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Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach

Covid‐19 has already taught us that the greatest public health challenges of our generation will show no respect for national boundaries, will impact lives and health of people of all nations, and will affect economies and quality of life in unprecedented ways. The types of rapid learning envisioned...

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Autores principales: Ros, Francisco, Kush, Rebecca, Friedman, Charles, Gil Zorzo, Esther, Rivero Corte, Pablo, Rubin, Joshua C., Sanchez, Borja, Stocco, Paolo, Van Houweling, Douglas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744897/
https://www.ncbi.nlm.nih.gov/pubmed/33349796
http://dx.doi.org/10.1002/lrh2.10253
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author Ros, Francisco
Kush, Rebecca
Friedman, Charles
Gil Zorzo, Esther
Rivero Corte, Pablo
Rubin, Joshua C.
Sanchez, Borja
Stocco, Paolo
Van Houweling, Douglas
author_facet Ros, Francisco
Kush, Rebecca
Friedman, Charles
Gil Zorzo, Esther
Rivero Corte, Pablo
Rubin, Joshua C.
Sanchez, Borja
Stocco, Paolo
Van Houweling, Douglas
author_sort Ros, Francisco
collection PubMed
description Covid‐19 has already taught us that the greatest public health challenges of our generation will show no respect for national boundaries, will impact lives and health of people of all nations, and will affect economies and quality of life in unprecedented ways. The types of rapid learning envisioned to address Covid‐19 and future public health crises require a systems approach that enables sharing of data and lessons learned at scale. Agreement on a systems approach augmented by technology and standards will be foundational to making such learning meaningful and to ensuring its scientific integrity. With this purpose in mind, a group of individuals from Spain, Italy, and the United States have formed a transatlantic collaboration, with the aim of generating a proposed comprehensive standards‐based systems approach and data‐driven framework for collection, management, and analysis of high‐quality data. This framework will inform decisions in managing clinical responses and social measures to overcome the Covid‐19 global pandemic and to prepare for future public health crises. We first argue that standardized data of the type now common in global regulated clinical research is the essential fuel that will power a global system for addressing (and preventing) current and future pandemics. We then present a blueprint for a system that will put these data to use in driving a range of key decisions. In the context of this system, we describe and categorize the specific types of data the system will require for different purposes and document the standards currently in use for each of these categories in the three nations participating in this work. In so doing, we anticipate some of the challenges to harmonizing these data but also suggest opportunities for further global standardization and harmonization. While we have scaled this transnational effort to three nations, we hope to stimulate an international dialogue with a culmination of realizing such a system.
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spelling pubmed-77448972020-12-17 Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach Ros, Francisco Kush, Rebecca Friedman, Charles Gil Zorzo, Esther Rivero Corte, Pablo Rubin, Joshua C. Sanchez, Borja Stocco, Paolo Van Houweling, Douglas Learn Health Syst Technical Reports Covid‐19 has already taught us that the greatest public health challenges of our generation will show no respect for national boundaries, will impact lives and health of people of all nations, and will affect economies and quality of life in unprecedented ways. The types of rapid learning envisioned to address Covid‐19 and future public health crises require a systems approach that enables sharing of data and lessons learned at scale. Agreement on a systems approach augmented by technology and standards will be foundational to making such learning meaningful and to ensuring its scientific integrity. With this purpose in mind, a group of individuals from Spain, Italy, and the United States have formed a transatlantic collaboration, with the aim of generating a proposed comprehensive standards‐based systems approach and data‐driven framework for collection, management, and analysis of high‐quality data. This framework will inform decisions in managing clinical responses and social measures to overcome the Covid‐19 global pandemic and to prepare for future public health crises. We first argue that standardized data of the type now common in global regulated clinical research is the essential fuel that will power a global system for addressing (and preventing) current and future pandemics. We then present a blueprint for a system that will put these data to use in driving a range of key decisions. In the context of this system, we describe and categorize the specific types of data the system will require for different purposes and document the standards currently in use for each of these categories in the three nations participating in this work. In so doing, we anticipate some of the challenges to harmonizing these data but also suggest opportunities for further global standardization and harmonization. While we have scaled this transnational effort to three nations, we hope to stimulate an international dialogue with a culmination of realizing such a system. John Wiley and Sons Inc. 2020-12-06 /pmc/articles/PMC7744897/ /pubmed/33349796 http://dx.doi.org/10.1002/lrh2.10253 Text en © 2020 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of the University of Michigan. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Technical Reports
Ros, Francisco
Kush, Rebecca
Friedman, Charles
Gil Zorzo, Esther
Rivero Corte, Pablo
Rubin, Joshua C.
Sanchez, Borja
Stocco, Paolo
Van Houweling, Douglas
Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title_full Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title_fullStr Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title_full_unstemmed Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title_short Addressing the Covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
title_sort addressing the covid‐19 pandemic and future public health challenges through global collaboration and a data‐driven systems approach
topic Technical Reports
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7744897/
https://www.ncbi.nlm.nih.gov/pubmed/33349796
http://dx.doi.org/10.1002/lrh2.10253
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