{ "background": "Community health centres are critical nodes in Ethiopia's primary healthcare system, yet systematic evaluations of their operational methodologies for measuring health risk reduction are lacking. Existing assessments often fail to account for the hierarchical structure of health data, which can obscure true intervention effects.", "purpose and objectives": "This brief report aims to methodologically evaluate the systems of community health centres by applying a multilevel modelling approach to quantify the reduction in key health risks. The objective is to demonstrate a robust analytical framework for measuring centre-level performance.", "methodology": "We conducted a secondary analysis of anonymised, cross-sectional patient data from multiple centres. A two-level random intercept logistic regression model was fitted to assess the probability of a negative health outcome. The model is specified as $\\logit(p{ij}) = \\beta0 + \\beta X{ij} + uj$, where $p{ij}$ is the probability for patient $i$ in centre $j$, $X$ represents patient-level covariates, and $uj \\sim N(0, \\sigma^2u)$ is the centre-specific random effect. Inference was based on robust standard errors.", "findings": "The multilevel analysis revealed significant centre variation ($\\sigma^2u = 0.42$, 95% CI: 0.31, 0.58). After adjusting for patient covariates, centres implementing the integrated reporting protocol showed a 33% lower odds (OR: 0.67, CI: 0.52, 0.86) of patient referral for severe malnutrition.", "conclusion": "The application of multilevel regression provides a more valid methodological framework for evaluating centre performance by accounting for data clustering. It identifies specific operational protocols associated with measurable health risk reduction.", "recommendations": "Programme evaluators should adopt hierarchical modelling techniques for performance assessment. Health policy should promote the integration of the specific reporting protocol linked to improved outcomes across all centres.", "key words": "health systems evaluation, mult