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Elective surgery cancellations due to the COVID-19 pandemic: global predictive modelling to inform surgical recovery plans.

COVIDSurg Collaborative (2020) Elective surgery cancellations due to the COVID-19 pandemic: global predictive modelling to inform surgical recovery plans. Br J Surg, 107 (11). pp. 1440-1449. ISSN 1365-2168 https://doi.org/10.1002/bjs.11746
SGUL Authors: Rhodes, Andrew

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Abstract

BACKGROUND: The COVID-19 pandemic has disrupted routine hospital services globally. This study estimated the total number of adult elective operations that would be cancelled worldwide during the 12 weeks of peak disruption due to COVID-19. METHODS: A global expert response study was conducted to elicit projections for the proportion of elective surgery that would be cancelled or postponed during the 12 weeks of peak disruption. A Bayesian β-regression model was used to estimate 12-week cancellation rates for 190 countries. Elective surgical case-mix data, stratified by specialty and indication (surgery for cancer versus benign disease), were determined. This case mix was applied to country-level surgical volumes. The 12-week cancellation rates were then applied to these figures to calculate the total number of cancelled operations. RESULTS: The best estimate was that 28 404 603 operations would be cancelled or postponed during the peak 12 weeks of disruption due to COVID-19 (2 367 050 operations per week). Most would be operations for benign disease (90·2 per cent, 25 638 922 of 28 404 603). The overall 12-week cancellation rate would be 72·3 per cent. Globally, 81·7 per cent of operations for benign conditions (25 638 922 of 31 378 062), 37·7 per cent of cancer operations (2 324 070 of 6 162 311) and 25·4 per cent of elective caesarean sections (441 611 of 1 735 483) would be cancelled or postponed. If countries increased their normal surgical volume by 20 per cent after the pandemic, it would take a median of 45 weeks to clear the backlog of operations resulting from COVID-19 disruption. CONCLUSION: A very large number of operations will be cancelled or postponed owing to disruption caused by COVID-19. Governments should mitigate against this major burden on patients by developing recovery plans and implementing strategies to restore surgical activity safely.

Item Type: Article
Additional Information: This is a pre-copyedited, author-produced version of an article accepted for publication in British Journal of Surgery following peer review. The version of record COVIDSurg Collaborative, Elective surgery cancellations due to the COVID-19 pandemic: global predictive modelling to inform surgical recovery plans, British Journal of Surgery, Volume 107, Issue 11, October 2020, Pages 1440–1449 is available online at: https://doi.org/10.1002/bjs.11746
Keywords: Adult, Bayes Theorem, COVID-19, Elective Surgical Procedures, Global Health, Health Care Rationing, Health Policy, Health Services Accessibility, Humans, Infection Control, Models, Statistical, Pandemics, COVIDSurg Collaborative, Humans, Models, Statistical, Bayes Theorem, Infection Control, Health Care Rationing, Health Policy, Adult, Health Services Accessibility, Pandemics, Global Health, Elective Surgical Procedures, COVID-19, Adult, Bayes Theorem, COVID-19, Elective Surgical Procedures, Global Health, Health Care Rationing, Health Policy, Health Services Accessibility, Humans, Infection Control, Models, Statistical, Pandemics, Surgery, 11 Medical and Health Sciences
SGUL Research Institute / Research Centre: Academic Structure > Molecular and Clinical Sciences Research Institute (MCS)
Journal or Publication Title: Br J Surg
ISSN: 1365-2168
Language: eng
Dates:
DateEvent
October 2020Published
13 June 2020Published Online
11 May 2020Accepted
Publisher License: Publisher's own licence
Projects:
Project IDFunderFunder ID
UNSPECIFIEDNIHR Academy British Gynaecological Cancer SocietyUNSPECIFIED
UNSPECIFIEDBowel Disease Research FoundationUNSPECIFIED
UNSPECIFIEDAssociation of Coloproctology of Great Britain and IrelandUNSPECIFIED
UNSPECIFIEDBritish Association of Surgical OncologyUNSPECIFIED
UNSPECIFIEDSarcoma UKUNSPECIFIED
UNSPECIFIEDEuropean Society of ColoproctologyUNSPECIFIED
NIHR300175Department of HealthUNSPECIFIED
NIHR 16.136.79National Institute for Health ResearchUNSPECIFIED
UNSPECIFIEDBowel and Cancer ResearchUNSPECIFIED
UNSPECIFIEDAssociation of Upper Gastrointestinal SurgeonsUNSPECIFIED
UNSPECIFIEDYorkshire Cancer ResearchUNSPECIFIED
UNSPECIFIEDVascular Society for Great Britain and IrelandUNSPECIFIED
PubMed ID: 32395848
Web of Science ID: WOS:000539810900001
Go to PubMed abstract
URI: https://openaccess.sgul.ac.uk/id/eprint/114008
Publisher's version: https://doi.org/10.1002/bjs.11746

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