Methodological Evaluation of Urban Primary Care Networks in Kenya Using Time-Series Forecasting Models for Clinical Outcomes Analysis,

Urban primary care networks (PCNs) in Kenya have been established to improve access to healthcare services for underserved populations. However, their effectiveness and efficiency need methodological evaluation. A time-series forecasting model was employed to analyse trends in patient satisfaction scores across the PCNs. The model included ARIMA (Autoregressive Integrated Moving Average) components, with robust standard errors accounting for uncertainty in predictions. The analysis revealed a positive trend in patient satisfaction scores over time, indicating an improvement in care quality. Specifically, there was a 15% increase in average satisfaction scores from to. Urban PCNs in Kenya have contributed positively to improving clinical outcomes measured by patient satisfaction scores. Future research should explore broader health indicators and intervention mechanisms. Further studies are recommended to assess the impact of PCN systems on other clinical parameters, such as treatment efficacy and patient recovery rates. Urban Primary Care Networks, Time-Series Forecasting, Patient Satisfaction, Clinical Outcomes Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.