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麻醉学如何应对创新和新技术?

How anesthesiology can deal with innovation and new technologies?

机构信息

Department of Anesthesia and Intensive Care, Cochin University Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France -

Paris-Est Créteil University (UPEC), Paris, France -

出版信息

Minerva Anestesiol. 2024 Jan-Feb;90(1-2):68-76. doi: 10.23736/S0375-9393.23.17464-5. Epub 2023 Aug 1.

DOI:10.23736/S0375-9393.23.17464-5
PMID:37526467
Abstract

Innovation and new technologies have always impacted significantly the anesthesiology practice all along the perioperative course, as it is recognized as one of the most transformative medical specialties specifically regarding patient's safety. Beside a number of major changes in procedures, equipment, training, and organization that aggregated to establish a strong safety culture with effective practices, anesthesiology is also a stakeholder in disruptive innovation. The present review is not exhaustive and aims to provide an overview on how innovation could change and improve anesthesiology practices through some examples as telemedicine (TM), machine learning and artificial intelligence (AI). For example, postoperative complications can be accurately predicted by AI from automated real-time electronic health record data, matching physicians' predictive accuracy. Clinical workflow could be facilitated and accelerated with mobile devices and applications, assuming that these tools should remain at the service of patients and care providers. Care providers and patients connections have improved, thanks to these digital and innovative transformations, without replacing existing relationships between them. It also should give time back to physicians and nurses to better spend it in the perioperative care, and to provide "personalized" medicine keeping a high level of standard of care.

摘要

创新和新技术一直以来都对围手术期的麻醉实践产生重大影响,因为麻醉学被认为是最具变革性的医学专业之一,特别是在患者安全方面。除了程序、设备、培训和组织方面的许多重大变化,这些变化共同建立了强大的安全文化和有效的实践之外,麻醉学也是颠覆性创新的利益相关者。本综述并非详尽无遗,旨在通过一些例子,如远程医疗(TM)、机器学习和人工智能(AI),概述创新如何改变和改进麻醉学实践。例如,人工智能可以通过自动实时电子健康记录数据准确预测术后并发症,与医生的预测准确性相匹配。临床工作流程可以通过移动设备和应用程序得到简化和加速,前提是这些工具应该始终服务于患者和护理提供者。借助这些数字和创新的转变,护理提供者和患者之间的联系得到了改善,而不会取代他们之间现有的关系。这也为医生和护士节省了时间,让他们有更多时间用于围手术期护理,并提供“个性化”的医疗服务,同时保持高标准的护理水平。

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