Time-Series Forecasting Model for Evaluating Maternal Care Facilities in Ghana: A Methodological Study

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Autori principali: Anyakwa, Kofi, Awuku, Yaw, Amofa, Adwoa
Natura: Recurso digital
Lingua:inglese
Pubblicazione: Zenodo 2008
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author Anyakwa, Kofi
Awuku, Yaw
Amofa, Adwoa
author_facet Anyakwa, Kofi
Awuku, Yaw
Amofa, Adwoa
contents <p>Maternal care facilities in Ghana are crucial for improving maternal health outcomes. However, there is a need to evaluate and improve these systems. A time-series forecasting model was developed using data from existing maternal care facilities. The model's effectiveness was tested through cross-validation techniques, with uncertainty quantified via robust standard errors. The forecasting model showed an average prediction error of ±5% for key clinical outcome measures such as neonatal mortality rates and post-partum hemorrhage incidence. The time-series forecasting model demonstrated the potential to predict clinical outcomes in maternal care facilities with reasonable accuracy, providing a tool for system evaluation and improvement. Maternal care facilities should use this model to forecast clinical outcomes and identify areas needing intervention. Regular updates of the model are recommended based on new data. maternal health, forecasting models, Ghana, neonatal mortality, post-partum hemorrhage 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_18862185
institution Zenodo
language eng
publishDate 2008
publisher Zenodo
record_format zenodo
spellingShingle Time-Series Forecasting Model for Evaluating Maternal Care Facilities in Ghana: A Methodological Study
Anyakwa, Kofi
Awuku, Yaw
Amofa, Adwoa
Ghanaian
MaternalHealth
TimeSeries
Epidemiology
Methodology
Evaluation
Forecasting
<p>Maternal care facilities in Ghana are crucial for improving maternal health outcomes. However, there is a need to evaluate and improve these systems. A time-series forecasting model was developed using data from existing maternal care facilities. The model's effectiveness was tested through cross-validation techniques, with uncertainty quantified via robust standard errors. The forecasting model showed an average prediction error of ±5% for key clinical outcome measures such as neonatal mortality rates and post-partum hemorrhage incidence. The time-series forecasting model demonstrated the potential to predict clinical outcomes in maternal care facilities with reasonable accuracy, providing a tool for system evaluation and improvement. Maternal care facilities should use this model to forecast clinical outcomes and identify areas needing intervention. Regular updates of the model are recommended based on new data. maternal health, forecasting models, Ghana, neonatal mortality, post-partum hemorrhage 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 Evaluating Maternal Care Facilities in Ghana: A Methodological Study
topic Ghanaian
MaternalHealth
TimeSeries
Epidemiology
Methodology
Evaluation
Forecasting
url https://doi.org/10.5281/zenodo.18862185