从数字健康到学习健康系统:使用数据用于数字健康设计的四种方法
Valeria Pannunzio1, Maaike Kleinsmann1, Dirk Snelders1
1Department of Design, Organization and Strategy, Faculty of Industrial Design Engineering, Delft University of Technology, Delft, the Netherlands.
Health systems (Basingstoke, England)
|January 18, 2024
概括
这项研究确定了数字健康设计的四种数据使用方法:无声,公开,数据支持和融合. 了解这些方法有助于优化数字健康解决方案和系统级动态.
科学领域:
- 数字健康数字健康
- 医疗信息学 医疗信息学
- 系统科学 系统科学
背景情况:
- 数字健康技术利用数据来提高卫生系统的效率和有效性.
- 对于数字健康设计中的各种数据利用策略及其对系统动态的影响的理解有限.
研究的目的:
- 识别和描述数字健康设计中数据使用的不同方法.
- 根据设计过程特征和系统级相关性来比较这些方法.
- 为数字健康领域的研究人员和从业人员提供一个概念框架.
主要方法:
- 文献审查和概念分析以确定数据使用方法.
- 方法的分类:沉默,公开,数据支持和融合.
- 使用选择的设计特征和现实世界的例子对方法进行比较分析.
主要成果:
- 确定并定义了数字健康设计中使用数据的四种不同的方法.
- 每种方法都显示了设计过程的独特优缺点.
- 该研究强调了不同数据利用策略对系统层面的影响.
结论:
- 提出了一个概念框架,以指导对数字健康设计中与数据相关的挑战和机会的审查.
- 这些发现为优化数字健康干预和改善卫生系统性能提供了见解.
- 建议进行进一步的研究,以探索这些数据使用方法的长期系统级影响.
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