International Seminar Series on Decision Support for Health Systems after COVID-19: Data, Models and Methods
An online seminar series on decision support for health systems after COVID-19 which is designed to provide an open, transparent platform for sharing models, methodologies and data to enable participants to discuss and learn from one another and spark new ideas.
You are invited to join our seminar with presenters from the University of Bath and the Bristol, North Somerset and South Gloucestershire (BNSSG) CCG on:
Modelling to inform intensive care surge capacity and triage considerations during COVID-19
Zoom Meeting, Tuesday 11th May 2021, 13:00 – 14:30
This seminar is free to join, but you need to register in advance. Register for this seminar here. After registering, you will receive a confirmation email containing information about joining the webinar.
13:00 – 13:30 Modelling to inform intensive care surge capacity and triage considerations during COVID-19
Professor Christos Vasilakis, Director for the Centre for Healthcare Innovation and Improvement, School of Management University of Bath
Dr Richard Wood, Head of Modelling and Analytics BNSSG CCG, Visiting Research Fellow School of Management University of Bath
13:30 – 14:30 Deep Dive Discussion Session
A lively Q&A session where participants will actively engage to discuss the methodology, implementation, assumptions, benefits and challenges of the approach
Managing healthcare demand and capacity is especially difficult in the context of the COVID-19 pandemic, where limited intensive care resources can be overwhelmed by a large number of cases requiring admission in a short space of time. If patients are unable to access this specialist resource, then death is a likely outcome. In this talk we will present two related applied research studies undertaken within the one-million-resident NHS BNSSG healthcare system. The first will describe the construction and application of a purpose-built discrete event simulation model to estimate the number of capacity-dependent deaths that may result from various management and clinical strategies considered during the first COVID-19 wave. The second will extend this dynamical simulation model in capturing the effect of a range of triage protocols that could be employed were intensive care services truly overwhelmed. Our simulation results suggest that total life-years lost can be reduced by at least 12% if ‘reverse triage’ is used – essentially admitting all patients where possible but prematurely discharging those whose age is above some threshold if an arriving younger patient cannot otherwise be admitted. The talk will cover the modelling objectives, scope, methodology, results, practical implications and further research opportunities.
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