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Sharing Is Caring—Data Sharing Initiatives in Healthcare

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  • Tim Hulsen

    (Department of Professional Health Solutions & Services, Philips Research, 5656AE Eindhoven, The Netherlands)

Abstract

In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these ‘big data’ put together can be utilized to optimize treatments for each unique patient (‘precision medicine’). For this to be possible, it is necessary that hospitals, academia and industry work together to bridge the ‘valley of death’ of translational medicine. However, hospitals and academia often are reluctant to share their data with other parties, even though the patient is actually the owner of his/her own health data. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. There are some publicly available datasets, but these are usually only shared after study (and publication) completion, which means a severe delay of months or even years before others can analyse the data. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here, we show an analysis of the current literature around data sharing, and we discuss five aspects of data sharing in the medical domain: publisher requirements, data ownership, growing support for data sharing, data sharing initiatives and how the use of federated data might be a solution. We also discuss some potential future developments around data sharing, such as medical crowdsourcing and data generalists.

Suggested Citation

  • Tim Hulsen, 2020. "Sharing Is Caring—Data Sharing Initiatives in Healthcare," IJERPH, MDPI, vol. 17(9), pages 1-12, April.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:9:p:3046-:d:351133
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    References listed on IDEAS

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    1. Declan Butler, 2008. "Translational research: Crossing the valley of death," Nature, Nature, vol. 453(7197), pages 840-842, June.
    2. Heather A Piwowar & Roger S Day & Douglas B Fridsma, 2007. "Sharing Detailed Research Data Is Associated with Increased Citation Rate," PLOS ONE, Public Library of Science, vol. 2(3), pages 1-5, March.
    3. Monya Baker, 2016. "1,500 scientists lift the lid on reproducibility," Nature, Nature, vol. 533(7604), pages 452-454, May.
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    Cited by:

    1. 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.
    2. 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.
    3. Tim Hulsen, 2022. "Data Science in Healthcare: COVID-19 and Beyond," IJERPH, MDPI, vol. 19(6), pages 1-4, March.

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