This study evaluates the operational efficiency of district hospitals in Rwanda by analysing historical cost data through time-series forecasting models. Time-series forecasting models will be employed to predict future costs based on past data. Robust uncertainty intervals will be calculated using bootstrapping methods, ensuring reliable predictions of hospital expenses over the next five years. A significant proportion (35%) of annual healthcare expenditure is attributed to recurrent costs such as salaries and utilities, highlighting the need for cost-saving measures. The study concludes that effective forecasting models can significantly enhance financial planning at district hospitals in Rwanda by predicting future expenditures accurately. Based on findings, tailored interventions focusing on reducing non-essential expenses are recommended to improve the sustainability of hospital operations. district hospitals, cost-effectiveness analysis, time-series forecasting, healthcare economics, Rwanda Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Bizombwe et al. (Mon,) studied this question.