ERAS and the challenge of the new technologies.

IF 2.9 3区 医学 Q1 ANESTHESIOLOGY
Elena Bignami, Brigida Leoni, Tania Domenichetti, Matteo Panizzi, Luis A Diego, Valentina Bellini
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引用次数: 0

Abstract

The integration of artificial intelligence (AI) and all new technologies (NTs) into enhanced recovery after surgery (ERAS) protocols offers significant opportunities to address implementation challenges and improve patient care. Despite the proven benefits of ERAS, limitations such as resistance to change, resource constraints, and poor interdepartmental communication persist. AI can play a crucial role in overcoming ERAS implementation barriers by simplifying clinical plans, ensuring high compliance, and creating patient-centered approaches. Advanced techniques like machine learning and deep learning can optimize preoperative management, intraoperative phases, and postoperative recovery pathways. AI integration in ERAS protocols has the potential to revolutionize perioperative medicine by enabling personalized patient care, enhancing monitoring strategies, and improving clinical decision-making. The technology can address common postoperative challenges by developing individualized ERAS plans based on patient risk factors and optimizing perioperative processes. While challenges remain, including the need for external validation and data security, the authors suggest that the combination of AI, NTs, and ERAS protocols should become an integral part of routine clinical practice. This integration ultimately leads to improved patient outcomes and satisfaction in surgical care, transforming the perioperative medicine landscape by tailoring pathways to patients' needs.

ERAS和新技术的挑战。
人工智能(AI)和所有新技术(nt)集成到增强手术后恢复(ERAS)协议中,为解决实施挑战和改善患者护理提供了重要机会。尽管ERAS的好处得到了证实,但是诸如抗拒改变、资源限制和部门间沟通不良等限制仍然存在。人工智能可以通过简化临床计划、确保高依从性和创建以患者为中心的方法,在克服ERAS实施障碍方面发挥关键作用。机器学习和深度学习等先进技术可以优化术前管理、术中阶段和术后恢复途径。人工智能在ERAS方案中的集成有可能通过实现个性化患者护理、加强监测策略和改善临床决策来彻底改变围手术期医学。该技术可以根据患者的危险因素制定个性化的ERAS计划,并优化围手术期流程,从而解决常见的术后挑战。尽管挑战依然存在,包括需要外部验证和数据安全,但作者建议,人工智能、nt和ERAS协议的结合应该成为常规临床实践的组成部分。这种整合最终改善了患者的手术治疗效果和满意度,通过根据患者的需求定制途径,改变了围手术期医学景观。
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来源期刊
Minerva anestesiologica
Minerva anestesiologica 医学-麻醉学
CiteScore
4.50
自引率
21.90%
发文量
367
审稿时长
4-8 weeks
期刊介绍: Minerva Anestesiologica is the journal of the Italian National Society of Anaesthesia, Analgesia, Resuscitation, and Intensive Care. Minerva Anestesiologica publishes scientific papers on Anesthesiology, Intensive care, Analgesia, Perioperative Medicine and related fields. Manuscripts are expected to comply with the instructions to authors which conform to the Uniform Requirements for Manuscripts Submitted to Biomedical Editors by the International Committee of Medical Journal Editors.
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