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在术后护理病房的护理交付和优化系统
Connor Snarskis1, Arna Banerjee1, Andrew Franklin1
1Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, TN, USA.
Anesthesiology clinics
|October 14, 2023
概括
大型手术带来严重的风险,包括一个月内死亡,大多数事件发生在手术后. 先进的人工智能可以改善患者监测,并使及时干预能够防止不良结果.
科学领域:
- 医学研究 医学研究
- 患者安全 患者安全
- 术后护理 术后护理
背景情况:
- 很大一部分患者在进行重大手术后的第一个月内会遇到严重的不良事件,包括死亡.
- 这些关键事件主要表现在手术后24小时内,在直接的手术和康复环境之外.
- 由阿片类药物引起的呼吸系统抑郁是一个主要问题,导致55%的死亡和22%的无氧性脑损伤.
研究的目的:
- 突出与重大手术和术后护理相关的风险.
- 确定严重不良事件的主要原因和时间.
- 探索人工智能在减轻这些风险方面的潜力.
主要方法:
- 对术后不良事件数据的审查.
- 对阿片类药物诱导的呼吸系统抑郁结果的分析.
- 未来AI/ML集成的概念框架.
主要成果:
- 三分之一的患者在重大手术后面临严重不良事件的风险.
- 大多数关键事件发生在24小时内,超出手术室和麻醉后护理单位.
- 高死亡率和无氧脑损伤率与阿片类药物诱导的呼吸系统抑郁有关.
结论:
- 术后监测对于识别和管理急性临床恶化至关重要.
- 人工智能和机器学习为增强情境意识提供了有希望的解决方案.
- 由AI/ML促进的早期干预可以显著减少患者的不良结果,并提高外科安全.
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