Methodological Evaluation of District Hospitals Systems in Tanzania Using Time-Series Forecasting Models for Clinical Outcomes Measurement
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| Auteurs principaux: | , , |
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2011
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| _version_ | 1866901924733779968 |
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| author | Mwanza, Mwanzika Kinyanjui, Kamau Tukiri, Tuyile |
| author_facet | Mwanza, Mwanzika Kinyanjui, Kamau Tukiri, Tuyile |
| contents | <p>District hospitals in Tanzania face challenges in managing clinical outcomes due to variability in healthcare systems. A systematic review of existing studies on district hospital performance, focusing on data sources, analytical methods, and clinical outcome measures. The study employed meta-analytic techniques to identify and synthesize findings. The analysis revealed that current approaches often lack robust statistical models for forecasting outcomes, leading to inconsistent results across different hospitals. A time-series forecasting model based on ARIMA (AutoRegressive Integrated Moving Average) was found effective in predicting clinical outcomes with a confidence interval of ±5%. The use of the proposed ARIMA-based forecasting model is recommended for district hospitals to enhance the accuracy and consistency of clinical outcome assessments. 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_18930904 |
| institution | Zenodo |
| language | eng |
| publishDate | 2011 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Methodological Evaluation of District Hospitals Systems in Tanzania Using Time-Series Forecasting Models for Clinical Outcomes Measurement Mwanza, Mwanzika Kinyanjui, Kamau Tukiri, Tuyile Tanzania District Hospitals Clinical Outcomes Time-Series Analysis Forecasting Models Healthcare Systems Methodology <p>District hospitals in Tanzania face challenges in managing clinical outcomes due to variability in healthcare systems. A systematic review of existing studies on district hospital performance, focusing on data sources, analytical methods, and clinical outcome measures. The study employed meta-analytic techniques to identify and synthesize findings. The analysis revealed that current approaches often lack robust statistical models for forecasting outcomes, leading to inconsistent results across different hospitals. A time-series forecasting model based on ARIMA (AutoRegressive Integrated Moving Average) was found effective in predicting clinical outcomes with a confidence interval of ±5%. The use of the proposed ARIMA-based forecasting model is recommended for district hospitals to enhance the accuracy and consistency of clinical outcome assessments. 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 | Methodological Evaluation of District Hospitals Systems in Tanzania Using Time-Series Forecasting Models for Clinical Outcomes Measurement |
| topic | Tanzania District Hospitals Clinical Outcomes Time-Series Analysis Forecasting Models Healthcare Systems Methodology |
| url | https://doi.org/10.5281/zenodo.18930904 |