Predicting critical care needs during a pandemic

Gillian Anderson, Frances Sneddon, Robert van der Meer (Editor)

Research output: Contribution to journalSpecial issuepeer-review

25 Downloads (Pure)

Abstract

NHS Lanarkshire is the third largest Health Board in Scotland, serving a population of 655,000 across rural and urban communities in Lanarkshire. Its 12,000-strong team of staff work in communities, health centres, clinics and offices in the region and at three district general hospitals. When COVID-19 emerged, it posed huge questions for healthcare organisations globally. How much capacity would be needed to care for those who became infected? Would there be enough ventilators and other equipment to care for patients appropriately? And so much more. At NHS Lanarkshire, advice from both UK and Scottish governments had suggested that the major NHS Trusts (in England and Wales) and Health Boards (in Scotland) prepare for the worst-case scenario of a fivefold increase in demand for critical
care in the Spring 2020 peak of the COVID-19 pandemic. This left NHS Lanarkshire with the challenge of trying to predict, at very short notice, the critical care resources they would actually require over the coming weeks and months. Time was of the essence for decision making and preparations required for the potential demand surges. Working in close collaboration with NHS Lanarkshire, the University of Strathclyde Business School health systems experts used Simul8 modelling software to predict critical care needs at the start of the COVID-19 pandemic.
Original languageEnglish
Pages (from-to)7-10
Number of pages4
JournalImpact
Volume2020
Issue number2
Early online date26 Oct 2020
DOIs
Publication statusPublished - 6 Nov 2020

Keywords

  • COVID-19 pandemic
  • simulation
  • discrete event simulation
  • forecasting
  • critical care
  • intensive care
  • bed utilisation
  • NHS Lanarkshire
  • NHS Scotland

Fingerprint

Dive into the research topics of 'Predicting critical care needs during a pandemic'. Together they form a unique fingerprint.

Cite this