Supporting COVID-19 elective recovery through scalable wait list modelling: Specialty-level application to all hospitals in England

Richard M. Wood

Research output: Contribution to journalArticlepeer-review

Abstract

The recovery of elective waiting lists represents a major challenge and priority for the health services of many countries. In England’s National Health Service (NHS), the waiting list has increased by 45% in the two years since the COVID-19 pandemic was declared in March 2020. Long waits associate with worse patient outcomes and can deepen inequalities and lead to additional demands on healthcare resources. Modelling the waiting list can be valuable for both estimating future trajectories and considering alternative capacity allocation strategies. However, there is a deficit within the current literature of scalable solutions that can provide managers and clinicians with hospital and specialty level projections on a routine basis. In this paper, a model representing the key dynamics of the waiting list problem is presented alongside its differential equation based solution. Versatility of the model is demonstrated through its calibration to routine publicly available NHS data. The model has since been used to produce regular monthly projections of the waiting list for every hospital trust and specialty in England.

Original languageEnglish
Pages (from-to)521-525
Number of pages5
JournalHealth Care Management Science
Volume25
Early online date7 Oct 2022
DOIs
Publication statusE-pub ahead of print - 7 Oct 2022
Externally publishedYes

Keywords

  • COVID-19
  • Elective care
  • Mathematical modelling
  • Operations Research
  • Waiting lists

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Health Professions(all)

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