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Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England

OBJECTIVES: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England’s National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estima...

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Autores principales: Howlett, Nicholas C., Wood, Richard M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365524/
https://www.ncbi.nlm.nih.gov/pubmed/35963839
http://dx.doi.org/10.1016/j.jval.2022.06.016
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author Howlett, Nicholas C.
Wood, Richard M.
author_facet Howlett, Nicholas C.
Wood, Richard M.
author_sort Howlett, Nicholas C.
collection PubMed
description OBJECTIVES: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England’s National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025. METHODS: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals “missed” during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic. RESULTS: As a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%. CONCLUSIONS: This study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience.
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spelling pubmed-93655242022-08-11 Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England Howlett, Nicholas C. Wood, Richard M. Value Health Themed Section: COVID-19 OBJECTIVES: A significant indirect impact of COVID-19 has been the increasing elective waiting times observed in many countries. In England’s National Health Service, the waiting list has grown from 4.4 million in February 2020 to 5.7 million by August 2021. The objective of this study was to estimate the trajectory of future waiting list size and waiting times up to December 2025. METHODS: A scenario analysis was performed using computer simulation and publicly available data as of November 2021. Future demand assumed a phased return of various proportions (0%, 25%, 50%, and 75%) of the estimated 7.1 million referrals “missed” during the pandemic. Future capacity assumed 90%, 100%, and 110% of that provided in the 12 months immediately before the pandemic. RESULTS: As a worst-case scenario, the waiting list would reach 13.6 million (95% confidence interval 12.4-15.6 million) by Autumn 2022, if 75% of missed referrals returned and only 90% of prepandemic capacity could be achieved. The proportion of patients waiting under 18 weeks would reduce from 67.6% in August 2021 to 42.2% (37.4%-46.2%) with the number waiting over 52 weeks reaching 1.6 million (0.8-3.1 million) by Summer 2023. At this time, 29.0% (21.3%-36.8%) of patients would be leaving the waiting list before treatment. Waiting lists would remain pressured under even the most optimistic of scenarios considered, with 18-week performance struggling to maintain 60%. CONCLUSIONS: This study reveals the long-term challenge for the National Health Service in recovering elective waiting lists and potential implications for patient outcomes and experience. International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. 2022-11 2022-08-11 /pmc/articles/PMC9365524/ /pubmed/35963839 http://dx.doi.org/10.1016/j.jval.2022.06.016 Text en © 2022 International Society for Pharmacoeconomics and Outcomes Research, Inc. Published by Elsevier Inc. 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 Themed Section: COVID-19
Howlett, Nicholas C.
Wood, Richard M.
Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title_full Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title_fullStr Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title_full_unstemmed Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title_short Modeling the Recovery of Elective Waiting Lists Following COVID-19: Scenario Projections for England
title_sort modeling the recovery of elective waiting lists following covid-19: scenario projections for england
topic Themed Section: COVID-19
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9365524/
https://www.ncbi.nlm.nih.gov/pubmed/35963839
http://dx.doi.org/10.1016/j.jval.2022.06.016
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