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Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia

OBJECTIVE: There is a coronavirus disease 2019 (COVID-19) pandemic. We aimed to describe the characteristics of patients transported by the Royal Flying Doctor Service (RFDS) for confirmed or suspected COVID-19 and to investigate the surge capacity of and operational implications for the RFDS in dea...

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Autores principales: Gardiner, Fergus W., Johns, Hannah, Bishop, Lara, Churilov, Leonid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Air Medical Journal Associates. Published by Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229980/
https://www.ncbi.nlm.nih.gov/pubmed/32425475
http://dx.doi.org/10.1016/j.amj.2020.05.011
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author Gardiner, Fergus W.
Johns, Hannah
Bishop, Lara
Churilov, Leonid
author_facet Gardiner, Fergus W.
Johns, Hannah
Bishop, Lara
Churilov, Leonid
author_sort Gardiner, Fergus W.
collection PubMed
description OBJECTIVE: There is a coronavirus disease 2019 (COVID-19) pandemic. We aimed to describe the characteristics of patients transported by the Royal Flying Doctor Service (RFDS) for confirmed or suspected COVID-19 and to investigate the surge capacity of and operational implications for the RFDS in dealing with COVID-19. METHODS: This was a prospective cohort study. To determine the characteristics of patients transported for confirmed or suspected COVID-19, we included patient data from February 2, 2020, to May 6, 2020. To investigate the surge capacity and operational implications for the RFDS in dealing with COVID-19, we built and validated an interactive operations area-level discrete event simulation decision support model underpinned by RFDS air medical activity data from 2015 to 2019 (4 years). This model was subsequently used in a factorial in silico experiment to systematically investigate both the supply of RFDS air medical services and the increased rates of demand for these services for diseases of the respiratory system. RESULTS: The RFDS conducted 291 patient episodes of care for confirmed or suspected COVID-19. This included 288 separate patients, including 136 men and 119 women (sex missing = 33), with a median age of 62.0 years (interquartile range, 43.5-74.9 years). The simulation decision support model we developed is capable of providing dynamic and real-time support for RFDS decision makers in understanding the system's performance under uncertain COVID-19 demand. With increased COVID-19–related demand, the ability of the RFDS to cope will be driven by the number of aircraft available. The simulation model provided each aviation section with estimated numbers of aircraft required to meet a range of anticipated demands. CONCLUSION: Despite the lack of certainty in the actual level of COVID-19–related demand for RFDS services, modeling demonstrates that the robustness of meeting such demand increases with the number of operational and medically staffed aircraft.
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spelling pubmed-72299802020-05-18 Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia Gardiner, Fergus W. Johns, Hannah Bishop, Lara Churilov, Leonid Air Med J Original Research OBJECTIVE: There is a coronavirus disease 2019 (COVID-19) pandemic. We aimed to describe the characteristics of patients transported by the Royal Flying Doctor Service (RFDS) for confirmed or suspected COVID-19 and to investigate the surge capacity of and operational implications for the RFDS in dealing with COVID-19. METHODS: This was a prospective cohort study. To determine the characteristics of patients transported for confirmed or suspected COVID-19, we included patient data from February 2, 2020, to May 6, 2020. To investigate the surge capacity and operational implications for the RFDS in dealing with COVID-19, we built and validated an interactive operations area-level discrete event simulation decision support model underpinned by RFDS air medical activity data from 2015 to 2019 (4 years). This model was subsequently used in a factorial in silico experiment to systematically investigate both the supply of RFDS air medical services and the increased rates of demand for these services for diseases of the respiratory system. RESULTS: The RFDS conducted 291 patient episodes of care for confirmed or suspected COVID-19. This included 288 separate patients, including 136 men and 119 women (sex missing = 33), with a median age of 62.0 years (interquartile range, 43.5-74.9 years). The simulation decision support model we developed is capable of providing dynamic and real-time support for RFDS decision makers in understanding the system's performance under uncertain COVID-19 demand. With increased COVID-19–related demand, the ability of the RFDS to cope will be driven by the number of aircraft available. The simulation model provided each aviation section with estimated numbers of aircraft required to meet a range of anticipated demands. CONCLUSION: Despite the lack of certainty in the actual level of COVID-19–related demand for RFDS services, modeling demonstrates that the robustness of meeting such demand increases with the number of operational and medically staffed aircraft. Air Medical Journal Associates. Published by Elsevier Inc. 2020 2020-05-16 /pmc/articles/PMC7229980/ /pubmed/32425475 http://dx.doi.org/10.1016/j.amj.2020.05.011 Text en © 2020 Air Medical Journal Associates. 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 Original Research
Gardiner, Fergus W.
Johns, Hannah
Bishop, Lara
Churilov, Leonid
Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title_full Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title_fullStr Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title_full_unstemmed Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title_short Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia
title_sort royal flying doctor service coronavirus disease 2019 activity and surge modeling in australia
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229980/
https://www.ncbi.nlm.nih.gov/pubmed/32425475
http://dx.doi.org/10.1016/j.amj.2020.05.011
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