Forecasting Yield Improvement in Ugandan District Hospitals Using Time-Series Models: A Methodological Evaluation

Ugandan district hospitals play a crucial role in healthcare delivery, but their performance metrics such as patient yield improvement are often poorly documented and forecasted. Time-series analysis was employed to model yield improvements over time. The Box-Jenkins methodology was used with an ARIMA (AutoRegressive Integrated Moving Average) model for forecasting. The ARIMA(2,1,0) model provided a forecast direction of increase in patient yield improvement by approximately 5% within the next year. Time-series models effectively predict yield improvements at Ugandan district hospitals, offering a robust methodological evaluation. Further research should explore integrating these models into hospital management systems for better resource allocation and planning. Uganda, District Hospitals, Time-Series Forecasting, Yield Improvement, ARIMA Model Treatment effect was estimated with logit(pᵢ)=β₀+β^ Xᵢ, and uncertainty reported using confidence-interval based inference.