{ "background": "District hospitals are critical nodes in sub-Saharan African health systems, yet persistent inefficiencies constrain service delivery and outcomes. Robust longitudinal analysis of their operational efficiency remains methodologically underdeveloped, limiting evidence for systemic improvement.", "purpose and objectives": "This study provides a methodological evaluation of panel-data estimation techniques for measuring technical efficiency gains within district hospital systems. It aims to identify the most robust econometric approach for this context and to generate initial longitudinal efficiency estimates.", "methodology": "We constructed a balanced panel dataset from administrative and financial records for all district-level facilities. Technical efficiency was estimated using a true fixed-effects stochastic frontier model: $\\ln y{it} = \\alphai + \\beta\\ln x{it} + v{it} - u{it}$, where $u{it}$ follows a half-normal distribution. Model robustness was assessed via bootstrapped standard errors and comparison with alternative specifications.", "findings": "The true fixed-effects specification outperformed pooled and random-effects models, controlling for unobserved heterogeneity. Estimated mean technical efficiency showed a statistically significant upward trend, increasing by approximately 0.8% per annum (95% CI: 0.5% to 1.1%). Efficiency gains were positively associated with higher nurse-to-patient ratios.", "conclusion": "Panel-data stochastic frontier analysis, employing a true fixed-effects estimator, provides a methodologically robust framework for tracking hospital efficiency over time. The application confirms measurable, though modest, long-term efficiency improvements within the system studied.", "recommendations": "Health system planners should adopt panel-data stochastic frontier analysis for routine monitoring of hospital efficiency. Policy should prioritise investments in clinical staffing to sustain the observed positive trajectory.", "key words": "technical efficiency, stochastic frontier analysis, panel data, health systems, hospitals, econometrics", "contribution statement": "This paper introduces a novel application of the true fixed-effects stochastic frontier model to African hospital data, providing a validated methodological template for longitudinal efficiency analysis in resource-constrained settings