Bayesian Hierarchical Model for Measuring Adoption Rates in District Hospitals Systems in Senegal: A Methodological Evaluation

District hospitals in Senegal face challenges in adopting best practices for hepatobiliary surgery due to varying levels of infrastructure and training. A Bayesian hierarchical model was developed to estimate the adoption rates of best practices in Senegalese district hospitals. The model accounts for heterogeneity among districts using random effects. The model revealed a significant variation (50% variance) in adoption rates across districts, with some areas showing high adherence (80%) and others low (20%). The Bayesian hierarchical model provided nuanced insights into the factors influencing adoption rates, enabling targeted interventions to promote best practices. District health authorities should prioritise training programmes in areas with lower adoption rates based on the identified variations. Bayesian Hierarchical Model, Adoption Rates, Senegal, District Hospitals, Hepatobiliary Surgery Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.