Benjamin Popoff, Sandie Cabon, Marc Cuggia, Guillaume Bouzillé, Thomas Clavier
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This will be used to guide the development of an AI-based CDSS on which our team is working to ensure user-centered design and successful integration into clinical practice.</p><p><strong>Methods: </strong>A prospective cross-sectional survey of French-speaking physicians with clinical activity in intensive care was conducted between December 2023 and April 2024. The questionnaire consisted of 20 questions structured around 4 axes: overview of the problem and current practices concerning weaning from CRRT, opinion on AI-based CDSS, implementation in daily clinical practice, real-life operation and willingness to adopt the CDSS in everyday practice. Statistical analyses included Wilcoxon rank sum tests for quantitative variables and χ2 or Fisher exact tests for qualitative variables, with multivariate analyses performed using ordinal logistic regression.</p><p><strong>Results: </strong>A total of 171 complete responses were received. 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引用次数: 0
摘要
背景:重症监护病房(icu)的危重患者需要持续监测,产生大量数据。利用人工智能(AI)技术的临床决策支持系统(CDSS)在改善诊断、预后和治疗决策方面显示出了希望。然而,这些模型在临床实践中很少得到应用。目的:本研究的目的是调查ICU医生,了解他们对建议的基于人工智能的CDSS用于持续肾替代治疗(CRRT)断奶的期望、意见和知识水平,这是一个仍然复杂且缺乏指南的临床决策过程。这将用于指导基于人工智能的CDSS的开发,我们的团队正在努力确保以用户为中心的设计并成功整合到临床实践中。方法:对2023年12月至2024年4月期间在重症监护室有临床活动的法语医师进行前瞻性横断面调查。问卷共20个问题,围绕4个轴构成:CRRT断奶问题概述及实践现状、对基于人工智能的CDSS的看法、在临床日常实践中的实施情况、实际操作情况以及在日常实践中采用CDSS的意愿。统计分析包括定量变量的Wilcoxon秩和检验和定性变量的χ2或Fisher精确检验,多变量分析使用有序逻辑回归进行。结果:共收到171份完整回复。70.2%(120/171)的医生对CDSS用于CRRT断奶表示了兴趣,对基于人工智能的CDSS持赞成态度。关于断奶决定本身的困难,意见分歧,46.2%(79/171)不同意这是具有挑战性的,而31.6%(54/171)同意。然而,66.1%(113/171)的受访者支持基于人工智能的CDSS的价值,以帮助他们做出这一决定,年轻医生表现出更强的支持(81.8%,27/33 vs 62.3%;86/138;P = . 01)。大多数受访者(163/171,95.3%)强调理解模型用于预测的标准的重要性。结论:我们的研究结果突出了ICU医生对基于人工智能的CRRT脱机CDSS的乐观态度,强调了透明度的必要性,与现有工作流程的整合,以及与临床医生决策过程的一致性。可操作的建议包括纳入关键变量,如尿量和生物参数,定义建议的概率阈值,并确保模型透明度,以促进成功采用和整合到临床实践中。这项调查的方法可能有助于进一步发展基于人工智能的CDSS项目的开发前研究。
Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study.
Background: Critically ill patients in intensive care units (ICUs) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in improving diagnostic, prognostic, and therapeutic decision-making. However, these models are rarely implemented in clinical practice.
Objective: The aim of this study was to survey ICU physicians to understand their expectations, opinions, and level of knowledge regarding a proposed AI-based CDSS for continuous renal replacement therapy (CRRT) weaning, a clinical decision-making process that is still complex and lacking in guidelines. This will be used to guide the development of an AI-based CDSS on which our team is working to ensure user-centered design and successful integration into clinical practice.
Methods: A prospective cross-sectional survey of French-speaking physicians with clinical activity in intensive care was conducted between December 2023 and April 2024. The questionnaire consisted of 20 questions structured around 4 axes: overview of the problem and current practices concerning weaning from CRRT, opinion on AI-based CDSS, implementation in daily clinical practice, real-life operation and willingness to adopt the CDSS in everyday practice. Statistical analyses included Wilcoxon rank sum tests for quantitative variables and χ2 or Fisher exact tests for qualitative variables, with multivariate analyses performed using ordinal logistic regression.
Results: A total of 171 complete responses were received. Physicians expressed an interest in a CDSS for CRRT weaning, with 70.2% (120/171) viewing AI-based CDSS favorably. Opinions were split regarding the difficulty of the weaning decision itself, with 46.2% (79/171) disagreeing that it is challenging, while 31.6% (54/171) agreed. However, 66.1% (113/171) of respondents supported the value of an AI-based CDSS to assist them in this decision, with younger physicians showing stronger support (81.8%, 27/33 vs 62.3%; 86/138; P=.01). Most respondents (163/171, 95.3%) emphasized the importance of understanding the criteria used by the model to make its predictions.
Conclusions: Our findings highlight an optimistic attitude among ICU physicians toward AI-based CDSS for CRRT weaning, emphasizing the need for transparency, integration into existing workflows, and alignment with clinicians' decision-making processes. Actionable recommendations include incorporating key variables such as urine output and biological parameters, defining probability thresholds for recommendations and ensuring model transparency to facilitate the successful adoption and integration into clinical practice. The methodology of this survey may help the development of further predevelopment studies accompanying AI-based CDSS projects.
期刊介绍:
JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals.
Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.