{ "background": "Evaluating the cost-effectiveness of community-based health interventions in low-resource settings is methodologically challenging, requiring robust quasi-experimental designs to establish causal inference.", "purpose and objectives": "This case study aims to methodologically evaluate the application of a difference-in-differences (DiD) model for assessing the cost-effectiveness of a national community health centres programme, focusing on maternal and child health outcomes.", "methodology": "We employ a retrospective DiD design using panel data from administrative health and financial records. The core model is specified as $Y{it} = \\beta0 + \\beta1 \\text{Treat}i + \\beta2 \\text{Post}t + \\delta (\\text{Treat}i \\times \\text{Post}t) + \\epsilon_{it}$, where $\\delta$ is the average treatment effect on the treated. Inference is based on cluster-robust standard errors at the district level.", "findings": "The methodological application revealed that the DiD estimator identified a statistically significant reduction in the cost per facility-based delivery attributable to the programme. A key finding was a 22% decrease in average cost, with a 95% confidence interval of 15% to 29%. The analysis highlighted critical assumptions, particularly parallel trends, and the importance of granular cost-tracking for accurate estimation.", "conclusion": "The DiD model provides a viable and rigorous framework for cost-effectiveness analysis in this context, though its validity depends heavily on the plausibility of its identifying assumptions and data quality.", "recommendations": "Future evaluations should incorporate pre-intervention period checks for parallel trends and integrate activity-based costing from the outset to strengthen causal claims about cost-effectiveness.", "key words": "cost-effectiveness analysis, difference-in-differences, quasi-experimental design, community health, maternal health, health economics", "contribution statement": "This study provides a novel methodological blueprint for applying DiD to cost-effectiveness evaluations of complex public health