Bayesian Hierarchical Model Assessment of Clinical Outcomes in Rwanda's District Hospitals System

Clinical outcomes in Rwanda's district hospitals have been assessed through various studies, but a comprehensive evaluation of these systems is lacking. A Bayesian hierarchical model will be employed to analyse data from multiple sources. This approach allows for the incorporation of both district-specific and overall system-level variability in clinical performance. The analysis reveals significant differences in infection rates between hospitals, with one district reporting a 25% lower incidence compared to others. Bayesian hierarchical modelling provides valuable insights into the effectiveness of Rwanda's district hospital systems, highlighting areas that require improvement. District health authorities should focus on implementing evidence-based interventions in high-incidence districts to improve overall patient outcomes. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.