This study evaluates urban primary care networks in Rwanda to assess their effectiveness on clinical outcomes. Urban primary care networks were evaluated across multiple sites. The DiD model was applied to measure clinical outcomes, accounting for potential confounders such as pre-existing patient conditions and socioeconomic factors. Uncertainty in findings is addressed through robust standard errors provided by the DiD analysis. In one of the networked urban areas, a significant improvement (p < 0. 05) was observed in patient recovery rates compared to non-networked regions. The DiD model effectively highlighted the positive impact of urban primary care networks on clinical outcomes, providing valuable insights for policy makers and healthcare administrators. Based on these findings, recommendations include scaling up successful models, investing in training for network staff, and integrating continuous quality improvement measures into operational protocols. Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Byaruhanga et al. (Sun,) studied this question.