robust standard errors to account for serial correlation.", "findings": "The methodological evaluation indicates that the DiD estimator successfully identified a significant positive treatment effect. The model revealed a sustained 18% improvement in the composite efficiency score for intervention centres relative to controls, with the coefficient on the interaction term $\\delta$ being statistically significant at the 1% level.", "conclusion": "The difference-in-differences approach provides a rigorous framework for attributing longitudinal efficiency improvements to systemic interventions in community health systems, controlling for underlying temporal confounders.", "recommendations": "Future research and policy evaluation in similar contexts should adopt quasi-experimental designs like DiD to strengthen causal claims. Investment in longitudinal, facility-level data systems is critical to support such analyses.", "key words": "quasi-experimental design, health systems efficiency, panel data, causal inference, primary healthcare", "contribution statement": "This paper provides a novel methodological application of the DiD model for evaluating long-term health system efficiency in a sub-Saharan African context, demonstrating its utility for policy assessment where randomised trials are