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Digital phenotyping and sensitive health data: Implications for data governance.

Ignacio Perez-PozueloDimitris SpathisJordan Gifford-MooreJessica MorleyJosh Cowls
Published in: Journal of the American Medical Informatics Association : JAMIA (2021)
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.
Keyphrases
  • electronic health record
  • big data
  • healthcare
  • public health
  • mental health
  • health information
  • machine learning
  • gene expression
  • high throughput
  • dna methylation
  • social media
  • clinical practice
  • replacement therapy