在复杂的社会技术生态系统和学习健康系统中的患者护理
Shin-Ping Tu1, Brittany Garcia1, Xi Zhu2
1Department of Internal Medicine University of California, Davis Sacramento California USA.
Learning health systems
|June 17, 2024
概括
本研究探讨使用电子健康记录 (EHR) 数据来理解癌症护理中的团队沟通. 分析多团队系统 (MTS) 可以在学习健康系统 (LHS) 中改善医疗保健服务和患者的结果.
科学领域:
- 提供医疗保健的科学.
- 医疗信息学 医疗信息学
- 组织沟通组织沟通
背景情况:
- 学习健康系统 (LHS) 模型需要实时数据流来快速改善医疗保健.
- 电子健康记录 (EHR) 包含有价值的数据,用于理解复杂的医疗保健系统.
- 需要创新的方法来确定医疗保健提供中高效的团队结构.
研究的目的:
- 通过使用EHR数据研究多团队系统 (MTS) 来推进医疗保健提供科学.
- 开发新的网络指标来分析MTS通信结构.
- 研究EHR通信网络结构对癌症护理患者结果的影响.
主要方法:
- 利用来自EHR系统的真实世界癌症护理交付数据.
- 应用诸如多组系统 (MTS) 框架和通信网络等理论.
- 开发和分析用于MTS通信的新型网络指标.
主要成果:
- 目前正在进行的研究重点是开发网络指标,以研究癌症护理中的MTS.
- 分析将检查EHR通信网络结构与患者结果之间的关系.
- 该研究旨在确定基于证据的协作方法,以实现最佳的LHS.
结论:
- 通过EHR数据了解团队沟通对于推进学习健康系统至关重要.
- 这项研究为开发改善医疗保健协作和患者结果的干预措施提供了基础.
- 利用医疗IT数据可以导致医疗保健中更有效的团队结构和基于证据的实践.
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