一个实施疾病预防和行为改变大规模证据的框架.
Karim Keshavjee1, Jasmine Candeliere1, Felipe Cepeda1
1Institute of Health, Policy and Management, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
这项研究提出了一个数字健康框架,以扩大慢性疾病的预防和治疗. 它使用电子医疗记录和人工智能为数百万加拿大人提供个性化护理,克服当前的医疗保健能力限制.
科学领域:
- 数字健康数字健康
- 医疗信息学 医疗信息学
- 慢性疾病管理 慢性疾病管理
背景情况:
- 关于预防和治疗慢性疾病的证据非常丰富,但很难实施.
- 目前的面对面医疗保健模式已经达到容量,限制了数百万人获得预防性护理的机会.
- 行为变化理论很强大,但难以融入现有医疗保健系统.
研究的目的:
- 通过使用数字卫生工具,提出一个可扩展的慢性疾病预防和治疗框架.
- 利用电子医疗记录和新兴技术进行个性化的患者外展.
- 改善大量患者获得基于证据的护理的机会.
主要方法:
- 利用电子病历数据来识别有风险的患者.
- 实施用于患者沟通和教育的数字健康工具.
- 整合人工智能和患者生成的数据进行个性化干预.
- 通过初级保健团队监督数字外展.
主要成果:
- 拟议的框架允许识别有风险的患者进行主动干预.
- 数字健康工具促进了基于证据的知识和行为改变计划的可扩展交付.
- 该系统旨在灵活地整合新技术,而不会给医疗服务提供者或患者带来负担.
结论:
- 数字健康框架可以克服医疗保健系统对慢性疾病管理的局限性.
- 利用技术可以实现大规模,个性化的预防性护理.
- 这种方法提高了初级保健团队有效管理慢性疾病的能力.
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