Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Emergency Care Units across Senegal

Emergency care units in Senegal face variability in clinical outcomes due to differences in infrastructure, staff training, and patient demographics. A Bayesian hierarchical model was employed to analyse clinical outcome data from multiple emergency care units. The model accounts for both unit-level (e.g., staff competence) and patient-level (e.g., age, comorbidities) variability. The model identified significant unit-specific effects on clinical outcomes, with some units showing better performance than others, particularly in the treatment of respiratory infections. The Bayesian hierarchical model provides a nuanced understanding of how different emergency care units operate and can inform policy decisions aimed at improving patient care across Senegal. Health policymakers should prioritise training for staff in high-risk areas and allocate resources to support these identified units. Bayesian Hierarchical Model, Emergency Care Units, Clinical Outcomes, Senegal Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.