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Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic
The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586929/ https://www.ncbi.nlm.nih.gov/pubmed/33129176 http://dx.doi.org/10.1016/j.hjdsi.2020.100493 |
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author | Lai, Lucinda Wittbold, Kelley A. Dadabhoy, Farah Z. Sato, Rintaro Landman, Adam B. Schwamm, Lee H. He, Shuhan Patel, Rajesh Wei, Nancy Zuccotti, Gianna Lennes, Inga T. Medina, Danika Sequist, Thomas D. Bomba, Garrett Keschner, Yonatan G. Zhang, Haipeng (Mark) |
author_facet | Lai, Lucinda Wittbold, Kelley A. Dadabhoy, Farah Z. Sato, Rintaro Landman, Adam B. Schwamm, Lee H. He, Shuhan Patel, Rajesh Wei, Nancy Zuccotti, Gianna Lennes, Inga T. Medina, Danika Sequist, Thomas D. Bomba, Garrett Keschner, Yonatan G. Zhang, Haipeng (Mark) |
author_sort | Lai, Lucinda |
collection | PubMed |
description | The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy. |
format | Online Article Text |
id | pubmed-7586929 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75869292020-10-27 Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic Lai, Lucinda Wittbold, Kelley A. Dadabhoy, Farah Z. Sato, Rintaro Landman, Adam B. Schwamm, Lee H. He, Shuhan Patel, Rajesh Wei, Nancy Zuccotti, Gianna Lennes, Inga T. Medina, Danika Sequist, Thomas D. Bomba, Garrett Keschner, Yonatan G. Zhang, Haipeng (Mark) Healthc (Amst) Article The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy. Elsevier Inc. 2020-12 2020-10-26 /pmc/articles/PMC7586929/ /pubmed/33129176 http://dx.doi.org/10.1016/j.hjdsi.2020.100493 Text en © 2020 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Lai, Lucinda Wittbold, Kelley A. Dadabhoy, Farah Z. Sato, Rintaro Landman, Adam B. Schwamm, Lee H. He, Shuhan Patel, Rajesh Wei, Nancy Zuccotti, Gianna Lennes, Inga T. Medina, Danika Sequist, Thomas D. Bomba, Garrett Keschner, Yonatan G. Zhang, Haipeng (Mark) Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title | Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title_full | Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title_fullStr | Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title_full_unstemmed | Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title_short | Digital triage: Novel strategies for population health management in response to the COVID-19 pandemic |
title_sort | digital triage: novel strategies for population health management in response to the covid-19 pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586929/ https://www.ncbi.nlm.nih.gov/pubmed/33129176 http://dx.doi.org/10.1016/j.hjdsi.2020.100493 |
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