Clinical outcomes in Rwanda's regional monitoring networks are influenced by a variety of factors including healthcare quality and accessibility. A comprehensive search strategy was employed to identify relevant studies. Studies were assessed based on their methodologies, including statistical models such as fixed effects regression (FE) and random effects regression (RE). Panel data analysis revealed a significant positive relationship between healthcare quality indicators and patient outcomes in the regions studied. Fixed effects models provided more accurate estimates of treatment effects compared to random effects models, with robust standard errors indicating reliable results. Future research should consider implementing mixed-effects models that account for both fixed and random effects to enhance the precision of clinical outcome assessments. Model estimation used $\hat{\theta}=argmin_{\theta}\sum_i\ell(y_i,f_\theta(x_i))+\lambda\lVert\theta\rVert_2^2$, with performance evaluated using out-of-sample error.