Bayesian Hierarchical Model for Evaluating Clinical Outcomes in Urban Primary Care Networks: A Meta-Analysis of Tanzanian Studies

Urban primary care networks in Tanzania have been established to improve healthcare access and quality. However, there is a need for methodological evaluation of these systems' effectiveness across various clinical outcomes. A Bayesian hierarchical model was employed to analyse data from multiple studies conducted by various researchers in Tanzania between and . This approach allows for the integration of diverse datasets while accounting for potential heterogeneity across sites. The analysis revealed a significant improvement in patient satisfaction scores with primary care services, indicating a positive impact on the quality of care provided. This study provides robust evidence supporting the effectiveness of urban primary care networks in Tanzania and highlights areas where further intervention may be necessary to enhance clinical outcomes. Health policymakers should prioritise resource allocation towards strengthening these networks to ensure equitable access to healthcare, particularly for underserved populations. Bayesian hierarchical model, urban primary care networks, Tanzanian studies, clinical outcomes, quality of care Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.