Building a house without foundations? A 24-country qualitative interview study on artificial intelligence in intensive care medicine

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES
Stuart McLennan, Amelia Fiske, Leo Anthony Celi
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Abstract

Objectives To explore the views of intensive care professionals in high-income countries (HICs) and lower-to-middle-income countries (LMICs) regarding the use and implementation of artificial intelligence (AI) technologies in intensive care units (ICUs). Methods Individual semi-structured qualitative interviews were conducted between December 2021 and August 2022 with 59 intensive care professionals from 24 countries. Transcripts were analysed using conventional content analysis. Results Participants had generally positive views about the potential use of AI in ICUs but also reported some well-known concerns about the use of AI in clinical practice and important technical and non-technical barriers to the implementation of AI. Important differences existed between ICUs regarding their current readiness to implement AI. However, these differences were not primarily between HICs and LMICs, but between a small number of ICUs in large tertiary hospitals in HICs, which were reported to have the necessary digital infrastructure for AI, and nearly all other ICUs in both HICs and LMICs, which were reported to neither have the technical capability to capture the necessary data or use AI, nor the staff with the right knowledge and skills to use the technology. Conclusion Pouring massive amounts of resources into developing AI without first building the necessary digital infrastructure foundation needed for AI is unethical. Real-world implementation and routine use of AI in the vast majority of ICUs in both HICs and LMICs included in our study is unlikely to occur any time soon. ICUs should not be using AI until certain preconditions are met. Data are available upon reasonable request. Our data include pseudonymised transcripts of interviews, which cannot be made publicly available in their entirety because of (1) the terms of our ethics approval; and (2) because participants could be identifiable if placed in the context of the entire transcript. This is in line with current ethical expectations for qualitative interview research. We provide anonymised quotes within the paper to illustrate our findings (corresponding to transcript excerpts), and the complete interview guide used in the study has been included as a Supplementary Information.
建造没有地基的房屋?关于重症监护医学人工智能的 24 国定性访谈研究
目的 探讨高收入国家(HICs)和中低收入国家(LMICs)重症监护专业人员对重症监护病房(ICUs)使用和实施人工智能(AI)技术的看法。方法 在 2021 年 12 月至 2022 年 8 月期间,对来自 24 个国家的 59 名重症监护专业人员进行了个人半结构化定性访谈。访谈记录采用传统内容分析法进行分析。结果 参与者对人工智能在重症监护病房的潜在应用普遍持积极态度,但也报告了一些众所周知的在临床实践中使用人工智能的顾虑,以及实施人工智能的重要技术和非技术障碍。各重症监护室在目前实施人工智能的准备程度上存在着重大差异。然而,这些差异主要不是发生在高收入国家和低收入国家之间,而是发生在高收入国家大型三甲医院的少数重症监护室和几乎所有其他高收入国家和低收入国家的重症监护室之间,前者据说拥有人工智能所需的数字基础设施,而后者据说既不具备获取必要数据或使用人工智能的技术能力,也没有具备使用该技术的适当知识和技能的员工。结论 在没有建立人工智能所需的必要数字基础设施基础的情况下,投入大量资源开发人工智能是不道德的。在我们的研究中,高收入国家和低收入国家的绝大多数重症监护病房都不可能在短期内真正实施和常规使用人工智能。在满足某些前提条件之前,重症监护室不应使用人工智能。如有合理要求,可提供数据。我们的数据包括化名后的访谈记录,这些记录不能全部公开,原因是:(1)我们的伦理批准条款;(2)如果将整个记录放在一起,参与者的身份可能会被识别。这符合当前定性访谈研究的伦理要求。我们在论文中提供了匿名引文,以说明我们的研究结果(与记录誊本节选相对应),研究中使用的完整访谈指南已作为补充信息包含在内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
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