{ "background": "Rural clinic systems are critical for healthcare delivery in sub-Saharan Africa, yet robust quantitative evaluations of their impact on clinical outcomes are scarce. Existing studies often lack rigorous counterfactual analysis, limiting causal inference.", "purpose and objectives": "This study aims to quantify the causal effect of a systemic intervention in rural primary care clinics on key population health indicators, specifically maternal and child health outcomes.", "methodology": "We employ a quasi-experimental difference-in-differences design, leveraging the phased rollout of the intervention across districts. The primary model is $Y{dt} = \\beta0 + \\beta1 (\\text{Treated}{dt}) + \\beta2 (\\text{Post}{dt}) + \\beta3 (\\text{Treated}{dt} \\times \\text{Post}{dt}) + \\epsilon{dt}$, where $Y_{dt}$ is the outcome in district $d$ at time $t$. Inference is based on cluster-robust standard errors at the district level.", "findings": "Preliminary analysis of a pilot phase indicates a positive direction of effect. The intervention is associated with a 12.3 percentage point increase in the rate of facility-based deliveries (95% CI: 8.1, 16.5) in treated districts relative to controls.", "conclusion": "The phased intervention model shows significant potential for improving maternal healthcare utilisation. The difference-in-differences approach provides a robust framework for ongoing evaluation as the rollout continues.", "recommendations": "Policy makers should consider the phased implementation model for similar systemic healthcare interventions to enable rigorous impact evaluation. Future research should incorporate cost-effectiveness analysis.", "key words": "health systems evaluation, maternal health, quasi-experimental design, primary healthcare, sub-Saharan Africa", "contribution statement": "This paper provides a novel application of the difference-in-differences methodology to evaluate a large-scale, real-world health system intervention in a rural African setting, generating a unique