{ "background": "District hospitals in sub-Saharan Africa face systemic challenges in patient safety and operational risk management. Existing evaluations often rely on cross-sectional data, which fail to capture temporal dynamics and may misattribute causality in system interventions.", "purpose and objectives": "This study aimed to methodologically evaluate a multi-component intervention in district hospital systems and quantify its effect on clinical risk reduction using a longitudinal panel-data framework.", "methodology": "We conducted an intervention study across a panel of district hospitals. A fixed-effects panel model was estimated to isolate the intervention's impact, controlling for time-invariant heterogeneity. The primary model was specified as $Risk{it} = \\beta0 + \\beta1 Intervention{it} + \\mathbf{X}{it}\\boldsymbol{\\beta} + \\alphai + \\epsilon{it}$, where $\\alphai$ denotes hospital-specific fixed effects. Inference was based on cluster-robust standard errors.", "findings": "The intervention was associated with a statistically significant reduction in aggregate clinical risk scores. A 23.5% reduction (95% CI: 18.2% to 28.8%) was observed in treated facilities relative to the pre-intervention baseline. The panel estimation confirmed the effect was robust to unobserved, time-invariant confounders.", "conclusion": "The longitudinal panel-data approach provides a robust methodological framework for evaluating health system interventions, demonstrating that structured, multi-component programmes can substantially mitigate systemic clinical risks in resource-constrained settings.", "recommendations": "Health system planners should adopt panel-data methodologies for evaluating complex interventions. The specific intervention components, including structured audit cycles and supply chain protocols, should be considered for scale-up.", "key words": "health systems research, patient safety, fixed-effects model, clinical audit, health policy evaluation", "contribution statement": "This paper provides a novel application of econometric panel-data methods to the evaluation of a hospital systems intervention, generating robust evidence for a 23.5% reduction in clinical