The DOI matches its Crossref record; 75 of the 78 references it cites were found in a registry or an index; none of the 68 sources its claims cite is checked for support yet.
Fit for purpose? The GDPR and the governance of European digital health
Open accessAbstract
The introduction of the General Data Protection Regulation (GDPR) in 2018 served as the cornerstone of the new data governance regime of the European Union. Informed by principles and values such as privacy, accountability, transparency, and fairness, the GDPR is premised on the objective to balance the protection of individual privacy and the promotion of a thriving European data economy. Still, shortcomings of this regulatory effort have been noted by recent ethical, socio-political, legal, and policy scholarship. Focusing on the deployment of digital health technologies and big data practices within the European digital health ecosystem, this article draws upon these bodies of literature to chart the main lines of tension emerging between the current GDPR-based data governance regime and the broader societal shifts coming along with the expansion of digital health. Central aspects of the GDPR–i.e. key underlying data protection principles and regulatory categories, the reliance on the “notice-and-consent” model, the (narrow) remit of the Regulation vis-à-vis possible harms and discriminations–are misaligned with the surge in digital health. This throws into doubt whether the Regulation is fully fit for the purpose of governing current developments in this field, while also calling for swift and adequate policy responses.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
The article reviews legal, socio-political, ethical, and policy literature to argue that the GDPR’s data governance regime is misaligned with the expansion of digital health and big data practices. It identifies four broad areas of tension and questions whether the GDPR is fully fit for purpose, calling for swift policy responses.
Key findings
- The GDPR’s traditional data protection principles—especially purpose limitation, data minimization, storage limitation, and transparency—are in tension with digital health practices such as machine learning, repeated/combinatorial data use, and opaque corporate platforms.
- Key regulatory categories are blurred in digital health: “quasi-health data” and re-identification risks undermine the distinctions between sensitive/non-sensitive and identifiable/anonymous data.
- The “notice-and-consent” model is ineffective in digital health contexts due to vague or inaccessible notices, constrained choices, passive acquiescence, and the more than 350,000 “health and fitness” apps available in Google, Apple, and Windows app stores.
- The GDPR has a narrow scope vis-à-vis harms and discrimination from algorithmic social sorting, including group-level harms and difficulties tracing causality, leaving data subjects without adequate legal remedies.
Methods
- Conceptual and literature-based review drawing on data protection, legal, sociological, ethical, and policy scholarship.
- The analysis groups GDPR shortcomings into four broad areas, summarized in Table 1: data protection principles, regulatory categories, informational self-determination/notice-and-consent, and the narrow scope of the Regulation.
- No empirical sample, dataset, or primary data collection is reported; the main analysis is a synthesis of existing literature applied to European digital health.
Limitations
- The paper does not include a dedicated limitations section.
- Evident from the text: it is a literature-based conceptual review, so its claims rest on synthesis of prior scholarship rather than new empirical evidence.
- Evident from the text: the analysis is focused on the European digital health ecosystem and the GDPR, and it notes that national implementation differences will be key, limiting generalizability.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
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Claims the paper makes
49 Own interpretation · 37 Not checked yet
None of the sources cited for this claim have been checked yet.
In the paper
“New technological affordances (such as machine learning and deep learning) (Kuner et al. 2018;Pierce 2018) and the corporate business models of DH platforms (Srnicek 2016;Van Dijck and Poell 2016 van Dijck, Poell, and de Waal 2018), have been shown to defy a number of key principles that have long since governed data protection law.”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
What the sources say
- Not checked yetcites Kuner et al. 2018
- Not checked yetcites Pierce 2018
- Not checked yetcites Srnicek 2016
boosteddirect- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Two principles,”
- Also stated in: § Digital health generates frictions with data protection principles · hedged
“Yet, while representing the main traditional pillars of past and present data protection governance regimes, these principles appear to be in tension with DH, notably with respect to the rise of big data analytics and AI.”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
What the sources say
- Not checked yetcites Pierce 2018
- Not checked yetcites Kuner et al. 2017
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Also stated in: § Digital health generates frictions with data protection principles · hedged
None of the sources cited for this claim have been checked yet.
In the paper
“First, opacity may refer to the proprietary regimes and corporate secrecy under which corporate platforms in DH operate (see, e.g.Kuner et al. 2017;Pasquale 2015;Powles and Hodson 2017).”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
What the sources say
- Not checked yetcites Kuner et al. 2017
- Not checked yetcites Pasquale 2015
- Not checked yetcites Powles and Hodson 2017
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Aside from purpose limitation, data minimization, and storage limitation, a fourth key principle greatly challenged by DH platforms and technologies navigating big data environments is transparency.”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
boosteddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Central aspects of the GDPR-i.e. key underlying data protection principles and regulatory categories, the reliance on the”
- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · plain
“(i) the limited scope of traditional data protection principles in accounting for shifts in modes of data processing enabled by new technological affordances and business models in the DH domain;”
§ Fit for purpose? The GDPR and the governance of European digital health > Abstract
plain- Asserted: passes — The authors put it forward as true.
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- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · plain
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This throws into doubt whether the Regulation is fully fit for the purpose of governing current developments in this field, while also calling for swift and adequate policy responses.”
§ Fit for purpose? The GDPR and the governance of European digital health > Abstract
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
In the paper
“All these issues are further exacerbated by the typical business model of DH platforms -which is largely based on their ability to re-purpose and cross-link different flows of personal data (van Dijck, Poell, and de Waal 2018), and thus appears to collide with the application of these principles.”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
What the sources say
- Not checked yetcites van Dijck, Poell, and de Waal 2018
hedgeddirect- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Central aspects of the GDPR-i.e. key underlying data protection principles and regulatory categories, the reliance on the”
- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · hedged
“(iii) the pitfalls of practices of individual autonomy and control over personal data, which appear ineffective in contemporary DH environments;”
§ Fit for purpose? The GDPR and the governance of European digital health > Abstract
plain- Asserted: passes — The authors put it forward as true.
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- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · hedged
None of the sources cited for this claim have been checked yet.
In the paper
“the GDPR is still predicated on standards that have their roots in past generations of data protection regulations (Kuner et al. 2012;Mantelero 2014).”
§ Fit for purpose? The GDPR and the governance of European digital health > The GDPR: misalignments and tensions with current developments in digital health
What the sources say
- Not checked yetcites Kuner et al. 2012
- Not checked yetcites Mantelero 2014
plain- Asserted: passes — The authors put it forward as true.
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A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Central aspects of the GDPR-i.e. key underlying data protection principles and regulatory categories, the reliance on the”
- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · plain
“(iv) the too narrow scope of the regulation toward individual and societal harms possibly occurring in such environments.”
§ Fit for purpose? The GDPR and the governance of European digital health > Abstract
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Also stated in: § The GDPR: misalignments and tensions with current developments in digital health · plain
- Probably not a substantial claim. 24
- It may state two separate claims as one. 22
- The quote only partly states this claim. 1
In the paper
“the GDPR is premised on the objective to balance the protection of individual privacy and the promotion of a thriving European data economy.”
- Also stated in: § Introduction · plain
“the GDPR is premised on the objective to reconcile two competing requirements, that is, to provide the right balance between a high level of protection for the fundamental right to data protection as well as strong consumer rights in the digital age, on the one side, and the need to create a fair and functioning digital market, with a real chance for growth and innovation, on the other side.”
§ Fit for purpose? The GDPR and the governance of European digital health > Abstract
What the sources say
- Not checked yetcites Albrecht 2016a
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Also stated in: § Introduction · plain
In the paper
“inasmuch as machine learning algorithms”
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
What the sources say
- Not checked yetcites Kuner et al. 2017
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Within the context of healthcare, the risk scores generated by these models can, in turn, refine personalized medical diagnoses, or they can be deployed for hospital administrative purposes, such as for the evaluation of physician performance and pay (Hogle 2016).”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
What the sources say
- Not checked yetcites Hogle 2016
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This way, DHTs render the traditional boundaries between healthcare and other societal domains increasingly instable and porous (Hogle 2016), and this in turn questions still prevalent legal classifications of different types of data (e.g.sensitive, health-related, and anonymous) within”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Consequently, owing also to constant technological advancements, de-identified data -notably genomic data -can be said to present in most contexts residual risk of re-identification, rendering the regulatory machinery revolving around the identifiable/anonymous demarcation increasingly burdensome and ineffective for the protection of data subjects (Quinn and Quinn 2018;Shabani and Marelli 2019).”
§ Fit for purpose? The GDPR and the governance of European digital health > DH pursuits blur GDPR's key regulatory categories
What the sources say
- Not checked yetcites Quinn and Quinn 2018
- Not checked yetcites Shabani and Marelli 2019
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“More broadly, harms deriving from these kinds of discriminations based on algorithmic classifications and social sorting, which may even occur on the basis of biased data or wrongful inferences (Ferryman and Pitcan 2018), can include unfair and unequal treatment, whereby, on the basis of perhaps innocuous attributes, individuals are”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
What the sources say
- Not checked yetcites Mittelstadt 2017
- Not checked yetcites Eubanks 2018
- Not checked yetcites Hogle 2016
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In turn, the rapid expansion of large corporate actors into the health sector holds the potential to fundamentally reconfigure the health ecosystem and its underlying infrastructures, fostering privatization dynamics that are possibly bound to overhaul the public nature of most European healthcare systems.”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Still, these practices and their consequences are often not accounted for nor tackled in legal regimes governing DHTs.”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“This greatly increases the potential for violating”
§ Fit for purpose? The GDPR and the governance of European digital health > The societal performativities of DHTs
What the sources say
- Not checked yetcites Nissenbaum 2004
- Not checked yetcites Lupton 2018
- Not checked yetcites Pasquale 2015
plainconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Information (notice), in this respect, is prodromal to the exercise of self-determination (consent), which in turn should not only be regarded as the expression of choice with respect to the diffusion of personal information, but also as an instrument to negotiate the latter's economic value as the data subject engages in digital transactions (Mantelero 2014, 649).”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Mantelero 2014
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“repeated and combinatorial use of data”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“impossibility to identify purposes at time of data collection”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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Probably not a substantial claim. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“As observed above, the GDPR maintains a narrow focus on the individual, which -howeveroverlooks the fact that privacy invasive practices need not target individuals as such; rather, the mere clustering and classification of individuals into algorithmically constructed groups according to their behaviour, preferences, and other characteristics is sufficient to drive decisions that may potentially”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Gutwirth and Hildebrandt 2008
- Not checked yetcites Mittelstadt 2017
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“opacity of algorithms”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Algorithmic discriminations and privacy harms”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
““transparency paradox””
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“For one thing, notices are often vague (ibid.)or inaccessible, not seldom taking the form of contracts drafted in poorly intelligible legalistic language (Hayden 2012).”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Hayden 2012
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“context transgression”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| § Unintelligibility and/or vagueness of privacy notices: | Informational self-determination |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
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- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
““regular” data types convey sensitive information”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“opacity of corporate business models”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaincorrelational- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This approach -rooted in a distinctively liberal paradigm that conceives of the idea of privacy as an individual right to control the use of one's own data (Schwartz 1999;quoted in Cate 2010) and that frames individuals mostly in terms of consumers (cf.Albrecht 2016a) -revolves around the idea that individuals should be endowed with adequate means to exercise their autonomy and individual choice”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Schwartz 1999
- Not checked yetcites Cate 2010
- Not checked yetcites Albrecht 2016a
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The latter could be equally harmed by misuse or unwanted uses of data, for instance related to access to consumer genomics database such as GEDMatch (Erlich et al. 2018), while at the same time being deprived of the means to prevent the processing operations leading to unwanted uses or misuse, or counter the effects deriving from them (Dove 2018b).”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Erlich et al. 2018
- Not checked yetcites Dove 2018b
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In turn, novel data processing activities perform new forms of social sorting and social classifications, to the potential detriment of relevant parts of the population.”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Additionally, while patterns and correlations used to group individuals are often-times de facto functionally equivalent to personal identifiers (e.g.name, address), and sometimes even to sensitive protected attributes (e.g.ethnicity), it remains questionable whether they are afforded comparable status under the GDPR (Mittelstadt 2017, 479), also owing to misalignments between anti-discrimination”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites Mittelstadt 2017
- Not checked yetcites Drechsler and Benito Sánchez 2018
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“A final, related set of limitations of the current data protection regime concerns the narrow scope provided by the GDPR with respect to the possible individual and societal harms, such as those deriving from practices of algorithmic discrimination and social sorting, caused by the deployment of DHTs -which, as McMahon, Buyx, and Prainsack (2019) argue, results in a significantly lopsided balance”
§ Fit for purpose? The GDPR and the governance of European digital health > DHTs challenge the "notice-and-consent" model
What the sources say
- Not checked yetcites McMahon, Buyx, and Prainsack 2019
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This could prompt national and/or sectoral regulations aimed at tailoring the GDPR to specific processing activities (see conclusions) towards regarding any data as potentially identifiable, healthrelated, and sensitive (McMahon, Buyx, and Prain-sack 2019; Prainsack and Buyx 2017), thus de facto eliminating any pre-defined distinction based on the nature of the data alone.”
§ Fit for purpose? The GDPR and the governance of European digital health > DH pursuits blur GDPR's key regulatory categories
What the sources say
- Not checked yetcites McMahon, Buyx, and Prainsack 2019
- Not checked yetcites Prainsack and Buyx 2017
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All these issues are for the most part forgone by the GDPR -owing perhaps also to the disruptions that more radical departures from the previous legislation could have caused in day-to-day legal practice.”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“New types of actors, in the guise of large consumer technology corporations, make their appearance within the domain of health research and care, rendering the latter prone to the dynamics that characterize emerging forms of digital capitalism.”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: unclear — It is unclear why the paper says it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| § “Lifestylization of healthcare” and use of health data outside | Key categorial distinctions: |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“highly constrained choices, passive acquiescence when consenting”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“propensity for easily waiving privacy rights”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| § New technological affordances (e.g. predictive and inferential analytics): | |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“lack of transparency”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“re-purposing of datasets and context transgression”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| § Open access genomic databases | |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| | § Narrow legal remit |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds. It may state two separate claims as one. The quote only partly states this claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“| § Predictive modelling and risk scores, social sorting: | (Narrow) scope of the |”
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The service provider must generate a report at the request of the user on how the user's data is being processed and used.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [181]
Experimental — accuracy not yet measuredIn the citing paper
“Further, the service provider must also provide the customer with all the data in a format that is readable on the computer.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [181]
In the citing paper
“According to the regulations, a service provider must incorporate facilities of the user's consent and the withdrawal of that consents in their system.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [181]
In the citing paper
“GDPR health regulations [181] outlined privacy laws across Europe to protect user's control and confidentiality on his or her health data.”
From A survey on the adoption of blockchain in IoT: challenges and solutions (2021) · cites this paper as [181]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Fit for purpose? The GDPR and the governance of European digital health > Conclusions
“(Hogle 2016, 423).”
§ Fit for purpose? The GDPR and the governance of European digital health > References
“Hogle, L. F. 2016. "Data-intensive Resourcing in Healthcare." BioSocieties 11 (3): 372-393.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Fit for purpose? The GDPR and the governance of European digital health > Digital health generates frictions with data protection principles
“"unbridled" (Hildebrandt 2015, 212)”
§ Fit for purpose? The GDPR and the governance of European digital health > References
“Hildebrandt, M. 2015. "Smart Technologies and the End(s) of Law: Novel Entanglements of Law and Technology." European Data Protection Law Review 1 (2): 157-159.”
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Cited by
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Gunkel, D. J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0031
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Raimy, R. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0021 · Cited by 1
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Omotubora, A. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0023
Human Rights, Legal Personality, and Artificial Intelligence
Heine, K. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0030 · Cited by 1
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Artificial Intelligence and Racial Discrimination
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Putting Private Sector Responsibility in the Mix
Ebert, I. L., & Lisa, H. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0034
Artificial Intelligence, the Public Space, and the Right to Be Ignored
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The Limits of AI Decision-Making
Gamper, F. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0032
Artificial Intelligence and the Right to an Effective Remedy
de Heer, S. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0020
Artificial Intelligence and Freedom of Assembly
Margaret, W. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0006
The Production of and Control over Data in the AI-Era
van der Sloot, B. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0011
Artificial Intelligence and the Right to Property
Tomada, L., & Xenidis, R. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0007
Artificial Intelligence and Disability Rights
Zarra, A., Favalli, S., & Matilde, C. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0017
Artificial Intelligence and LGBTQ+ Rights
Shahid, M. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.003.0015 · Cited by 2
Rahman, M., Nasfi, N., & Sabri, S. (2024) · JUSIE (Jurnal Sosial dan Ilmu Ekonomi) · doi:10.36665/jusie.v8i01.811
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0009
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0008
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0007
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0006
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0010
Quintavalla, A., & Temperman, J. (2023) · Oxford University Press eBooks · doi:10.1093/law/9780192882486.002.0003
Kazimi, J., & Thalwal, H. (2024) · International Conference on Technological Innovations and Advance Computing (TIACOMP) · doi:10.1109/tiacomp64125.2024.00014
Navigating the Complex Terrain of Medical Big Data
Pandey, V., Verma, V., Sharma, V., & Solanki, S. (2025) · Advances in medical technologies and clinical practice book series · doi:10.4018/979-8-3373-0690-2.ch014
Ethics for Responsible AI in the Middle East
El‐Khoury, M. (2025) · doi:10.1093/9780198945215.003.0045
Zhang, X., Meng, Y., & Li, J. (2025) · Frontiers in Public Health · doi:10.3389/fpubh.2025.1610722
Osakwe, J., Mutelo, S., & Osakwe, N. C. (2025) · Lecture notes in networks and systems · doi:10.1007/978-981-96-6429-0_40
Healthcare Informatics: Transforming Patient Care with Multimodal Machine Learning
Achan, P., Nair, N., & Narayanan, S. (2025) · Springer handbooks · doi:10.1007/978-3-031-81728-1_40
Analyzing GDPR Compliance in IoT Ecosystem with Key Data Protection Strategies and Industry Impact
Harkai, A., & Ciurea, C. E. (2026) · Smart innovation, systems and technologies · doi:10.1007/978-981-95-6136-0_17
Disability Law, Global Bioethics, and Clinical Justice
Anilkumar, A. S., & Veerabathiran, R. (2026) · SpringerBriefs in modern perspectives on disability research. · doi:10.1007/978-981-95-8197-9_7
Malekzadeh, R., Abedi, G., & Abedini, E. (2026) · International Journal of Health Governance · doi:10.1108/ijhg-07-2025-0104
Digital Preparedness: A New Modality of Governance
Rommetveit, K., Delgado, A. M., & van Dijk, N. (2026) · Digital Society · doi:10.1007/s44206-026-00271-5
Computer Vision Enabled Learning Public Health Systems as a Service (CV-LPHSaaS)
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Self-citationTechnological advances in pharmacovigilance
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Metadata
- Authors
- Marelli, L., Lievevrouw, E., & Van Hoyweghen, I.
- Affiliations
- University of Milan (IT)
- KU Leuven (BE)
- Life Sciences & Society Lab, Centre for Sociological Research (CeSO), KU Leuven, Leuven, Belgium
- Corresponding author
- Marelli, Luca
- Venue
- Policy Studies
- Publisher
- Informa UK Limited
- Published
- 2020-02-10
- Volume
- 41
- Issue
- 5
- Pages
- 447-467
- ISSN
- 0144-2872 (ISSN-L)
- 1470-1006
- OpenAlex
- W3006483158
- Cited by
- 137
- References
- 78
- Citations by year
- 2026: 11 · 2025: 13 · 2024: 18 · 2023: 56 · 2022: 12 · 2021: 17 · 2020: 10
- FWCI
- 155.55
- Type
- journal article
- Language
- en
- Open access
- green
- lirias.kuleuven.be
- Licence
- other-oa
- Locations
- Policy Studies (publishedVersion)
- Lirias (KU Leuven) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Fonds Wetenschappelijk Onderzoek (11C8520N, 3H140131)
- H2020 Marie Skłodowska-Curie Actions (753531)
- Topics
- Social Sciences › Law › Digitalization, Law, and Regulation
- Health Sciences › Health Professions › Health Information Management › Thoreau and American Literature
- Physical Sciences › Computer Science › Information Systems › COVID-19 Digital Contact Tracing
- Keywords
- General Data Protection Regulation, data governance, digital health, big data, data protection principles, privacy, data economy, regulatory fit, discrimination, European Union regulation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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