District hospitals in Senegal face challenges in cost-effectiveness analysis due to variability in financial and operational data. A time-series forecasting model was applied to historical cost and resource utilization data from Senegalese district hospitals. Robust standard errors were used to account for uncertainty. The model demonstrated an average forecast accuracy of 85% in predicting future costs, with a confidence interval indicating the reliability of these predictions. The methodology offers a robust tool for assessing and improving cost-effectiveness in Senegalese district hospitals. Further research should explore broader applications of this model across different regions and healthcare systems. District Hospitals, Cost-Effectiveness Analysis, Time-Series Forecasting, Robust Standard Errors Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Muhammadou Sylla (Thu,) studied this question.