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Digital phenotyping and sensitive health data: Implications for data governance.
Perez-Pozuelo, Ignacio; Spathis, Dimitris; Gifford-Moore, Jordan; Morley, Jessica; Cowls, Josh.
  • Perez-Pozuelo I; MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom.
  • Spathis D; The Alan Turing Institute, London, United Kingdom.
  • Gifford-Moore J; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Morley J; School of Law, University of Oxford, Oxford, United Kingdom.
  • Cowls J; Oxford Internet Institute, University of Oxford, Oxford, United Kingdom.
J Am Med Inform Assoc ; 28(9): 2002-2008, 2021 08 13.
Article in English | MEDLINE | ID: covidwho-1393285
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Jamia

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Prognostic study Topics: Vaccines Limits: Humans Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2021 Document Type: Article Affiliation country: Jamia