African Neurology and Neurosurgery | 09 May 2007
Bayesian Hierarchical Model for Measuring Clinical Outcomes in Rural Clinics Systems Over Time in South Africa,
S, i, k, u, M, a, s, e, b, o
Abstract
This study aims to evaluate the effectiveness of rural clinics in South Africa by measuring clinical outcomes over time. Bayesian Hierarchical Model (BHM) was employed to analyse longitudinal data from South African clinics. The BHM accounts for the variability between individual clinics while accounting for common trends over time. The Bayesian hierarchical model demonstrated significant heterogeneity in clinical outcomes across different rural clinics, with some clinics showing improvement rates of up to 20% compared to baseline. The findings suggest that targeted interventions could enhance the performance and efficiency of rural health systems in South Africa. Policy makers should consider implementing data-driven strategies to improve clinic performance based on this model's insights. Treatment effect was estimated with $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.