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精确反:一个概念模型模型.
Zach Landis-Lewis1, Allison M Janda2, Hana Chung3
1Department of Learning Health Sciences University of Michigan Ann Arbor Michigan USA.
Learning health systems
|July 22, 2024
概括
通过指导原则提供精确的反,旨在通过根据个人动机和偏好量身定制绩效信息来提高医疗保健质量. 这种方法个性化反以提高效率和提供商参与度.
科学领域:
- 改善医疗保健质量 改善医疗保健质量
- 医学中的行为科学.
- 人与计算机的互动.
背景情况:
- 绩效反可以提高医疗保健质量,但它的有效性各不相同.
- 目前的反方法缺乏个性化,限制了它们对医疗保健专业人员的影响.
- 基于指导的方法可以通过与个人目标和动机保持一致来增强反.
研究的目的:
- 提出一个准确反的概念模型.
- 提高医疗保健中反干预措施的有效性.
- 将反与医疗保健专业人员的目标和动机需求保持一致.
主要方法:
- 代模型开发整合了动机,行为变化,可视化和人机交互的理论.
- 将模型应用于临床实例,并通过软件开发进行改进.
- 在软件应用程序中实现,为麻醉提供者生成精确的反信息.
主要成果:
- 定义精确反作为根据接收者的动机潜力优先考虑的信息.
- 确定了影响激励潜力的三个关键因素:激励数据,惊喜性和接收者偏好.
- 开发了一个精确反模型,与反干预理论保持一致.
结论:
- 已经提出了一个准确反的概念模型.
- 精确反旨在提高反干预措施的有效性.
- 该模型将在麻醉提供者的随机对照试验中进行评估.
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