Health Data Pools under European Policy and Data Protection Law: Research as a New Efficiency Defence?

Author:Giulia Schneider
Position:Research Fellow at Lider-Lab, Sant'Anna School of Advanced Studies, Pisa.
Pages:49-67
SUMMARY

The increasing employment of artificial intelligence and machine learning in the biomedical sector as well as the growing number of partnerships aimed at pooling together different types of digital health data, stress the importance of an effective regulation and governance of data sharing in the health and life sciences. This paper explores the emerging economic reality of health data pools from ... (see full summary)

 
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Health Data Pools under European Policy and Data Protection Law
2020
49
1
Health Data Pools under European Policy
and Data Protection Law: Research
as a New Efficiency Defence?
by Giulia Schneider*
© 2020 Giulia Schneider
Everybody may disseminate this ar ticle by electronic m eans and make it available for downloa d under the terms and
conditions of the Digital P eer Publishing Licence (DPPL). A copy of the license text may be obta ined at http://nbn-resolving.
de/urn:nbn:de:0009-dppl-v3-en8.
Recommended citation: Giulia S chneider, Health Data Pools under European Policy and Data Pro tection Law: Research as a
New Efficiency D efence?, 11 (2020) JIPIT EC 49 para 1.
Keywords: Data sharing; Research; Innovation; Data protection; Digital health
After having described the phenomenon of health
data pools as a primary means to conduct research
in digital health markets, the study first contextual-
izes health data sharing practices at European policy
level, with specific reference to the Digital Single Mar-
ket Strategy. Here, both the digital health sector and
the free-flow of information are emerging as strate-
gic areas of European intervention.
Against this backdrop, the second section will enquire
the regulatory framework regarding the processing of
special categories of data for research purposes un-
der the General Data Protection Regulation. As will
be demonstrated, this framework partly disavows
fundamental rights protection objectives, in order to
promote research based on health data and related
market objectives.
Abstract: The increasing employment of artificial in-
telligence and machine learning in the biomedical
sector as well as the growing number of partner-
ships aimed at pooling together different types of
digital health data, stress the importance of an ef-
fective regulation and governance of data sharing in
the health and life sciences. This paper explores the
emerging economic reality of health data pools from
the perspective of European Union policy and law.
The goal of the study is to validate the role of the in-
ternal market integration objective in the data pro-
tection framework of special categories of data, and
thus to unveil the alignment of the General Data
Protection Regulation’s research exemption with
the broader policy goals of the Digital Single Market
Strategy.
A. Introduction and Outline
of the Study
1

and machine learning in the biomedical sector as
well as the growing number of partnerships aimed
at pooling together different types of digital health
data, stress the importance of an effective regulation
and governance of data sharing in the health and
      
economic reality of health data pools from the
perspective of European Union policy and law. The
goal of the study is to validate the role of the internal
market integration objective in the data protection
framework of special categories of data, and thus to
unveil the alignment of the General Data Protection
    
the processing of special categories of data with the
broader policy goals of the Digital Single Market
Strategy.
2
Innovation in health-related markets, such as the
ones of medical devices and pharmaceuticals is
growingly occurring through the door of digitisation
 1. This means that in the
* Research Fellow at Lider-Lab, Sant’Anna School of Advanced
Studies, Pisa.
1         ,
  
      
2020
Giulia Schneider
50
1

as well as highly sophisticated analytical techniques
are needed in order to achieve innovation in health-
related markets2.
3
Traditional actors in the healthcare setting, such
as pharmaceutical companies or public healthcare
providers, lack of the needed information-

looking for the support of big data companies, which
own mass amounts of users’ data, who have the
standard technical infrastructure in order to run
  
prompter clinical responses. On the other hand,
big data companies entering health markets need
the more sophisticated health-related data and the

sector have.
4 As a result of the matching between these different
economic interests, the conduction of healthcare
    
architecture, where courses of biomedical
innovation are driven by new forms of collaborative
networks3 between high-tech companies, and
traditional stakeholders in the health sector such
as pharmaceutical companies and public health
providers4. These collaborations’ primary goal
relates to the sharing of different types of health
data.
relies principally on pure information goods: collected
data, patterns discovered within that data, and validation

2        
datasets is key for the success and commercial value of
companies acting in digital markets is stressed by Karl-
Heinz Fezer, ‘Data Property of the People-An Intrinsic
Intellectual Property Law Sui Generis Regarding People’s
Behavior-generated Informational Data’ (2017) Zeitschrift
        
reality of the market, behaviour-generated informational
data represents a tradable commodity and crucial asset in a

3        -Matos
and Hamideh Afsarmanesh, ‘Collaborative Networks-Value
Creation in a Knowledge Society’ in: Kesheng Wang and
George L. Kovacs and Michael Wozny and Minglun Fang
(eds.), Knowledge Enterprise: Intelligent Strategies in Product
Design, Manufacturing, and Management (Springer, 2006) 26-
40.
4 From a more general perspective, not strictly related to
the medical sector, the emergence of new collaboration
scenarios characterising high technology markets, is well
highlighted by Giuseppe Colangelo, Mercato e cooperazione
tecnologica. I contratti di patent pooling (Giuffrè- Quaderni di
Aida, 2008) 32 ff.
These sharing practices are giving rise to outright
5.
5  
valuable asset, the accessibility and the processing of
which is ever more becoming essential for research

health. Economic advancements in this sector are in
turn believed to promisingly heighten the standard
of health overall enjoyed.
6
Health data availability is indeed believed to improve
and fasten the design of digital health products, in
terms of optimisation and personalisation of the
manufacturing processes and with related gains in
terms of quality of the resulting products6.
7
In these regards, according to a growing strand
of the literature, regulatory incentives and a
correspondent legislative action are needed in order
    
health through the aggregation of differently owned
datasets7.
5 In this regard, some strand of the literature has referred to

and social arrangements underpinning the environments in

Sonja Marjanovic and Ioana Ghiga-Miaoqing Yang and Anna
Knack, ‘Understanding Value in Health Data Ecosystems-
A Review of Current Evidence and Ways Forward’ (Rand,
2017) 1 online available at <https://www.rand.org/pubs/
research_reports/RR1972.html>. Emphasis added. Similarly,
also Effy Vayena and Alessandro Blasimme, ‘Biomedical
Big Data: New Models of Control over Access, Use and
Governance’ (2017) 14 Bioethical Enquiry, 501, 503, where
     
and processes that rely on the production and circulation of

6 Björn LindqvistCompetition and Data Pools’ (2018) Journal
of European Consumer and Market Law, 146, 147-148.
7 Arti K. Rai, ‘Risk Regulation and Innovation: the Case of
Rights-Encumbered Biomedical Data Silos’ (2017) 92, 4
Notre Dame Law Review, 101 ff.; Rebecca S. Eisenberg and
Arti K. Rai, ‘    
Sponsored Research: Intellectual Property Rights and
Data Sharing in California Stem’s Cell Initiative’ (2006) 21
Berkeley Technology Law Journal, 1187, 1196-1199. Against
this backdrop, the proposed legal incentives are both of
private nature, as the establishment of a right to property
over health data and the creation of public funders resource
      
to promote data pooling. See, e.g., Jorge L. Contreras,
‘Leviathan in the Commons: Biomedical Data and the State’
in: Katherine J. Strandburg- Michael J. Madison- Brett M.
Frischmann (ed.), Governing Medical Knowledge Commons
(Cambridge University Press, 2017) 9-18.

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