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

Nicholas C. Howlett, Richard M. Wood

Research output: Contribution to journalArticlepeer-review

8 Citations (SciVal)

Abstract

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.

Original languageEnglish
Pages (from-to)1805-1813
Number of pages9
JournalValue in Health
Volume25
Issue number11
Early online date11 Aug 2022
DOIs
Publication statusPublished - 30 Nov 2022
Externally publishedYes

Bibliographical note

Funding Information:
Funding/Support: The authors received no financial support for this research.

Keywords

  • computer simulation
  • COVID-19
  • elective backlog
  • elective performance
  • waiting lists
  • waiting times

ASJC Scopus subject areas

  • Health Policy
  • Public Health, Environmental and Occupational Health

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