What question did this study set out to answer?

To assess the effectiveness of a time-series forecasting model for cost predictions in Senegalese district hospitals.

March 16, 20260 citationsOpen Access

Time-Series Forecasting Model Evaluation for Cost-Effectiveness Analysis in Senegal's District Hospital Systems

MSMuhammadou SyllaAfrican Institute for Mathematical Sciences

Key Points

To assess the effectiveness of a time-series forecasting model for cost predictions in Senegalese district hospitals.
Applied a time-series forecasting model to historical data from district hospitals.
Utilized robust standard errors to manage uncertainty.
Measured forecast accuracy of the model using confidence intervals.
Achieved an average forecast accuracy of 85% for predicting future costs.
Confidence intervals indicated reliability of the predictions.
Model offers a strong framework for evaluating cost-effectiveness.

Abstract

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.

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