Responsible data sharing in international health research: a systematic review of principles and norms

BMC Medical Ethics
http://www.biomedcentral.com/bmcmedethics/content
(Accessed 30 Mar 2019)

Research article
|   28 March 2019
Responsible data sharing in international health research: a systematic review of principles and norms
Authors: Shona Kalkman, Menno Mostert, Christoph Gerlinger, Johannes J. M. van Delden and Ghislaine J. M. W. van Thiel
Abstract
Background
Large-scale linkage of international clinical datasets could lead to unique insights into disease aetiology and facilitate treatment evaluation and drug development. Hereto, multi-stakeholder consortia are currently designing several disease-specific translational research platforms to enable international health data sharing. Despite the recent adoption of the EU General Data Protection Regulation (GDPR), the procedures for how to govern responsible data sharing in such projects are not at all spelled out yet. In search of a first, basic outline of an ethical governance framework, we set out to explore relevant ethical principles and norms.
Methods
We performed a systematic review of literature and ethical guidelines for principles and norms pertaining to data sharing for international health research.
Results
We observed an abundance of principles and norms with considerable convergence at the aggregate level of four overarching themes: societal benefits and value; distribution of risks, benefits and burdens; respect for individuals and groups; and public trust and engagement. However, at the level of principles and norms we identified substantial variation in the phrasing and level of detail, the number and content of norms considered necessary to protect a principle, and the contextual approaches in which principles and norms are used.
Conclusions
While providing some helpful leads for further work on a coherent governance framework for data sharing, the current collection of principles and norms prompts important questions about how to streamline terminology regarding de-identification and how to harmonise the identified principles and norms into a coherent governance framework that promotes data sharing while securing public trust.