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

Bayesian hierarchical models have shown promise in analysing complex healthcare data across diverse settings. A Bayesian hierarchical linear regression model was developed to estimate the impact of various factors on patient outcomes. Uncertainty quantification was provided through credible intervals. The analysis revealed significant heterogeneity in clinical performance across CHCs, with some centres achieving higher treatment success rates than others. Bayesian hierarchical models offer a robust framework for understanding and improving healthcare delivery in Ghanaian CHCs. Policy makers should consider stratifying resources based on the assessment of individual CHC performance to optimise service provision. Bayesian hierarchical model, clinical outcomes, community health centres, Ghana Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.