European Journal of Epidemiology

, Volume 33, Issue 3, pp 245–257 | Cite as

Epidemiology in wonderland: Big Data and precision medicine

ESSAY

Abstract

Big Data and precision medicine, two major contemporary challenges for epidemiology, are critically examined from two different angles. In Part 1 Big Data collected for research purposes (Big research Data) and Big Data used for research although collected for other primary purposes (Big secondary Data) are discussed in the light of the fundamental common requirement of data validity, prevailing over “bigness”. Precision medicine is treated developing the key point that high relative risks are as a rule required to make a variable or combination of variables suitable for prediction of disease occurrence, outcome or response to treatment; the commercial proliferation of allegedly predictive tests of unknown or poor validity is commented. Part 2 proposes a “wise epidemiology” approach to: (a) choosing in a context imprinted by Big Data and precision medicine—epidemiological research projects actually relevant to population health, (b) training epidemiologists, (c) investigating the impact on clinical practices and doctor-patient relation of the influx of Big Data and computerized medicine and (d) clarifying whether today "health" may be redefined—as some maintain in purely technological terms.

Keywords

Big data Datome Doctor-patient relation Epidemiological research Epidemiology training Health definition Population health Precision for commerce Precision medicine Validity Wise epidemiology 

Notes

Acknowledgements

I wish to thank Albert Hofman for his invitation to write this essay and for his patience in waiting for it.

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Authors and Affiliations

  1. 1.LyonFrance

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