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Digital phenotyping and sensitive health data: Implications for data governance

Ignacio Perez-Pozuelo, Dimitris Spathis, Jordan Gifford-Moore, Jessica Morley, Josh Cowls

2021Journal of the American Medical Informatics Association32 citationsDOIOpen Access PDF

Abstract

In this perspective we want to highlight the rise of what we call "digital phenotyping" or inferring insights about peopleãs health and behavior from their digital devices and data, and the challenges this introduces. Indeed, the collection, processing, and storage of data comes with significant ethical, security and data governance considerations. The COVID-19 pandemic has laid bare the importance of scientific data and modeling, both to understand the nature and spread of the disease, and to develop treatment. But digital devices have also played a (controversial) role, with track and trace systems and increasingly "vaccine passports" being rolled out to help societies open back up. These systems epitomize a wider and longer-standing trend towards seeing almost any form of personal data as potentially health data, especially with the rise of consumer health trackers and other gadgets. Here, we offer an overview of the risks this introduces, drawing on the earlier revolution in genomic sequencing, and propose guidelines to help protect privacy whilst utilizing personal data to help get society back up to speed.

Topics & Concepts

Data scienceData governanceDigital healthTRACE (psycholinguistics)Computer scienceInternet privacyCorporate governanceBitTorrent trackerSoftware deploymentBig dataHealth dataPerspective (graphical)Data collectionPandemicData Protection Act 1998Digital RevolutionCoronavirus disease 2019 (COVID-19)Computer securityData securityHealth careBusinessPolitical scienceMedicineData miningSociologyDiseaseInfectious disease (medical specialty)MarketingArtificial intelligenceTelecommunicationsEye trackingFinanceMetric (unit)LinguisticsLawData qualitySocial scienceOperating systemPhilosophyEncryptionEthics in Clinical ResearchEthics and Social Impacts of AIPrivacy-Preserving Technologies in Data
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