智能社区高血压管理:对承诺和挑战的叙述性审查
Manhong Yang1, Long Wu1, Yuzhen Zeng1
1Hengqin Hongqi Community Health Service Center, Hengqin Hospital, The First Affiliated Hospital of Guangzhou Medical University, Zhuhai, People's Republic of China.
Journal of multidisciplinary healthcare
|March 11, 2026
概括
使用移动健康,物联网和人工智能进行智能高血压管理,改善了初级保健中的血压控制和资源效率. 解决数字沟和数据安全对于公平有效的实施至关重要.
科学领域:
- 心脏病学 心脏病学
- 数字健康数字健康
- 公共卫生 公共卫生
背景情况:
- 控制高血压是全球初级保健的挑战,受到了低效的手工流程的阻碍.
- 移动健康,物联网 (IoT) 和人工智能 (AI) 为基于社区的管理提供了创新的解决方案.
- 目前的社区高血压管理面临着效率低下和不平等.
研究的目的:
- 审查社区环境中智能高血压管理模型的证据.
- 确定主导的智能管理方法及其对血压控制和资源分配的影响.
- 突出智能高血压管理的挑战和未来方向.
主要方法:
- 关于智能高血压管理的最新证据的叙述性综述.
- 识别和综合三个主要的管理方法:移动健康自主管理,远程监控干预和人工智能自动后续.
- 分析报告的临床改善和资源优化.
主要成果:
- 智能高血压管理模型在血压控制方面显示出临床上有意义的改善.
- 远程监控干预措施显示血压控制率显著改善 (15-25个百分点).
- 这些模型优化了资源分配,使得服务不足的人口受益.
结论:
- 智能管理模式在血压控制和资源效率方面提供了可衡量的改进.
- 关键的挑战包括数字沟和数据安全问题.
- 未来的努力应集中在大规模试验,支持公平政策和强有力的数据治理上.
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