Resisting big data exploitations in public healthcare: free riding or distributive justice?

Vezyridis, Paraskevas; Timmons, Stephen

doi:10.1111/1467-9566.12969

Cited by 21 publications

(20 citation statements)

References 54 publications

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“…The latter may also help to explain why there was a clear preference for making their DNA and medical information available to non-profit research in the German sample (see Table 3), which could be seen as a commitment to using one's personal data in such a way that it creates public benefits. This interpretation is in line with findings from a qualitative study on NHS England's care.data programme and the reasons as to why people opt out [20].…”

Section: Discussionsupporting

confidence: 84%

Willingness to donate genomic and other medical data: results from Germany

et al. 2020

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This paper reports findings from Germany-based participants in the "Your DNA, Your Say" study, a collaborative effort among researchers in more than 20 countries across the world to explore public attitudes, values and opinions towards willingness to donate genomic and other personal data for use by others. Based on a representative sample of German residents (n = 1506) who completed the German-language version of the survey, we found that views of genetic exceptionalism were less prevalent in the German-language arm of the study than in the English-language arm (43% versus 52%). Also, people's willingness to make their data available for research was lower in the German than in the Englishlanguage samples of the study (56% versus 67%). In the German sample, those who were more familiar with genetics, and those holding views of genetic exceptionalism were more likely to be willing to donate data than others. We explain these findings with reference to the important role that the "right of informational self-determination" plays in German public discourse. Rather than being a particularly strict interpretation of privacy in the sense of a right to be left alone, the German understanding of informational self-determination bestows on each citizen the responsibility to carefully consider how their personal data should be used to protect important rights and to serve the public good.

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Section: Discussionsupporting

confidence: 84%

Willingness to donate genomic and other medical data: results from Germany

et al. 2020

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“…(Researcher 11) Lastly, and notwithstanding some criticism on issues of medical confidentiality (Brown et al, 2010), these research services have not attracted the public outcry provoked by other exploitations of these public datasets, namely NHS England's defunct care.data (see Freeman, 2016;Vezyridis and Timmons, 2017), and Alphabet's DeepMind unlawful contractual data arrangements with certain London NHS Trusts (see Powles and Hodson, 2017). Citizens interviewed were generally supportive of research that benefits the common good but were increasingly skeptical of NHS patient data exploitations that often take place away from the public eye, especially after the aforementioned debacles (Skovgaard et al, 2019;Vezyridis and Timmons, 2019). However, they emphasized the great challenge they face, as NHS patients, to get access to their EHR in order to understand what is in there that such research services continuously assetize.…”

Section: Politics Economics and Societal Valuations For Asymmetrical Asset Flowsmentioning

confidence: 99%

“…Some researchers understood information governance in this area to be a ‘hygienic’ practice in ethics (Vezyridis and Timmons, 2019) of critical importance for minimizing moral frictions and, thus, maintaining ‘social sustainability’ (Brown and Michael, 2003; Tupasela, 2017) with the public and the healthcare professionals that co-produce the data. Others, acknowledging their limited understanding of the complicated legal framework surrounding the use of these datasets, suggested the introduction of new disciplines within research teams (e.g.…”

Section: Politics Economics and Societal Valuations For Asymmetrical Asset Flowsmentioning

confidence: 99%

“…While it has facilitated an unprecedented expansion of the so called 'secondary use' of NHS patient data, during the interviews, it was still problematised as an unavoidable but also necessary burden within organisational and scientific routines: a bureaucratic activity separate from the wider societal and historical context of unconsented medical research and part of the costs involved with the assetisation of these datasets. Some researchers understood information governance in this area to be a 'hygienic' practice in ethics (Vezyridis and Timmons, 2019) of critical importance for minimising moral frictions and, thus, maintaining 'social sustainability' (cf. Brown and Michael, 2003;Tupasela, 2017) with the public and the healthcare professionals that co-produce the data.…”

Section: Politics Economics and Societal Valuations For Asymmetrical Asset Flowsmentioning

confidence: 99%

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E-Infrastructures and the divergent assetization of public health data: Expectations, uncertainties, and asymmetries

Vezyridis

Timmons

2021

Soc Stud Sci

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In this article, we examine some of the expectations, frictions and uncertainties involved with the assetization of de-identified NHS patient data by (primary care) research services in UK. Pledges to Electronic Health Record (EHR) data-driven research attempt to reconfigure public health data as an asset for realizing multiple values across healthcare, research and finance. We introduce the concept of ‘asymmetrical divergence’ in public health data assetization to study the various practices of configuring and using this data, both as a continuously generated resource to be extracted and as an asset to be circulated in the knowledge economy. As data assetization and exploitations grow bigger and more diverse, the capitalization of these datasets may constitute EHR data-driven research in healthcare as an attractive technoscientific activity, but one limited to those actors with specific sociotechnical resources in place to fully exploit them at the required scale.

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“…However, there are a limited number of studies that consider the effect of GDP and free-riding behavior. Free-riding behavior is not conducive to group development because it affects the initiative of individuals [14]. Therefore, free-riding behavior should be considered in the decision-making process of the closed-loop supply chain.…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Game Theory Study for Construction and Demolition Waste Recycling Considering Green Development Performance under the Chinese Government’s Reward–Penalty Mechanism

Long

Liu

et al. 2020

IJERPH

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The low efficiency of the closed-loop supply chain in construction and demolition waste (CDW) recycling has restricted the green development of China’s construction industry. Additionally, the government’s reward–penalty mechanism has a huge influence on green development. This study aimed to investigate the effect of green development performance (GDP) and the government’s reward–penalty mechanism on the decision-making process of production and recycling units, as well as to reveal the optimal strategies under different conditions. Therefore, the strategies’ evolutionary paths of production and recycling units were investigated by using evolutionary game theory. Firstly, an evolutionary game model between production units and recycling units was proposed under the government’s reward–penalty mechanism. Then, the evolutionary stability strategies in different scenarios were discussed. Finally, the effects of the relevant parameters on the evolutionary paths of the game model were analyzed using numerical simulations. The main conclusions are as follows. (1) When the range of GDP changes, the evolutionary stable strategy changes accordingly. GDP plays a positive role in promoting the high-quality development of the CDW recycling supply chain, but an increase in GDP can easily lead to the simultaneous motivation of free-riding. (2) The government’s reward–penalty mechanism effectively regulates the decision-making process of production and recycling units. An increase in the subsidy rate and supervision probability helps to reduce free-riding behavior. Moreover, the incentive effect of the subsidy probability on recycling units is more obvious, while the effect of the supervision probability on improving the motivation of active participation for production units is more remarkable. This paper not only provides a decision-making basis to ensure production and recycling units to make optimal strategy choices under different conditions but also provides a reference for the government to formulate a reasonable reward–penalty mechanism that is conducive to a macro-control market.

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Resisting big data exploitations in public healthcare: free riding or distributive justice?

Cited by 21 publications

References 54 publications

Willingness to donate genomic and other medical data: results from Germany

Willingness to donate genomic and other medical data: results from Germany

E-Infrastructures and the divergent assetization of public health data: Expectations, uncertainties, and asymmetries

An Evolutionary Game Theory Study for Construction and Demolition Waste Recycling Considering Green Development Performance under the Chinese Government’s Reward–Penalty Mechanism

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