{ "background": "District hospital systems in Nigeria face significant operational risks, including supply chain failures and workforce shortages, which compromise service delivery. Existing evaluations often lack rigorous longitudinal analysis to quantify the impact of systemic interventions on risk mitigation.", "purpose and objectives": "This study aimed to methodologically evaluate a multi-component intervention in district hospital systems and to estimate its effect on reducing composite operational risk scores using panel-data econometrics.", "methodology": "We conducted a quasi-experimental intervention study across multiple districts. The intervention comprised integrated logistics management and targeted staff training. A balanced panel dataset was constructed from routine administrative records. The primary effect was estimated using a two-way fixed effects model: $Risk{it} = \\alpha + \\beta Intervention{it} + \\mui + \\lambdat + \\epsilon{it}$, where $\\mui$ and $\\lambda_t$ denote hospital and time fixed effects. Inference was based on cluster-robust standard errors.", "findings": "The intervention was associated with a statistically significant reduction in the composite risk score. Estimates indicate a 17.5% reduction (95% CI: 12.1% to 22.9%, p<0.01) attributable to the intervention package, with logistics management driving the majority of the observed effect.", "conclusion": "The applied panel-data methodology provides a robust framework for evaluating health system interventions. The integrated intervention package effectively reduced measurable operational risks within the studied hospital systems.", "recommendations": "Health policymakers should adopt panel-data estimation for routine monitoring and evaluation of system-level interventions. Scaling the integrated logistics and training package to other districts is warranted, with attention to contextual adaptation.", "key words": "health systems research, panel data, fixed effects, operational risk, hospital management, intervention evaluation", "contribution statement": "This paper provides a novel application of two-way fixed effects estimation to quantify the impact of a complex health system intervention on a composite risk metric, offering a replicable methodological framework for low-resource