{ "background": "District hospitals are critical nodes in healthcare delivery, yet systematic evaluations of their operational reliability in low-resource settings are methodologically fragmented. Existing studies often lack robust statistical frameworks to account for hierarchical data structures and temporal trends, limiting actionable insights for system strengthening.", "purpose and objectives": "This meta-analysis aims to methodologically evaluate published and grey literature on district hospital systems in Uganda and to apply a novel multilevel regression framework for quantifying system reliability and its determinants.", "methodology": "A systematic search identified relevant studies. Extracted data on reliability indicators (e.g., equipment functionality, service continuity) were synthesised. The core analytical framework employed a three-level Bayesian hierarchical model: $y{ijt} = \\beta0 + \\beta X{ijt} + uj + vt + \\epsilon{ijt}$, where $i$, $j$, and $t$ index observations, districts, and time, respectively, with random intercepts for district ($uj$) and temporal effects ($vt$). Model inference used Markov chain Monte Carlo methods with 95% credible intervals.", "findings": "The synthesis of 42 studies revealed pronounced inter-district heterogeneity, with facility-level factors accounting for an estimated 35% of the variance in reliability scores. The multilevel analysis identified infrastructure investment as a consistently positive predictor (posterior mean 0.42, 95% CrI [0.18, 0.67]), whereas staff density showed a non-significant association after accounting for district-level clustering.", "conclusion": "The methodological application demonstrates that multilevel regression is essential for unbiased estimation of health system reliability determinants in Uganda, revealing that district-level contextual effects are substantial and often overshadow facility-specific inputs.", "recommendations": "Future research and monitoring should adopt hierarchical modelling by default. Policy interventions must be tailored to district contexts rather than applying uniform national standards, with a renewed focus on core infrastructure as a foundational reliability driver.", "key words": "health systems research,