Bayesian Hierarchical Model for Measuring Adoption Rates in South African District Hospitals Systems,

South African district hospitals play a crucial role in providing essential healthcare services to rural populations. However, there is limited data on their performance and adoption rates of new medical technologies. A Bayesian hierarchical model will be employed to analyse data collected from -. This method allows for the estimation of local hospital-specific adoption rates while accounting for regional variability and uncertainty in data collection. The analysis revealed a significant variation in technology adoption among district hospitals, with some regions showing higher adoption rates compared to others. This study provides insights into the adoption patterns of medical technologies within South African district hospitals, contributing to better resource allocation and healthcare planning. Future research should consider expanding data collection over a longer period to capture more comprehensive trends in technology adoption. Bayesian hierarchical model, district hospitals, medical technology adoption, uncertainty quantification Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.