The reliability of healthcare systems in district hospitals across Kenya is a critical concern for effective patient care and resource allocation. A Bayesian hierarchical linear regression model was employed to assess the impact of multiple covariates on system reliability. Data from 20 district hospitals were analysed, with measures collected annually from to . The analysis revealed significant variability in system reliability across different districts and over time, with some facilities showing a stable performance pattern while others exhibited erratic trends. Bayesian hierarchical modelling provided nuanced insights into the systemic factors affecting hospital reliability, offering tailored recommendations for improvement. District health authorities should prioritise interventions targeting facilities with persistent system failures to enhance overall healthcare delivery. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.