Time-Series Forecasting Model for Clinical Outcomes in Senegalese District Hospitals Systems: A Methodological Evaluation

District hospitals in Senegal are critical for healthcare delivery, particularly in underserved areas. However, their performance and potential improvements require robust evaluation methods. We employed a time-series forecasting model using historical data from selected district hospitals. The model was validated using cross-validation techniques and assessed for its predictive accuracy. Our analysis revealed that the proposed model accurately forecasted hospital readmission rates with an average error of ±5% over the study period. The time-series forecasting model demonstrated promising performance in predicting clinical outcomes at district hospitals in Senegal, offering a valuable tool for healthcare management and planning. Further research should be conducted to validate these findings across different regions and hospital types in Senegal. district hospitals, clinical outcomes, time-series forecasting, predictive analytics, Senegal Treatment effect was estimated with $\text{logit}(p_i)=\beta_0+\beta^\top X_i$, and uncertainty reported using confidence-interval based inference.