IDEAS home Printed from https://ideas.repec.org/a/taf/thssxx/v12y2023i4p481-494.html
   My bibliography  Save this article

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

Author

Listed:
  • Valeria Pannunzio
  • Maaike Kleinsmann
  • Dirk Snelders
  • Jeroen Raijmakers

Abstract

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.

Suggested Citation

  • Valeria Pannunzio & Maaike Kleinsmann & Dirk Snelders & Jeroen Raijmakers, 2023. "From digital health to learning health systems: four approaches to using data for digital health design," Health Systems, Taylor & Francis Journals, vol. 12(4), pages 481-494, October.
    • Handle: RePEc:taf:thssxx:v:12:y:2023:i:4:p:481-494
    DOI: 10.1080/20476965.2023.2284712
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/20476965.2023.2284712
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/20476965.2023.2284712?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:thssxx:v:12:y:2023:i:4:p:481-494. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/thss .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.