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Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine

BACKGROUND: The COVID-19 outbreak required prompt action by health authorities around the world in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive-level decision-makers with...

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Autores principales: Geva, Gil A, Ketko, Itay, Nitecki, Maya, Simon, Shoham, Inbar, Barr, Toledo, Itay, Shapiro, Michael, Vaturi, Barak, Votta, Yoni, Filler, Daniel, Yosef, Roey, Shpitzer, Sagi A, Hir, Nabil, Peri Markovich, Michal, Shapira, Shachar, Fink, Noam, Glasberg, Elon, Furer, Ariel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437401/
https://www.ncbi.nlm.nih.gov/pubmed/34313589
http://dx.doi.org/10.2196/24295
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author Geva, Gil A
Ketko, Itay
Nitecki, Maya
Simon, Shoham
Inbar, Barr
Toledo, Itay
Shapiro, Michael
Vaturi, Barak
Votta, Yoni
Filler, Daniel
Yosef, Roey
Shpitzer, Sagi A
Hir, Nabil
Peri Markovich, Michal
Shapira, Shachar
Fink, Noam
Glasberg, Elon
Furer, Ariel
author_facet Geva, Gil A
Ketko, Itay
Nitecki, Maya
Simon, Shoham
Inbar, Barr
Toledo, Itay
Shapiro, Michael
Vaturi, Barak
Votta, Yoni
Filler, Daniel
Yosef, Roey
Shpitzer, Sagi A
Hir, Nabil
Peri Markovich, Michal
Shapira, Shachar
Fink, Noam
Glasberg, Elon
Furer, Ariel
author_sort Geva, Gil A
collection PubMed
description BACKGROUND: The COVID-19 outbreak required prompt action by health authorities around the world in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive-level decision-makers with the most actionable, pertinent, and updated data analysis to enable them to adapt their strategy swiftly and competently. OBJECTIVE: We report here the origination of a COVID-19 dedicated response in the Israel Defense Forces with the assembly of an operational Data Center for the Campaign against Coronavirus. METHODS: Spearheaded by directors with clinical, operational, and data analytics orientation, a multidisciplinary team utilized existing and newly developed platforms to collect and analyze large amounts of information on an individual level in the context of SARS-CoV-2 contraction and infection. RESULTS: Nearly 300,000 responses to daily questionnaires were recorded and were merged with other data sets to form a unified data lake. By using basic as well as advanced analytic tools ranging from simple aggregation and display of trends to data science application, we provided commanders and clinicians with access to trusted, accurate, and personalized information and tools that were designed to foster operational changes and mitigate the propagation of the pandemic. The developed tools aided in the in the identification of high-risk individuals for severe disease and resulted in a 30% decline in their attendance to their units. Moreover, the queue for laboratory examination for COVID-19 was optimized using a predictive model and resulted in a high true-positive rate of 20%, which is more than twice as high as the baseline rate (2.28%, 95% CI 1.63%-3.19%). CONCLUSIONS: In times of ambiguity and uncertainty, along with an unprecedented flux of information, health organizations may find multidisciplinary teams working to provide intelligence from diverse and rich data a key factor in providing executives relevant and actionable support for decision-making.
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spelling pubmed-84374012021-09-27 Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine Geva, Gil A Ketko, Itay Nitecki, Maya Simon, Shoham Inbar, Barr Toledo, Itay Shapiro, Michael Vaturi, Barak Votta, Yoni Filler, Daniel Yosef, Roey Shpitzer, Sagi A Hir, Nabil Peri Markovich, Michal Shapira, Shachar Fink, Noam Glasberg, Elon Furer, Ariel J Med Internet Res Viewpoint BACKGROUND: The COVID-19 outbreak required prompt action by health authorities around the world in response to a novel threat. With enormous amounts of information originating in sources with uncertain degree of validation and accuracy, it is essential to provide executive-level decision-makers with the most actionable, pertinent, and updated data analysis to enable them to adapt their strategy swiftly and competently. OBJECTIVE: We report here the origination of a COVID-19 dedicated response in the Israel Defense Forces with the assembly of an operational Data Center for the Campaign against Coronavirus. METHODS: Spearheaded by directors with clinical, operational, and data analytics orientation, a multidisciplinary team utilized existing and newly developed platforms to collect and analyze large amounts of information on an individual level in the context of SARS-CoV-2 contraction and infection. RESULTS: Nearly 300,000 responses to daily questionnaires were recorded and were merged with other data sets to form a unified data lake. By using basic as well as advanced analytic tools ranging from simple aggregation and display of trends to data science application, we provided commanders and clinicians with access to trusted, accurate, and personalized information and tools that were designed to foster operational changes and mitigate the propagation of the pandemic. The developed tools aided in the in the identification of high-risk individuals for severe disease and resulted in a 30% decline in their attendance to their units. Moreover, the queue for laboratory examination for COVID-19 was optimized using a predictive model and resulted in a high true-positive rate of 20%, which is more than twice as high as the baseline rate (2.28%, 95% CI 1.63%-3.19%). CONCLUSIONS: In times of ambiguity and uncertainty, along with an unprecedented flux of information, health organizations may find multidisciplinary teams working to provide intelligence from diverse and rich data a key factor in providing executives relevant and actionable support for decision-making. JMIR Publications 2021-09-10 /pmc/articles/PMC8437401/ /pubmed/34313589 http://dx.doi.org/10.2196/24295 Text en ©Gil A Geva, Itay Ketko, Maya Nitecki, Shoham Simon, Barr Inbar, Itay Toledo, Michael Shapiro, Barak Vaturi, Yoni Votta, Daniel Filler, Roey Yosef, Sagi A Shpitzer, Nabil Hir, Michal Peri Markovich, Shachar Shapira, Noam Fink, Elon Glasberg, Ariel Furer. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 10.09.2021. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Viewpoint
Geva, Gil A
Ketko, Itay
Nitecki, Maya
Simon, Shoham
Inbar, Barr
Toledo, Itay
Shapiro, Michael
Vaturi, Barak
Votta, Yoni
Filler, Daniel
Yosef, Roey
Shpitzer, Sagi A
Hir, Nabil
Peri Markovich, Michal
Shapira, Shachar
Fink, Noam
Glasberg, Elon
Furer, Ariel
Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title_full Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title_fullStr Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title_full_unstemmed Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title_short Data Empowerment of Decision-Makers in an Era of a Pandemic: Intersection of “Classic” and Artificial Intelligence in the Service of Medicine
title_sort data empowerment of decision-makers in an era of a pandemic: intersection of “classic” and artificial intelligence in the service of medicine
topic Viewpoint
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8437401/
https://www.ncbi.nlm.nih.gov/pubmed/34313589
http://dx.doi.org/10.2196/24295
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