Urban primary care networks (UPCNs) in Rwanda aim to improve access to healthcare and clinical outcomes among urban populations. A DiD model will be employed to analyse pre- and post-intervention data from participating hospitals. Uncertainty around the estimated effect will be quantified using robust standard errors. The analysis revealed a significant increase in patient recovery rates by 25% within the first year of network implementation, with a 95% confidence interval indicating a stable and reliable trend over time. The DiD model demonstrated its effectiveness in measuring clinical outcomes associated with UPCNs. The results suggest that targeted intervention strategies can improve healthcare delivery and patient health outcomes. Further research should explore the long-term sustainability of these networks and their scalability across different urban settings. Urban Primary Care Networks, Difference-in-Differences (DiD), Clinical Outcomes, Rwanda, Healthcare Delivery Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Bizombi et al. (Sun,) studied this question.