{ "background": "District hospitals in Kenya face persistent challenges in delivering consistent, high-quality care due to systemic reliability issues. Existing evaluations often lack the methodological rigour to disentangle facility-level performance from broader regional or systemic influences, limiting actionable insights for health systems strengthening.", "purpose and objectives": "This study aimed to methodologically evaluate the application of multilevel regression modelling for measuring and attributing sources of variation in system reliability across district hospitals. The primary objective was to assess the model's capacity to partition variance between facility and administrative unit levels.", "methodology": "We conducted an intervention study applying a three-level hierarchical linear model. The core statistical model was $y{ijk} = \\beta0 + u{0jk} + v{0k} + \\epsilon{ijk}$, where $y{ijk}$ is the reliability score for observation $i$ in hospital $j$ in county $k$, $u{0jk}$ and $v{0k}$ are random intercepts for hospital and county, respectively, and $\\epsilon_{ijk}$ is the residual error. Robust standard errors were used for inference. Data were derived from routine health management information systems and structured facility assessments.", "findings": "The methodological evaluation demonstrated that the multilevel model effectively partitioned variance, revealing that approximately 65% of the variance in system reliability scores was attributable to differences between individual hospitals, while 22% was associated with county-level administrative effects (95% CI: 18% to 27%). The remaining variance was residual. The model identified significant random intercepts at both levels, confirming the necessity of the hierarchical approach.", "conclusion": "Multilevel regression provides a robust methodological framework for analysing health system reliability, offering superior insight into the nested sources of performance variation compared to conventional single-level analyses.", "recommendations": "Health systems researchers should adopt multilevel modelling for performance evaluations where data have a hierarchical structure. Policymakers should utilise such analyses to target interventions at the appropriate administrative level, as indicated by the