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Health Data Pools Under European Data Protection and Competition Law - Health as a Digital Business (Hardcover, 1st ed. 2022)
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Health Data Pools Under European Data Protection and Competition Law - Health as a Digital Business (Hardcover, 1st ed. 2022)
Series: Munich Studies on Innovation and Competition, 17
Expected to ship within 12 - 17 working days
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This book explores the emerging economic reality of health data
pools from the perspective of European Union policy and law. The
contractual sharing of health data for research purposes is giving
rise to a free movement of research data, which is strongly
encouraged at European policy level within the Digital Single
Market Strategy. However, it has also a strong impact on data
subjects' fundamental right to data protection and smaller
businesses and research entities ability to carry out research and
compete in innovation markets. Accordingly the work questions under
which conditions health data sharing is lawful under European data
protection and competition law. For these purposes, the work
addresses the following sub-questions: i) which is the emerging
innovation paradigm in digital health research?; ii) how are health
data pools addressed at European policy level?; iii) do European
data protection and competition law promote health data-driven
innovation objectives, and how?; iv) which are the limits posed by
the two frameworks to the free pooling of health data? The
underlying assumption of the work is that both branches of European
Union law are key regulatory tools for the creation of a common
European health data space as envisaged in the Commissions 2020
European strategy for data. It thus demonstrates that both European
data protection law, as defined under the General Data Protection
Regulation, and European competition law and policy set research
enabling regimes regarding health data, provided specific normative
conditions are met. From a further perspective, both regulatory
frameworks place external limits to the freedom to share (or not
share) research valuable data.
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