District hospitals in Rwanda are critical healthcare providers serving large populations. However, their operational efficiency varies significantly. This research aims to evaluate and improve these systems. A time-series forecasting model will be applied to historical data from district hospitals in Rwanda for the years -. The specific model used is an ARIMA (AutoRegressive Integrated Moving Average) model, with parameters estimated using maximum likelihood estimation and robust standard errors. The application of ARIMA models revealed a significant trend in patient admissions over time, which was consistent across all districts, indicating potential for future forecasting improvements. This pattern suggests that district hospitals can anticipate demand more accurately by understanding historical trends. The use of time-series forecasting models has provided valuable insights into the operational efficiency of district hospitals in Rwanda. These findings are expected to inform policy and resource allocation decisions. Based on the findings, it is recommended that district hospital managers implement ARIMA models for predictive analytics and improve patient flow management strategies. Additionally, further research should be conducted to validate these results across different time periods. district hospitals, Rwanda, time-series forecasting, efficiency gains, ARIMA Treatment effect was estimated with logit (pᵢ) =₀+^ Xᵢ, and uncertainty reported using confidence-interval based inference.
Umuhoza et al. (Wed,) studied this question.