IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i19p11876-d919884.html
   My bibliography  Save this article

Privacy-by-Design Environments for Large-Scale Health Research and Federated Learning from Data

Author

Listed:
  • Peng Zhang

    (Data Science Institute & Department of Computer Science, Vanderbilt University, Nashville, TN 37240, USA)

  • Maged N. Kamel Boulos

    (Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisbon, Portugal)

Abstract

This article offers a brief overview of ‘privacy-by-design (or data-protection-by-design) research environments’, namely Trusted Research Environments (TREs, most commonly used in the United Kingdom) and Personal Health Trains (PHTs, most commonly used in mainland Europe). These secure environments are designed to enable the safe analysis of multiple, linked (and often big) data sources, including sensitive personal data and data owned by, and distributed across, different institutions. They take data protection and privacy requirements into account from the very start (conception phase, during system design) rather than as an afterthought or ‘patch’ implemented at a later stage on top of an existing environment. TREs and PHTs are becoming increasingly important for conducting large-scale privacy-preserving health research and for enabling federated learning and discoveries from big healthcare datasets. The paper also presents select examples of successful TRE and PHT implementations and of large-scale studies that used them.

Suggested Citation

  • Peng Zhang & Maged N. Kamel Boulos, 2022. "Privacy-by-Design Environments for Large-Scale Health Research and Federated Learning from Data," IJERPH, MDPI, vol. 19(19), pages 1-13, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:11876-:d:919884
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/19/11876/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/19/11876/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Tim Hulsen, 2020. "Sharing Is Caring—Data Sharing Initiatives in Healthcare," IJERPH, MDPI, vol. 17(9), pages 1-12, April.
    2. Tanvi Desai & Felix Ritchie & Richard Welpton, 2016. "Five Safes: designing data access for research," Working Papers 20161601, Department of Accounting, Economics and Finance, Bristol Business School, University of the West of England, Bristol.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. David H. Schiller & Johanna Eberle & Daniel Fuß & Jan Goebel & Jörg Heining & Tatjana Mika & Dana Müller & Frank Röder & Michael Stegmann & Karsten Stephan, 2017. "Standards des sicheren Datenzugangs in den Sozial- und Wirtschaftswissenschaften - Überblick über verschiedene Remote-Access-Verfahren," RatSWD Working Papers 261, German Data Forum (RatSWD).
    2. Ian Foster, 2018. "Research Infrastructure for the Safe Analysis of Sensitive Data," The ANNALS of the American Academy of Political and Social Science, , vol. 675(1), pages 102-120, January.
    3. Kalinda E. Griffiths & Jessica Blain & Claire M. Vajdic & Louisa Jorm, 2021. "Indigenous and Tribal Peoples Data Governance in Health Research: A Systematic Review," IJERPH, MDPI, vol. 18(19), pages 1-22, September.
    4. Tim Hulsen, 2022. "Data Science in Healthcare: COVID-19 and Beyond," IJERPH, MDPI, vol. 19(6), pages 1-4, March.
    5. Tapotosh Ghosh & Md Istakiak Adnan Palash & Mohammad Abu Yousuf & Md. Abdul Hamid & Muhammad Mostafa Monowar & Madini O. Alassafi, 2023. "A Robust Distributed Deep Learning Approach to Detect Alzheimer’s Disease from MRI Images," Mathematics, MDPI, vol. 11(12), pages 1-20, June.
    6. Sallie-Anne Pearson & Nicole Pratt & Juliana de Oliveira Costa & Helga Zoega & Tracey-Lea Laba & Christopher Etherton-Beer & Frank M. Sanfilippo & Alice Morgan & Lisa Kalisch Ellett & Claudia Bruno & , 2021. "Generating Real-World Evidence on the Quality Use, Benefits and Safety of Medicines in Australia: History, Challenges and a Roadmap for the Future," IJERPH, MDPI, vol. 18(24), pages 1-20, December.

    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:gam:jijerp:v:19:y:2022:i:19:p:11876-:d:919884. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.