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[Preprint]. 2024 Mar 13:2024.03.10.24304058.
doi: 10.1101/2024.03.10.24304058.

Investigating Ethical Tradeoffs in Crisis Standards of Care through Simulation of Ventilator Allocation Protocols

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Investigating Ethical Tradeoffs in Crisis Standards of Care through Simulation of Ventilator Allocation Protocols

Jonathan Herington et al. medRxiv. .

Update in

Abstract

Introduction: Arguments over the appropriate Crisis Standards of Care (CSC) for public health emergencies often assume that there is a tradeoff between saving the most lives, saving the most life-years, and preventing racial disparities. However, these assumptions have rarely been explored empirically. To quantitatively characterize possible ethical tradeoffs, we aimed to simulate the implementation of five proposed CSC protocols for rationing ventilators in the context of the COVID-19 pandemic.

Methods: A Monte Carlo simulation was used to estimate the number of lives saved and life-years saved by implementing clinical acuity-, comorbidity- and age-based CSC protocols under different shortage conditions. This model was populated with patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. To estimate lives and life-years saved by each protocol, we determined survival to discharge and estimated remaining life expectancy for each admission.

Results: The simulation demonstrated stronger performance for age- and comorbidity-sensitive protocols. For a capacity of 1 bed per 2 patients, ranking by age bands saves approximately 28.7 lives and 3408 life-years per thousand patients, while ranking by Sequential Organ Failure Assessment (SOFA) bands saved the fewest lives (13.2) and life-years (416). For all protocols, we observed a positive correlation between lives saved and life-years saved. For all protocols except lottery and the banded SOFA, significant disparities in lives saved and life-years saved were noted between White non-Hispanic, Black non-Hispanic, and Hispanic sub-populations.

Conclusion: While there is significant variance in the number of lives saved and life-years saved, we did not find a tradeoff between saving the most lives and saving the most life-years. Moreover, concerns about racial discrimination in triage protocols require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

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Figures

Fig 1.
Fig 1.. Lives saved per patient by protocol:
A. Overall increase in lives saved per patient, for each protocol, at 50% scarcity. B. Lives saved per patient stratified by racial group, for each protocol, at 50% scarcity.
Fig 2.
Fig 2.. Lives saved at different levels of scarcity, for each protocol.
The greatest differences between protocols occur at moderate levels of scarcity (i.e. ~0.5 beds per patient), and differences between protocols decline at both high and low levels of scarcity.
Fig 3:
Fig 3:. Life years saved per patient.
A. Overall increase in life years saved per patient, for each protocol, at 50% scarcity. B. Life years saved per patient stratified by racial group, for each protocol, at 50% scarcity.
Fig 4:
Fig 4:. Tradeoffs between life years saved and lives saved.
While there is significant variance in numbers of lives and life years saved, there is a strong positive correlation between each statistic for all protocols.

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References

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