Urban primary care networks in Ethiopia aim to improve access to healthcare services for underserved populations. However, methodological challenges hinder effective evaluation of these systems. A retrospective analysis was conducted on electronic health records from to , employing Holt-Winters exponential smoothing for trend and seasonal decomposition of time series by loess (STL) method. Uncertainty in forecasts was quantified using standard errors. During the study period, there was a consistent decline in outpatient visits per month, suggesting potential underutilization of primary care services. The time-series forecasting models provided insights into the variability and trends in patient utilization within urban primary care networks. Further research should include qualitative assessments to understand barriers to service uptake and explore strategies for network improvement. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.