Digital diabetes: Perspectives for diabetes prevention, management and research

G. Fagherazzi*, P. Ravaud

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

66 Citations (Scopus)


Digital medicine, digital research and artificial intelligence (AI) have the power to transform the field of diabetes with continuous and no-burden remote monitoring of patients’ symptoms, physiological data, behaviours, and social and environmental contexts through the use of wearables, sensors and smartphone technologies. Moreover, data generated online and by digital technologies – which the authors suggest be grouped under the term ‘digitosome’ – constitute, through the quantity and variety of information they represent, a powerful potential for identifying new digital markers and patterns of risk that, ultimately, when combined with clinical data, can improve diabetes management and quality of life, and also prevent diabetes-related complications. Moving from a world in which patients are characterized by only a few recent measurements of fasting glucose levels and glycated haemoglobin to a world where patients, healthcare professionals and research scientists can consider various key parameters at thousands of time points simultaneously will profoundly change the way diabetes is prevented, managed and characterized in patients living with diabetes, as well as how it is scientifically researched. Indeed, the present review looks at how the digitization of diabetes can impact all fields of diabetes – its prevention, management, technology and research – and how it can complement, but not replace, what is usually done in traditional clinical settings. Such a profound shift is a genuine game changer that should be embraced by all, as it can provide solid research results transferable to patients, improve general health literacy, and provide tools to facilitate the everyday decision-making process by both healthcare professionals and patients living with diabetes.

Original languageEnglish
Pages (from-to)322-329
Number of pages8
JournalDiabetes and Metabolism
Issue number4
Publication statusPublished - Sept 2019
Externally publishedYes


  • Artificial intelligence
  • Big data
  • Diabetes
  • Social media
  • Technology


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