“The European health data space paves the way for a wave of innovation for the benefit of patients”
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Lhe European Commission chose, on July 20, to entrust the Health Data Huba consortium of sixteen partners from ten different countries, the construction, from September, of a first version of the future ” european health data area (European Health Data Space, EDHS in English).
May’s beginning, it presented its proposal for a regulation on the European health data area, which will soon be submitted to the Council of the European Union and then to the European Parliament. The choice of the operator, now confirmed, therefore brings the EDHS a little closer to reality, without however removing all the “reservations”. These relate in particular to the choice of Microsoft Azurean American player, as a host of this health data, and on the assurance that this data will not be able to cross the Atlantic.
To this question, as to others which will not fail to arise, it will be necessary to provide strong and transparent answers. These will guarantee a confidence without which the long-term investment would be compromised. But the stakes are high. The vocation of the EDHS is to “putting citizens at the center, giving them the power to control their data in order to benefit from better health care”in the words of Stella Kyriakides, European Commissioner for Health and Food Safety.
The EDHS paves the way for a wave of innovations for the benefit of patients and must also allow the formation of a single European market for digital therapies, equipped with common rules, which, in turn, will promote the emergence of a competitive European health technology fabric in the face of American competition.
A gold mine
At the heart of this revolution – and this is what makes the issue of data protection so sensitive – is “patient data”. Enhanced by artificial intelligence (AI) and big data, these are a gold mine for the identification of biological markers and the interpretation of data.
These markers are themselves the basis of new diagnostic tools (medical imaging, biology) and prevention tools (interpretation of symptoms, analysis of drug interactions) which are being deployed at high speed in hospitals and medical practices.
In diabetes and oncology, devices “point of care” [« au plus près des patients »]installed on smartphones and made smart thanks to the machine learningsupport patients in monitoring their pathology and their therapy, while keeping healthcare professionals “in the loop”.
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