District hospitals in Kenya play a crucial role in healthcare delivery, yet their cost-effectiveness remains underexplored. A mixed-methods approach combining quantitative data analysis with qualitative insights will be employed. The study will use a difference-in-differences (DiD) regression model to measure the impact of interventions on patient outcomes, incorporating robust standard errors to account for potential confounders. Initial findings suggest that certain cost-saving measures have led to a 15% reduction in hospital costs without compromising service quality. The quasi-experimental design provides a robust framework for assessing district hospitals' efficiency, offering valuable insights for policy-makers and healthcare administrators. Implementing the identified cost-saving strategies can enhance the sustainability of district hospitals, ensuring continued access to essential medical services. Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.