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Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings

While the importance of mHealth scale-up has been broadly emphasized in the mHealth community, it is necessary to guide scale up efforts and investment in ways to help achieve the mortality reduction targets set by global calls to action such as the Millennium Development Goals, not merely to expand...

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Detalles Bibliográficos
Autores principales: Jo, Youngji, Labrique, Alain B., Lefevre, Amnesty E., Mehl, Garrett, Pfaff, Teresa, Walker, Neff, Friberg, Ingrid K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4094557/
https://www.ncbi.nlm.nih.gov/pubmed/25014008
http://dx.doi.org/10.1371/journal.pone.0102224
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author Jo, Youngji
Labrique, Alain B.
Lefevre, Amnesty E.
Mehl, Garrett
Pfaff, Teresa
Walker, Neff
Friberg, Ingrid K.
author_facet Jo, Youngji
Labrique, Alain B.
Lefevre, Amnesty E.
Mehl, Garrett
Pfaff, Teresa
Walker, Neff
Friberg, Ingrid K.
author_sort Jo, Youngji
collection PubMed
description While the importance of mHealth scale-up has been broadly emphasized in the mHealth community, it is necessary to guide scale up efforts and investment in ways to help achieve the mortality reduction targets set by global calls to action such as the Millennium Development Goals, not merely to expand programs. We used the Lives Saved Tool (LiST)–an evidence-based modeling software–to identify priority areas for maternal and neonatal health services, by formulating six individual and combined interventions scenarios for two countries, Bangladesh and Uganda. Our findings show that skilled birth attendance and increased facility delivery as targets for mHealth strategies are likely to provide the biggest mortality impact relative to other intervention scenarios. Although further validation of this model is desirable, tools such as LiST can help us leverage the benefit of mHealth by articulating the most appropriate delivery points in the continuum of care to save lives.
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spelling pubmed-40945572014-07-15 Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings Jo, Youngji Labrique, Alain B. Lefevre, Amnesty E. Mehl, Garrett Pfaff, Teresa Walker, Neff Friberg, Ingrid K. PLoS One Research Article While the importance of mHealth scale-up has been broadly emphasized in the mHealth community, it is necessary to guide scale up efforts and investment in ways to help achieve the mortality reduction targets set by global calls to action such as the Millennium Development Goals, not merely to expand programs. We used the Lives Saved Tool (LiST)–an evidence-based modeling software–to identify priority areas for maternal and neonatal health services, by formulating six individual and combined interventions scenarios for two countries, Bangladesh and Uganda. Our findings show that skilled birth attendance and increased facility delivery as targets for mHealth strategies are likely to provide the biggest mortality impact relative to other intervention scenarios. Although further validation of this model is desirable, tools such as LiST can help us leverage the benefit of mHealth by articulating the most appropriate delivery points in the continuum of care to save lives. Public Library of Science 2014-07-11 /pmc/articles/PMC4094557/ /pubmed/25014008 http://dx.doi.org/10.1371/journal.pone.0102224 Text en © 2014 Jo et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Jo, Youngji
Labrique, Alain B.
Lefevre, Amnesty E.
Mehl, Garrett
Pfaff, Teresa
Walker, Neff
Friberg, Ingrid K.
Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title_full Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title_fullStr Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title_full_unstemmed Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title_short Using the Lives Saved Tool (LiST) to Model mHealth Impact on Neonatal Survival in Resource-Limited Settings
title_sort using the lives saved tool (list) to model mhealth impact on neonatal survival in resource-limited settings
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4094557/
https://www.ncbi.nlm.nih.gov/pubmed/25014008
http://dx.doi.org/10.1371/journal.pone.0102224
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