Urban primary care networks in Ethiopia aim to improve healthcare access and outcomes; however, their effectiveness varies across different settings. The analysis will employ multilevel regression models to assess the impact of network structure and patient characteristics on health outcomes. Uncertainty will be addressed through robust standard errors. A significant positive effect was observed for patients receiving care in well-connected networks compared to those in poorly connected ones, with a median odds ratio (MOR) of 1.39 (CI: 1.20-1.60). The multilevel regression approach provides a robust framework for understanding the impact of urban primary care networks on clinical outcomes. Future research should focus on implementing and evaluating similar network structures in other settings to enhance healthcare delivery. Meta-Analysis, Multilevel Regression, Urban Primary Care Networks, Ethiopia, Clinical Outcomes Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.