{ "background": "Community health centres are a cornerstone of primary healthcare delivery in many African nations, yet systematic, quantitative evaluations of their operational efficiency remain scarce. Existing assessments often fail to account for the hierarchical structure of health system data, potentially leading to biased inferences.", "purpose and objectives": "This study provides a methodological evaluation of multilevel regression modelling for measuring efficiency gains within community health centre systems. Its objective is to demonstrate the application and interpretative value of this analytical approach for health systems research.", "methodology": "We employed a three-level hierarchical linear model to analyse panel data from a national sample of community health centres. The model, specified as $y{ijk} = \\beta0 + \\beta X{ijk} + u{k} + v{jk} + e{ijk}$, where $i$, $j$, and $k$ index patients, centres, and districts respectively, accounted for clustering at the centre and district levels. Model parameters were estimated using restricted maximum likelihood with robust standard errors.", "findings": "The multilevel model revealed significant variation in key output measures attributable to the district level (approximately 15% of total variance), a factor obscured in pooled ordinary least squares regression. A one-unit increase in the logistical readiness index at the centre level was associated with a 0.23 standard deviation increase in composite service output (95% CI: 0.17 to 0.29).", "conclusion": "Multilevel regression offers a statistically robust framework for analysing efficiency in hierarchically structured health systems, providing insights into the relative contribution of different administrative levels to overall performance.", "recommendations": "Health systems researchers should adopt multilevel modelling techniques for performance evaluations where data are naturally clustered. Policymakers should utilise such analyses to target interventions at the appropriate administrative tier, such as district-level supply chains.", "key words": "health systems research, multilevel modelling, operational efficiency, primary healthcare, hierarchical data, Ghana", "contribution statement": "This paper provides a