计算机使用患者-提供者安全消息数据以实现更好的临床效率和沟通质量:系统性审查
Yawen Guo1, Di Hu1, Yiliang Zhou1
1University of California Irvine, Irvine, CA, United States.
AMIA ... Annual Symposium proceedings. AMIA Symposium
|February 23, 2026
概括
对安全消息传递 (SM) 的计算分析显示,对医疗保健来说是有前途的,BERT模型表现最好. 然而,由于数据集较小,目前的研究缺乏通用性,这凸显了需要改进方法的需要.
科学领域:
- 医疗信息学 医疗信息学
- 计算语言学 计算语言学
- 临床研究 临床研究
背景情况:
- 患者和提供者之间采用安全消息传递 (SM) 已经显著增长.
- 目前正在开发计算方法来分析SM数据的临床效率和通信质量.
研究的目的:
- 系统地审查和分析计算方法在患者和医疗服务提供者之间安全通讯中的应用.
- 确定现有研究中的趋势,常见应用和局限性.
主要方法:
- 对1374篇论文的系统文献综述,确定了19项相关研究 (2017-2024年).
- 对用于保护消息传输数据的计算方法的分析.
- 专注于诸如工作流程简化,疾病检测,决策支持和健康素养等应用程序.
主要成果:
- 在分析的计算方法中,BERT模型表现出卓越的性能.
- 确定的主要应用包括工作流程优化,早期疾病检测,个性化决策和增强患者健康素养.
- 研究受限于小型数据集和受限制的医疗保健环境,影响验证和概括性.
结论:
- 需要更强大的,可扩展的,公平的,和临床上适用的计算方法来保护消息数据.
- 未来的研究应该解决当前研究的局限性,以提高研究结果的概括性和临床实用性.
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