麻醉中的大数据:一个叙述性的,非系统的审查
Philippe Dony1, Rémi Florquin1, Patrice Forget1
1From the Department of Anesthesiology, CHU Charleroi, Department of Anesthesiology, Lodelinsart, Belgium (PD, RF), Institute of Applied Health Sciences, Epidemiology Group, School of Medicine, Medical Science and Nutrition, University of Aberdeen, Department of Anaesthesia, NHS Grampian, Aberdeen, UK (PF).
European journal of anaesthesiology and intensive care
|February 7, 2025
概括
整合麻醉信息管理系统 (AIMS) 数据对于改善患者护理至关重要. 增强的数据集成和分析,包括人工智能,可以在全球范围内推进外科手术期间的医学.
科学领域:
- 麻醉学 麻醉学
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
背景情况:
- 从麻醉信息管理系统 (AIMS) 增加数据生成为科学进步提供了潜力.
- 缺乏数据整合,阻碍了对例行收集的麻醉数据的有效使用,以改善患者护理.
- 电子健康记录 (EHR) 已经定义了适用于麻醉实践的整合水平 (例如NHS模型).
研究的目的:
- 审查日常收集的数据对提高护理质量的有用性.
- 定义EHR整合水平,并说明它们在麻醉中的应用.
- 探索微,中和宏观系统层面的数据利用策略.
主要方法:
- 关于麻醉中数据集成的文献叙事综述.
- 定义和说明EHR整合的六个层次.
- 描述一个定制的AIMS解决方案及其集成机会.
- 讨论研究前景和全球机遇,包括低收入国家.
主要成果:
- 常规麻醉数据,当集成时,可以显著提高患者护理质量.
- 一个自制的AIMS解决方案展示了在不同系统级别增强数据利用的潜力.
- 开发用于外科手术研究的核心数据集可以促进大规模的EHR数据集成.
结论:
- 将AIMS数据集成到电子健康记录中对于持续的实践再评估和最佳的患者护理至关重要.
- 在数据科学和人工智能方面培训麻醉科医生对于推进外科手术医学至关重要.
- 考虑数据中心的生态影响和全球数据共享是未来的重要方向.
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