Bayesian Hierarchical Model for Measuring Clinical Outcomes in District Hospitals Systems of Senegal

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Autori principali: Diop, Amadou, Ngom, Mariama, Ndiaye, Fatoumata, Sow, Cheikh
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2013
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author Diop, Amadou
Ngom, Mariama
Ndiaye, Fatoumata
Sow, Cheikh
author_facet Diop, Amadou
Ngom, Mariama
Ndiaye, Fatoumata
Sow, Cheikh
contents <p>Clinical outcomes in district hospitals systems of Senegal have been under surveillance to improve patient care and resource allocation. A Bayesian hierarchical model was constructed using data from district hospitals in Senegal. The model accounts for variability between hospitals and within each hospital over time, incorporating uncertainty through credible intervals around estimated parameters. The model identified significant variations in clinical outcomes among districts, with certain regions showing a 15% improvement in treatment success rates compared to previous benchmarks. The Bayesian hierarchical model demonstrated enhanced accuracy and reliability in assessing district hospital performance, providing actionable insights for policy makers. Policy recommendations should prioritise resource allocation towards areas where clinical outcomes are notably below average. Bayesian Hierarchical Model, District Hospitals, Clinical Outcomes, 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_18980269
institution Zenodo
language eng
publishDate 2013
publisher Zenodo
record_format zenodo
spellingShingle Bayesian Hierarchical Model for Measuring Clinical Outcomes in District Hospitals Systems of Senegal
Diop, Amadou
Ngom, Mariama
Ndiaye, Fatoumata
Sow, Cheikh
Sub-Saharan
Bayesian
Hierarchical
Markov Chain Monte Carlo
Spatial
Epidemiology
Random Effects
<p>Clinical outcomes in district hospitals systems of Senegal have been under surveillance to improve patient care and resource allocation. A Bayesian hierarchical model was constructed using data from district hospitals in Senegal. The model accounts for variability between hospitals and within each hospital over time, incorporating uncertainty through credible intervals around estimated parameters. The model identified significant variations in clinical outcomes among districts, with certain regions showing a 15% improvement in treatment success rates compared to previous benchmarks. The Bayesian hierarchical model demonstrated enhanced accuracy and reliability in assessing district hospital performance, providing actionable insights for policy makers. Policy recommendations should prioritise resource allocation towards areas where clinical outcomes are notably below average. Bayesian Hierarchical Model, District Hospitals, Clinical Outcomes, 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 Bayesian Hierarchical Model for Measuring Clinical Outcomes in District Hospitals Systems of Senegal
topic Sub-Saharan
Bayesian
Hierarchical
Markov Chain Monte Carlo
Spatial
Epidemiology
Random Effects
url https://doi.org/10.5281/zenodo.18980269