From digital health to learning health systems: four approaches to using data for digital health design

被引：3

作者：

Pannunzio, Valeria ^{[1
]}

Kleinsmann, Maaike ^{[1
]}

Snelders, Dirk ^{[1
]}

Raijmakers, Jeroen ^{[1
,2
]}

机构：

[1] Delft Univ Technol, Fac Ind Design Engn, Dept Design Org & Strategy, Landbergstr 15, NL-2628 Delft, Netherlands

[2] Philips, Philips Experience Design, Eindhoven, Netherlands

来源：

HEALTH SYSTEMS | 2023年 / 12卷 / 04期

关键词：

Healthcare design science; clinical systems and Informatics; decision support systems; data mining & data analytics; CARE; INNOVATION;

D O I：

10.1080/20476965.2023.2284712

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Digital health technologies, powered by digital data, provide an opportunity to improve the efficacy and efficiency of health systems at large. However, little is known about different approaches to the use of data for digital health design, or about their possible relations to system-level dynamics. In this contribution, we identify four existing approaches to the use of data for digital health design, namely the silent, the overt, the data-enabled, and the convergent. After characterising the approaches, we provide real-life examples of each. Furthermore, we compare the approaches in terms of selected desirable characteristics of the design process, highlighting relative advantages and disadvantages. Finally, we reflect on the system-level relevance of the differentiation between the approaches and point towards future research directions. Overall, the contribution provides researchers and practitioners with a broad conceptual framework to examine data-related challenges and opportunities in digital health design.

引用

页码：481 / 494

页数：14

共 85 条

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