African Plant Pathology (Agri/Plant Science) | 12 June 2010
Forecasting Yield Improvement in Ugandan District Hospitals Using Time-Series Models: A Methodological Evaluation
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Abstract
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 $\text{logit}(p<em>i)=\beta</em>0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.