从床上到长椅,再回:在临床环境中部署内压力数据分析所面临的挑战
Laura Moss1,2, Martin Shaw1,2, Ian Piper2
1Dept. of Clinical Physics, NHS Greater Glasgow and Clyde, Glasgow, United Kingdom.
Brain & spine
|August 6, 2024
概括
在床边实施复杂的内压力 (ICP) 模型面临技术,分析和数据完整性的挑战. 克服这些障碍对于利用ICP数据分析来改善患者护理至关重要.
科学领域:
- 神经临界护理是指神经临界护理.
- 生物医学工程 生物医学工程
- 临床信息学是一种临床信息学.
背景情况:
- 内压力 (ICP) 监测产生复杂的生理数据.
- 机器学习增强了用于诊断和预测临床决策的ICP模型.
- 很少有ICP模型在患者床边常规部署,这限制了实时改进.
研究的目的:
- 识别和讨论在患者床边实施复杂的ICP模型和分析方面的挑战.
- 探索将ICP数据洞察转化为可部署的临床工具的障碍.
主要方法:
- 在神经临床护理中实施障碍的叙事审查.
- 一个描述性的chart-adapt项目的案例研究.
主要成果:
- 主要障碍包括技术问题 (设备互操作性,高频数据分析的基础设施不足),分析挑战和数据完整性问题.
- 临床信心,伦理考虑,信任,安全和患者保密也构成重大障碍.
- 缺乏互操作性和基础设施不足阻碍了数据收集和模型部署.
结论:
- 快速提供和有意义地沟通ICP数据分析结果对于临床益处至关重要.
- 解决技术,分析和数据完整性的障碍是广泛采用ICP模型的必要条件.
- 解决方案必须应对现实世界的挑战,以便有效地实施ICP数据分析工具.
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