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Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions
Maternal, fetal, and neonatal mortality disproportionately impact low- and middle-income countries, and many current interventions that can save lives are often not available nor appropriate for these settings. Maternal and Neonatal Directed Assessment of Technologies (MANDATE) is a mathematical mod...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Global Health: Science and Practice
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5752604/ https://www.ncbi.nlm.nih.gov/pubmed/29284695 http://dx.doi.org/10.9745/GHSP-D-16-00174 |
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author | Jones-Hepler, Bonnie Moran, Katelin Griffin, Jennifer McClure, Elizabeth M Rouse, Doris Barbosa, Carolina MacGuire, Emily Robbins, Elizabeth Goldenberg, Robert L |
author_facet | Jones-Hepler, Bonnie Moran, Katelin Griffin, Jennifer McClure, Elizabeth M Rouse, Doris Barbosa, Carolina MacGuire, Emily Robbins, Elizabeth Goldenberg, Robert L |
author_sort | Jones-Hepler, Bonnie |
collection | PubMed |
description | Maternal, fetal, and neonatal mortality disproportionately impact low- and middle-income countries, and many current interventions that can save lives are often not available nor appropriate for these settings. Maternal and Neonatal Directed Assessment of Technologies (MANDATE) is a mathematical model designed to evaluate which interventions have the greatest potential to save maternal, fetal, and neonatal lives saved in sub-Saharan Africa and India. The MANDATE decision-support model includes interventions such as preventive interventions, diagnostics, treatments, and transfers to different care settings to compare the relative impact of different interventions on mortality outcomes. The model is calibrated and validated based on historical and current rates of disease in sub-Saharan Africa and India. In addition, each maternal, fetal, or newborn condition included in MANDATE considers disease rates specific to sub-Saharan Africa and India projected to intervention rates similar to those seen in high-income countries. Limitations include variance in quality of data to inform the estimates and generalizability of findings of the effectiveness of the interventions. The model serves as a valuable resource to compare the potential impact of multiple interventions, which could help reduce maternal, fetal, and neonatal mortality in low-resource settings. The user should be aware of assumptions in evaluating the model and interpret results accordingly. |
format | Online Article Text |
id | pubmed-5752604 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Global Health: Science and Practice |
record_format | MEDLINE/PubMed |
spelling | pubmed-57526042018-01-10 Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions Jones-Hepler, Bonnie Moran, Katelin Griffin, Jennifer McClure, Elizabeth M Rouse, Doris Barbosa, Carolina MacGuire, Emily Robbins, Elizabeth Goldenberg, Robert L Glob Health Sci Pract Original Article Maternal, fetal, and neonatal mortality disproportionately impact low- and middle-income countries, and many current interventions that can save lives are often not available nor appropriate for these settings. Maternal and Neonatal Directed Assessment of Technologies (MANDATE) is a mathematical model designed to evaluate which interventions have the greatest potential to save maternal, fetal, and neonatal lives saved in sub-Saharan Africa and India. The MANDATE decision-support model includes interventions such as preventive interventions, diagnostics, treatments, and transfers to different care settings to compare the relative impact of different interventions on mortality outcomes. The model is calibrated and validated based on historical and current rates of disease in sub-Saharan Africa and India. In addition, each maternal, fetal, or newborn condition included in MANDATE considers disease rates specific to sub-Saharan Africa and India projected to intervention rates similar to those seen in high-income countries. Limitations include variance in quality of data to inform the estimates and generalizability of findings of the effectiveness of the interventions. The model serves as a valuable resource to compare the potential impact of multiple interventions, which could help reduce maternal, fetal, and neonatal mortality in low-resource settings. The user should be aware of assumptions in evaluating the model and interpret results accordingly. Global Health: Science and Practice 2017-12-28 /pmc/articles/PMC5752604/ /pubmed/29284695 http://dx.doi.org/10.9745/GHSP-D-16-00174 Text en © Jones-Hepler et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly cited. To view a copy of the license, visit http://creativecommons.org/licenses/by/4.0/. When linking to this article, please use the following permanent link: https://doi.org/10.9745/GHSP-D-16-00174 |
spellingShingle | Original Article Jones-Hepler, Bonnie Moran, Katelin Griffin, Jennifer McClure, Elizabeth M Rouse, Doris Barbosa, Carolina MacGuire, Emily Robbins, Elizabeth Goldenberg, Robert L Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title | Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title_full | Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title_fullStr | Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title_full_unstemmed | Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title_short | Maternal and Neonatal Directed Assessment of Technologies (MANDATE): Methods and Assumptions for a Predictive Model for Maternal, Fetal, and Neonatal Mortality Interventions |
title_sort | maternal and neonatal directed assessment of technologies (mandate): methods and assumptions for a predictive model for maternal, fetal, and neonatal mortality interventions |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5752604/ https://www.ncbi.nlm.nih.gov/pubmed/29284695 http://dx.doi.org/10.9745/GHSP-D-16-00174 |
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