{ "background": "Community health centres are critical nodes in Uganda's healthcare system, yet persistent inefficiencies in resource allocation and service delivery constrain their operational yield. A robust methodological framework for quantifying and analysing longitudinal performance improvements in these settings is lacking.", "purpose and objectives": "This study aims to develop and apply a panel-data econometric model to evaluate systemic yield optimisation within a network of community health centres. The primary objective is to estimate the marginal effects of key operational inputs on a composite yield metric, controlling for unobserved heterogeneity.", "methodology": "We utilise a uniquely constructed administrative panel dataset from a nationally representative sample of centres. Yield is measured as a weighted index of patient visits, successful referrals, and vaccine doses administered. The core specification is a two-way fixed effects model: $Y{it} = \\alpha + \\beta1 Staff{it} + \\beta2 Supply{it} + \\beta3 Training{it} + \\mui + \\lambdat + \\epsilon{it}$, where $\\mui$ and $\\lambdat$ denote centre and time fixed effects, respectively. Inference is based on cluster-robust standard errors.", "findings": "The analysis indicates that targeted staff training interventions had the strongest positive association with yield ($\\beta_3 = 0.18$, 95% CI: 0.11, 0.25), explaining approximately 15% of the observed inter-period variation. Increases in consumable supplies showed a smaller, non-linear effect, while baseline staffing levels were not a statistically significant predictor after accounting for centre-level fixed factors.", "conclusion": "The methodological approach confirms that panel-data techniques are essential for isolating the drivers of health system yield in this context, as they account for time-invariant centre-specific confounders. Yield optimisation is more sensitive to enhancements in human resource capability than to incremental increases in material inputs alone.", "recommendations": "Health system planners should prioritise continuous, data-driven training programmes over blanket resource allocation.