通过将远程螺旋测量装置集成到基于EHR的人工智能驱动的临床决策支持系统中来管理小儿喘:一个可行性实用性临床试验
Lynnea Myers1, Tracey A Brereton2, Shauna Overgaard2
1Precision Population Science Lab, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, United States of America; Department of Women and Children's Health, Karolinska Institutet, 171 77 Stockholm, Sweden; Gustavus Adolphus College, 800 College Avenue West, St. Peter, MN 56082, United States of America.
Contemporary clinical trials
|December 26, 2025
概括
这项研究发现,将人工智能支持的临床决策支持系统 (A-GPS) 与远程监控应用程序 (AsthmaTuner) 集成在一起,对于儿科喘管理是可行的. 该系统增强了远程护理,并为评估医疗保健中的AI工具提供了一个框架.
科学领域:
- 医疗保健中的人工智能
- 数字卫生技术数字卫生技术
- 临床决策支持系统 临床决策支持系统
背景情况:
- 喘是一种常见的儿童慢性疾病,控制不佳,导致高医疗费用.
- 电子健康记录 (EHR) 在获取及时的临床信息方面存在挑战.
- 一个机器学习和自然语言处理驱动系统 (A-GPS) 已开发出来,用于提取和合成用于喘管理的EHR数据.
研究的目的:
- 评估实现与AsthmaTuner集成的A-GPS与AsthmaTuner用于远程儿科喘管理的可行性和满意度.
- 评估使用来自家庭螺旋计和喘控制的移动应用程序的实时患者数据.
- 通过数字平台确定临床医生规定的喘行动计划的有效性.
主要方法:
- 进行了一项并行组,非盲目的,双部位,双臂实用随机临床试验 (RCT).
- 这项研究包括梅奥诊所卫生系统和梅奥诊所的22位临床医生和患者.
- 主要终点是成功实施综合系统和参与者满意度.
主要成果:
- 在远程喘管理的初级保健中,A-GPS和AsthmaTuner的技术整合被发现是可行的.
- 该研究建立了一个评估医疗保健环境中AI工具的框架.
- 该协议允许通过RCT实现数字技术.
结论:
- 集成的A-GPS和AsthmaTuner系统是一个可行的临床决策支持工具,用于远程儿科喘管理.
- 该协议提供了一个最佳实践框架,用于在临床环境中评估AI工具.
- 这项研究为将人工智能驱动的慢性疾病管理扩展到成年人身上铺平了道路.
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