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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.
Afiliación
  • Ros F; Escuela Técnica Superior Ingenieros de Telecomunicación Universidad Politécnica de Madrid Madrid Spain.
  • Kush R; Elligo Health Research and Catalysis Austin Texas USA.
  • Friedman C; Department of Learning Health Sciences University of Michigan Medical School Ann Arbor Michigan USA.
  • Gil Zorzo E; Fundetec Foundation Madrid Spain.
  • Rivero Corte P; Digital Health Roster WHO, & Everis Palma de Mallorca Spain.
  • Rubin JC; Department of Learning Health Sciences University of Michigan Medical School Ann Arbor Michigan USA.
  • Sanchez B; Ministry of Science, Innovation and University Government of the Principality of Asturias Oviedo Spain.
  • Stocco P; Services Care for Elderly ASSP Cortina Cortina d'Ampezzo BL Italy.
  • Van Houweling D; Department of Learning Health Sciences University of Michigan Medical School Ann Arbor Michigan USA.
Learn Health Syst ; 5(1): e10253, 2021 Jan.
Article en En | MEDLINE | ID: mdl-33349796
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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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Learn Health Syst Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Guideline / Prognostic_studies Idioma: En Revista: Learn Health Syst Año: 2021 Tipo del documento: Article