Bioethics in Simulation: Using Quantitative Bioethics to Investigate Ethical Tradeoffs in Crisis Standards of Care Protocols

Abstract: 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 and we therefore have little evidence that particular CSC protocols actually promote the goals that they are intended to promote. To quantitatively characterize possible ethical tradeoffs, we developed a computer simulation of the implementation of five proposed CSC protocols (New York, Colorado, Age-Group, Pure SOFA and a previously published multi-principle protocol). To more accurately estimate the number of lives saved and life-years saved by these protocols, we applied the model to patient data from 3707 adult admissions requiring ventilator support in a New York hospital system between April 2020 and May 2021. In this paper, we report the preliminary results of this simulation and the implications for bioethical debates over CSC protocols. In particular, we suggest that while there is significant variance in the number of lives saved and life-years saved, there is unlikely to be a tradeoff between saving the most lives and saving the most life-years. Moreover, while some protocols produce significant racial disparities in lives and life-years saved, they perform better for all groups than protocols without racial disparities. Our results suggest that concerns about racial discrimination in triage protocols thus require thinking carefully about the tradeoff between enforcing equality of survival rates and maximizing the lives saved in each sub-population.

Jessica Shand – University of Rochester; Jeanne Holden-Wiltse – University of Rochester; Anthony Corbett – University of Rochester; Richard Dees – University of Rochester; Chin-Lin Ching – University of Rochester; Margie Shaw – University of Rochester; Xueya Cai – University of Rochester; Martin Zand – University of Rochester