28 June 2023 - 28 June 2023
11:30AM - 1:00PM
Online - Zoom
The Covid-19 Pandemic created “extraordinary and sustained” pressures and in some cases demands for rationing critical resource including intensive care (ICU) beds, medical equipment and health professionals. Advanced systems modelling and simulation approaches can help.
Doctor and Patient
Existing triage policies aimed at prioritising and rationing critical care resources are underpinned by the four fundamental principles: maximizing the benefits produced by scarce resources, treating people equally, promoting and rewarding instrumental value, and giving priority to the worst off. In practice, when triage criteria are applied to individual patients at the time of ICU admission, their priorities are determined mainly by individual attributes based on single or some of those values, including the illness severity and the near-term prognosis after discharge. Nevertheless, they do not consider the dynamic illness pathway of individual patients over the duration of treatment in ICU. Further, they ignore the overall mixture of current patient profiles and the uncertainty in the number of patients who become critical ill over time. Above all, the existing triage criteria do not adopt and operationalise all these values simultaneously, leading to suboptimal policies that challenge the principle of fairness in resource rationing.
To address these limitations, we developed an empirically informed algorithmic model that assigns patient priority based on ICU operational data from one NHS trust. The performance of our prioritisation policies is evaluated against existing triage benchmarks in a comprehensive computer simulation study.
Christos Vasilakis, Li Ding and Dong Li
Acknowledgement: This research was funded by UKRI/EPSRC Covid-19 Rapid Response Grant (Grant Ref: EP/V050761/1).
NOTE: This talk is geared towards health professionals