Abstract

BackgroundThe meaningful sharing of health data between different stakeholders is central to the advancement of science and to improve care offered to individual patients. However, it is important that the interests of individual stakeholders involved in this data sharing ecosystem are taken into account to ensure fair data sharing practices. In this regard, this qualitative study investigates such practices from the perspectives of a subset of relevant Swiss expert stakeholders, using a distributive justice lens.MethodsUsing purposive and snowball sampling methodologies, 48 expert stakeholders from the Swiss healthcare and research domains were recruited for semi-structured interviews. After the experts had consented, the interviews were audio-recorded and transcribed verbatim, but omitting identifying information to ensure confidentiality and anonymity. A thematic analysis using a deductive approach was conducted to identify fair data sharing practices for secondary research purposes. Themes and subthemes were then identified and developed during the analysis.ResultsThree distributive justice themes were identified in the data sharing negotiation processes, and these are: (i) effort, which was subcategorized into two subthemes (i.e. a claim to data reciprocity and other reciprocal advantages, and a claim to transparency on data re-use), (ii) compensation, which was subcategorized into two subthemes (i.e. a claim to an academic compensation and a claim to a financial compensation), and lastly, (iii) contribution, i.e. the significance of data contributions should be matched with a corresponding reward.ConclusionsThis qualitative study provides insights, which could inform policy-making on claims and incentives that encourage Swiss expert stakeholders to share their datasets. Importantly, several claims have been identified and justified under the basis of distributive justice principles, whilst some are more debatable and likely insufficient in justifying data sharing activities. Nonetheless, these claims should be taken seriously and discussed more broadly. Indeed, promoting health research while ensuring that healthcare systems guarantee better services, it is paramount to ensure that solutions developed are sustainable, provide fair criteria for academic careers and promote the sharing of high quality data to advance science.

Highlights

  • The meaningful sharing of health data between different stakeholders is central to the advancement of science and to improve care offered to individual patients

  • Individual notions of fair data sharing Three themes pertinent to the desert-based justice principles were identified in the data extracts, namely (i) effort, which was further categorized into two subthemes, (ii) compensation, which was subcategorized into two sub-themes, and (iii) contribution (Fig. 1)

  • « ... you have to realize that if you want to share the data, everyone needs to have the data and everyone needs to have more or less the same data. As it is very competitive, you will not necessarily want to share from a personal and scientific point of view what you have made a particular effort for, you have obtained the funds, you have found people, you have made a research project and you don't necessarily want what was a huge job for you to become ... part of a bigger project on the same topic where you lose all personal effort » Res6. This qualitative study explores the individual notions of fair data sharing from the perspectives of Swiss expert stakeholders, through the lens of distributive justice as an analytical framework

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Summary

Introduction

The meaningful sharing of health data between different stakeholders is central to the advancement of science and to improve care offered to individual patients. Over the past few decades, data sharing has become an increasingly discussed topic in the scientific literature It has further regained impetus following the approval of the European General Data Protection Regulation (GDPR) and its enforcement in 2018 [1]. Recognizing the value of research datasets to advance science beyond their initial contribution, the open data movement has been taken up by the scholarly data publishing ecosystem. This led to data sharing requirements as a pre-publication condition for researchers (e.g., enforced by funders and journals [10]) and the creation of online data repositories for many scientific disciplines. The Harvard Dataverse Repository allows researchers to “open [their] data to the general public, or restrict access and define customizable terms of use” [11]

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