Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Ethiopian Community Health Centres Systems

Community health centres in Ethiopia face challenges in providing consistent clinical outcomes due to variability across different regions and service delivery levels. A Bayesian hierarchical model was developed using data from multiple Ethiopian community health centres. The model accounts for regional variations and service delivery differences by incorporating random effects at both the centre level and district level. Uncertainty quantification is achieved through robust standard errors and credible intervals. The model estimated that clinical outcomes varied significantly between districts, with a proportion of 30% of centres achieving above-average performance in key indicators such as vaccination coverage and infant mortality rates. The Bayesian hierarchical model provides a nuanced understanding of regional disparities in health centre performance and can guide targeted interventions to improve service delivery. Health authorities should prioritise investments in infrastructure and training for the lowest-performing districts, based on the findings from this study. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.