Time-Series Forecasting Model for Clinical Outcomes in Senegalese District Hospitals Systems: A Methodological Evaluation
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| Natura: | Recurso digital |
| Lingua: | inglese |
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Zenodo
2001
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| _version_ | 1866901802727768064 |
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| author | Ndaw, Mama Diop |
| author_facet | Ndaw, Mama Diop |
| contents | <p>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.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18726504 |
| institution | Zenodo |
| language | eng |
| publishDate | 2001 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Time-Series Forecasting Model for Clinical Outcomes in Senegalese District Hospitals Systems: A Methodological Evaluation Ndaw, Mama Diop African geography Senegal district hospitals time-series analysis forecasting models clinical outcomes methodological evaluation <p>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.</p> |
| title | Time-Series Forecasting Model for Clinical Outcomes in Senegalese District Hospitals Systems: A Methodological Evaluation |
| topic | African geography Senegal district hospitals time-series analysis forecasting models clinical outcomes methodological evaluation |
| url | https://doi.org/10.5281/zenodo.18726504 |