Urban primary care networks (UPCNs) are essential for providing accessible healthcare in urban settings of developing countries like Tanzania. However, their effectiveness and efficiency require rigorous evaluation. A mixed-methods approach was employed with a focus on data from urban primary care clinics. Multilevel regression models were used to analyse patient-level and clinic-level variables, accounting for spatial autocorrelation. The analyses revealed significant variation in treatment success rates across different clinics (e. g. , an average improvement of 15% in recovery times). Multilevel regression analysis provided a robust framework to evaluate the impact and efficiency of urban primary care networks. Further research should focus on implementation strategies and continuous quality improvements within these systems. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Kamasi Mbiusi (Mon,) studied this question.