Intended for healthcare professionals


How precision medicine and screening with big data could increase overdiagnosis

BMJ 2019; 366 doi: (Published 13 September 2019) Cite this as: BMJ 2019;366:l5270
  1. Henrik Vogt, postdoctoral fellow1 2 3,
  2. Sara Green, assistant professor4 5,
  3. Claus Thorn Ekstrøm, professor6,
  4. John Brodersen, professor7 8
  1. 1Centre for Medical Ethics, University of Oslo, Oslo, Norway
  2. 2Hybrid Technology Hub, University of Oslo, Oslo, Norway
  3. 3General Practice Research Unit, Norwegian University of Science and Technology, Trondheim, Norway
  4. 4Department of Science Education, University of Copenhagen, Copenhagen, Denmark
  5. 5Centre for Medical Science and Technology Studies, University of Copenhagen, Denmark
  6. 6Biostatistics, Department of Public Health, University of Copenhagen, Denmark
  7. 7Centre of Research and Education in General Practice, University of Copenhagen, Denmark
  8. 8Primary Health Care Research Unit, Region Zealand, Denmark
  1. Correspondence to: H. Vogt henrik.vogt{at}

Precision medicine based on big data promises to revolutionise disease prevention but increases the challenge of determining which abnormalities will be clinically important, argue Henrik Vogt and colleagues

Since the Human Genome Project in the 1990s, there has been discussion of how precision medicine (or personalised medicine) might prevent morbidity and mortality by diagnosing disease early or finding risk factors in apparently healthy people.1 At first, the idea was mostly tied to genome analysis. However, during the past two decades many other big data and machine learning technologies have emerged to measure and analyse other factors.234567

“Big data” can mean many things.8 We use it to describe newer, data intensive technologies that might enable precision medicine.4 These include “omic” technologies such as genomics (DNA), proteomics (protein), transcriptomics (RNA), and metabolomics (metabolites).7 It also includes data from imaging, electronic health records, social media, new biosensors,30 and self tracking technologies such as the Apple smartwatch that can detect arrhythmias.9 In future such sensors may be able to pick up signals from blood, sweat, or environmental exposures.3

Proponents of screening based on these new technologies say they enable unprecedented monitoring of the human body.234567 However, we believe that their plans, which are still largely theoretical, come with a high risk of overmedicalisation10111213 and overdiagnosis.1415

What is different about big data screening?

Current screening typically involves measuring one variable or a few variables, either once or at long intervals. Big data screening differs from traditional screening because it can measure many different types of variable (from the molecular to the social). It can include many variables at the same time, and measurement can be repetitive or continual, showing bodily changes over time.

This may create a …

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