开发和部署一个实时医疗预测分析平台
概括
一个新的平台集成了电子健康记录 (EHR) 数据,用于实时预测分析. 这种可扩展的基于云的系统支持临床决策,包括在急诊室预测早期的败血症.
科学领域:
- 医疗信息学 医疗信息学
- 临床决策支持系统 临床决策支持系统
- 医疗保健中的机器学习
背景情况:
- 将预测分析集成到医疗保健工作流程中是一项挑战.
- 电子健康记录 (EHR) 数据对临床见解有很大的潜力.
- 现有的系统往往缺乏可扩展性和无集成能力.
研究的目的:
- 为处理EHR数据提供一个可扩展的,基于云的,耐故障的平台.
- 为了实现实时数据提取和结果在医疗保健系统内的转移.
- 为了促进预测分析算法的部署.
主要方法:
- 开发一个基于云计算的平台,用于EHR数据处理.
- 使用可互操作的数据标准来实现可移植性.
- 集成与加州大学圣地亚哥分校的健康系统进行部署.
主要成果:
- 该平台成功地提取和处理患者入院后的EHR数据.
- 结果被转移回到EHR系统中.
- 该平台正在运行,并支持用于败血症预测的深度学习模型.
结论:
- 开发的平台为EHR数据集成提供了一个可扩展和容错的解决方案.
- 它可以在临床环境中无部署预测分析.
- 该系统具有临床相关性,目前用于急诊室早期败血症预测.
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