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The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic

In Ontario on March 16, 2020, a directive was issued to all acute care hospitals to halt nonessential procedures in anticipation of a potential surge in COVID-19 patients. This included scheduled outpatient cardiac surgical and interventional procedures that required the use of intensive care units,...

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Autores principales: Tam, Derrick Y., Naimark, David, Natarajan, Madhu K., Woodward, Graham, Oakes, Garth, Rahal, Mirna, Barrett, Kali, Khan, Yasin A., Ximenes, Raphael, Mac, Stephen, Sander, Beate, Wijeysundera, Harindra C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Canadian Cardiovascular Society. Published by Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241392/
https://www.ncbi.nlm.nih.gov/pubmed/32447059
http://dx.doi.org/10.1016/j.cjca.2020.05.024
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author Tam, Derrick Y.
Naimark, David
Natarajan, Madhu K.
Woodward, Graham
Oakes, Garth
Rahal, Mirna
Barrett, Kali
Khan, Yasin A.
Ximenes, Raphael
Mac, Stephen
Sander, Beate
Wijeysundera, Harindra C.
author_facet Tam, Derrick Y.
Naimark, David
Natarajan, Madhu K.
Woodward, Graham
Oakes, Garth
Rahal, Mirna
Barrett, Kali
Khan, Yasin A.
Ximenes, Raphael
Mac, Stephen
Sander, Beate
Wijeysundera, Harindra C.
author_sort Tam, Derrick Y.
collection PubMed
description In Ontario on March 16, 2020, a directive was issued to all acute care hospitals to halt nonessential procedures in anticipation of a potential surge in COVID-19 patients. This included scheduled outpatient cardiac surgical and interventional procedures that required the use of intensive care units, ventilators, and skilled critical care personnel, given that these procedures would draw from the same pool of resources required for critically ill COVID-19 patients. We adapted the COVID-19 Resource Estimator (CORE) decision analytic model by adding a cardiac component to determine the impact of various policy decisions on the incremental waitlist growth and estimated waitlist mortality for 3 key groups of cardiovascular disease patients: coronary artery disease, valvular heart disease, and arrhythmias. We provided predictions based on COVID-19 epidemiology available in real-time, in 3 phases. First, in the initial crisis phase, in a worst case scenario, we showed that the potential number of waitlist related cardiac deaths would be orders of magnitude less than those who would die of COVID-19 if critical cardiac care resources were diverted to the care of COVID-19 patients. Second, with better local epidemiology data, we predicted that across 5 regions of Ontario, there may be insufficient resources to resume all elective outpatient cardiac procedures. Finally in the recovery phase, we showed that the estimated incremental growth in waitlist for all cardiac procedures is likely substantial. These outputs informed timely data-driven decisions during the COVID-19 pandemic regarding the provision of cardiovascular care.
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spelling pubmed-72413922020-05-21 The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic Tam, Derrick Y. Naimark, David Natarajan, Madhu K. Woodward, Graham Oakes, Garth Rahal, Mirna Barrett, Kali Khan, Yasin A. Ximenes, Raphael Mac, Stephen Sander, Beate Wijeysundera, Harindra C. Can J Cardiol Training/Practice In Ontario on March 16, 2020, a directive was issued to all acute care hospitals to halt nonessential procedures in anticipation of a potential surge in COVID-19 patients. This included scheduled outpatient cardiac surgical and interventional procedures that required the use of intensive care units, ventilators, and skilled critical care personnel, given that these procedures would draw from the same pool of resources required for critically ill COVID-19 patients. We adapted the COVID-19 Resource Estimator (CORE) decision analytic model by adding a cardiac component to determine the impact of various policy decisions on the incremental waitlist growth and estimated waitlist mortality for 3 key groups of cardiovascular disease patients: coronary artery disease, valvular heart disease, and arrhythmias. We provided predictions based on COVID-19 epidemiology available in real-time, in 3 phases. First, in the initial crisis phase, in a worst case scenario, we showed that the potential number of waitlist related cardiac deaths would be orders of magnitude less than those who would die of COVID-19 if critical cardiac care resources were diverted to the care of COVID-19 patients. Second, with better local epidemiology data, we predicted that across 5 regions of Ontario, there may be insufficient resources to resume all elective outpatient cardiac procedures. Finally in the recovery phase, we showed that the estimated incremental growth in waitlist for all cardiac procedures is likely substantial. These outputs informed timely data-driven decisions during the COVID-19 pandemic regarding the provision of cardiovascular care. Canadian Cardiovascular Society. Published by Elsevier Inc. 2020-08 2020-05-21 /pmc/articles/PMC7241392/ /pubmed/32447059 http://dx.doi.org/10.1016/j.cjca.2020.05.024 Text en © 2020 Canadian Cardiovascular Society. Published by 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 Training/Practice
Tam, Derrick Y.
Naimark, David
Natarajan, Madhu K.
Woodward, Graham
Oakes, Garth
Rahal, Mirna
Barrett, Kali
Khan, Yasin A.
Ximenes, Raphael
Mac, Stephen
Sander, Beate
Wijeysundera, Harindra C.
The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title_full The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title_fullStr The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title_full_unstemmed The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title_short The Use of Decision Modelling to Inform Timely Policy Decisions on Cardiac Resource Capacity During the COVID-19 Pandemic
title_sort use of decision modelling to inform timely policy decisions on cardiac resource capacity during the covid-19 pandemic
topic Training/Practice
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241392/
https://www.ncbi.nlm.nih.gov/pubmed/32447059
http://dx.doi.org/10.1016/j.cjca.2020.05.024
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