"background": "The reliability of community health centre systems is a critical determinant of healthcare delivery and outcomes in resource-limited settings. Existing methodological approaches for evaluating system reliability often fail to account for the hierarchical, clustered nature of health system data, potentially leading to biased inferences. ", "purpose and objectives": "This study aimed to methodologically evaluate the application of multilevel regression for measuring system reliability in a network of community health centres, assessing its advantages over conventional single-level models for informing targeted interventions. ", "methodology": "We conducted an intervention study, implementing a novel multilevel modelling framework. The core statistical model was a three-level random intercept logistic regression: (p{ijk) = \0 + \ Xijk + uk + vjk, where pijk is the probability of a reliable system outcome for observation i in facility j within district k, uk and vjk are district- and facility-level random effects. Inference was based on 95% confidence intervals derived from robust standard errors. ", "findings": "The multilevel model revealed significant variation attributable to district-level clustering, accounting for approximately 18% of the total variance in system reliability scores. This district-level effect was not discernible in a standard logistic regression, which produced artificially narrow confidence intervals for key predictors, overstating their precision. ", "conclusion": "Multilevel regression provides a methodologically superior framework for analysing health system reliability in this context, as it correctly accounts for data hierarchy and yields more valid estimates of uncertainty. ", "recommendations": "Future evaluations of health system performance in similar settings should adopt multilevel analytical techniques to guide more effective, context-specific interventions. Investment should be prioritised for capacity building in advanced statistical methods among health systems researchers. ", "key words": "health systems research, multilevel modelling, hierarchical data, reliability analysis, sub-Saharan Africa, methodological evaluation", "contribution statement": "This
Mtei et al. (Mon,) studied this question.