Ethics of ICU triage during COVID-19

Author:

Vinay Rasita1,Baumann Holger12,Biller-Andorno Nikola1

Affiliation:

1. Institute of Biomedical Ethics and History of Medicine, Faculty of Medicine, University of Zurich, Winterthurerstrasse 30, 8006 Zurich, Switzerland

2. Department of Philosophy, Zollikerstrasse 117, 8008 Zurich, Switzerland

Abstract

Abstract Introduction The coronavirus disease 2019 pandemic has placed intensive care units (ICU) triage at the center of bioethical discussions. National and international triage guidelines emerged from professional and governmental bodies and have led to controversial discussions about which criteria—e.g. medical prognosis, age, life-expectancy or quality of life—are ethically acceptable. The paper presents the main points of agreement and disagreement in triage protocols and reviews the ethical debate surrounding them. Sources of data Published articles, news articles, book chapters, ICU triage guidelines set out by professional societies and health authorities. Areas of agreement Points of agreement in the guidelines that are widely supported by ethical arguments are (i) to avoid using a first come, first served policy or quality-adjusted life-years and (ii) to rely on medical prognosis, maximizing lives saved, justice as fairness and non-discrimination. Areas of controversy Points of disagreement in existing guidelines and the ethics literature more broadly regard the use of exclusion criteria, the role of life expectancy, the prioritization of healthcare workers and the reassessment of triage decisions. Growing points Improve outcome predictions, possibly aided by Artificial intelligence (AI); develop participatory approaches to drafting, assessing and revising triaging protocols; learn from experiences with implementation of guidelines with a view to continuously improve decision-making. Areas timely for developing research Examine the universality vs. context-dependence of triaging principles and criteria; empirically test the appropriateness of triaging guidelines, including impact on vulnerable groups and risk of discrimination; study the potential and challenges of AI for outcome and preference prediction and decision-support.

Funder

Swiss Government Excellence Scholarship

Publisher

Oxford University Press (OUP)

Subject

General Medicine

Reference42 articles.

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