Suppr超能文献

人工智能在复苏相关伦理决策中的支持:需谨慎前行。

AI support for ethical decision-making around resuscitation: proceed with care.

机构信息

Institute of Biomedical Ethics and History of Medicine, Universität Zürich, Zurich, Switzerland

Collegium Helveticum, Zurich, Switzerland.

出版信息

J Med Ethics. 2022 Mar;48(3):175-183. doi: 10.1136/medethics-2020-106786. Epub 2021 Mar 9.

Abstract

Artificial intelligence (AI) systems are increasingly being used in healthcare, thanks to the high level of performance that these systems have proven to deliver. So far, clinical applications have focused on diagnosis and on prediction of outcomes. It is less clear in what way AI can or should support complex clinical decisions that crucially depend on patient preferences. In this paper, we focus on the ethical questions arising from the design, development and deployment of AI systems to support decision-making around cardiopulmonary resuscitation and the determination of a patient's Do Not Attempt to Resuscitate status (also known as code status). The COVID-19 pandemic has made us keenly aware of the difficulties physicians encounter when they have to act quickly in stressful situations without knowing what their patient would have wanted. We discuss the results of an interview study conducted with healthcare professionals in a university hospital aimed at understanding the status quo of resuscitation decision processes while exploring a potential role for AI systems in decision-making around code status. Our data suggest that (1) current practices are fraught with challenges such as insufficient knowledge regarding patient preferences, time pressure and personal bias guiding care considerations and (2) there is considerable openness among clinicians to consider the use of AI-based decision support. We suggest a model for how AI can contribute to improve decision-making around resuscitation and propose a set of ethically relevant preconditions-conceptual, methodological and procedural-that need to be considered in further development and implementation efforts.

摘要

人工智能(AI)系统在医疗保健领域的应用日益广泛,这要归功于这些系统所展现出的高水平性能。到目前为止,临床应用主要集中在诊断和预测结果上。在何种程度上,人工智能可以或应该支持那些严重依赖患者偏好的复杂临床决策,这一点还不太清楚。在本文中,我们专注于围绕心肺复苏和患者的不复苏意愿(也称为代码状态)决策设计、开发和部署人工智能系统所引发的伦理问题。COVID-19 大流行让我们敏锐地意识到,当医生在不知道患者意愿的情况下,必须在压力环境下迅速采取行动时,他们会遇到困难。我们讨论了一项在一所大学医院进行的医疗保健专业人员访谈研究的结果,该研究旨在了解复苏决策过程的现状,同时探讨人工智能系统在代码状态决策中的潜在作用。我们的数据表明:(1) 当前的实践存在诸多挑战,例如对患者偏好的了解不足、时间压力以及个人偏见会影响护理决策;(2) 临床医生对考虑使用基于人工智能的决策支持持开放态度。我们提出了一种人工智能如何有助于改善复苏决策的模型,并提出了一套与伦理相关的前提条件——概念、方法和程序,这些条件需要在进一步的开发和实施工作中得到考虑。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验