Bayesian Hierarchical Model for Evaluating Clinical Outcomes in District Hospitals Systems in Kenya

District hospitals in Kenya play a crucial role in primary healthcare delivery but often face challenges in maintaining optimal clinical outcomes. A Bayesian hierarchical model was employed to analyse data from multiple district hospitals across Kenya. The model accounts for hospital-specific variability by incorporating random effects that vary according to geographical regions. The analysis revealed significant heterogeneity in clinical outcomes between different regions, with some areas showing a 20% improvement in treatment efficacy compared to others. Bayesian hierarchical models provide a robust framework for understanding and enhancing the performance of district hospitals in Kenya. District hospital management should focus on regional-specific interventions based on model findings to optimise clinical outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.