{ "background": "Emergency care systems in sub-Saharan Africa are critical for reducing preventable mortality, yet robust methodological frameworks for their longitudinal evaluation are lacking. Existing assessments often rely on cross-sectional data, failing to capture system dynamics and temporal trends in performance.", "purpose and objectives": "This study aimed to develop and apply a panel-data methodology to evaluate the operational performance and clinical outcomes of hospital-based emergency care units in Uganda, identifying key drivers of system efficiency and patient survival.", "methodology": "We conducted a retrospective analysis of longitudinal administrative and clinical data from a nationally representative sample of units. A two-way fixed effects model was estimated: $Y{it} = \\alpha + \\beta1 X{it} + \\mui + \\lambdat + \\epsilon{it}$, where $Y_{it}$ is the risk-adjusted mortality rate for unit $i$ in period $t$. Inference was based on cluster-robust standard errors.", "findings": "A one-standard-deviation increase in nurse-to-patient ratio was associated with a 4.2 percentage-point reduction in risk-adjusted mortality (95% CI: -6.1, -2.3). Operational performance, measured by patient flow, showed significant heterogeneity, with central referral units underperforming regional facilities by an average of 15% on throughput metrics.", "conclusion": "The panel-data approach provides a robust methodological framework for health systems evaluation, revealing that resource allocation and patient flow management are significant, modifiable determinants of clinical outcomes in emergency care.", "recommendations": "Policy should prioritise targeted increases in human resources for emergency units and implement standardised patient flow protocols. Future research should integrate this methodological framework with cost-effectiveness analyses.", "key words": "health systems research, emergency medicine, panel data, fixed effects, Uganda, clinical outcomes, operational performance", "contribution statement": "This paper provides a novel methodological application of econometric panel-data models to the longitudinal evaluation of emergency care systems in a low-resource setting, generating