The healthcare landscape in Rwanda is characterized by a fragmented system of district hospitals, each operating independently with varying levels of resources and infrastructure. A mixed-methods approach combining quantitative surveys and qualitative interviews was employed. The study used a difference-in-differences (DiD) model for data analysis, with robust standard errors accounting for potential confounding factors. The DiD model revealed a significant increase in adoption rates from baseline to post-intervention across all district hospitals, indicating the effectiveness of the intervention. This study underscores the need for further research on scalability and sustainability of healthcare reforms within Rwanda’s district hospital systems. District health authorities should prioritise continuous training programmes for medical staff and establish standardised protocols to enhance the consistency and quality of care across all hospitals. Quasi-Experimental Design, Adoption Rates, District Hospitals, Rwanda Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.