Bayesian Hierarchical Model Evaluation of Clinical Outcomes in Rural Clinics Systems, Rwanda

Clinical outcomes in rural clinics systems have been a focus of interest for improving healthcare services in developing countries. A Bayesian hierarchical model was developed to assess the impact of various factors on clinical outcomes, including patient demographics and clinic quality indicators. Data were collected through structured surveys conducted in . The analysis revealed significant variation in average treatment success rates across different clinics (15% - 30%), with some clinics showing a higher likelihood of successful treatments compared to others. The findings suggest that clinic-specific improvements are necessary for achieving consistent and high-quality clinical outcomes. Clinics should be supported in enhancing their operational efficiency, particularly focusing on reducing patient wait times and increasing treatment success rates. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.