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Responsible data sharing in a big data-driven translational research platform: lessons learned.

S Kalkman^1,2, M Mostert³, N Udo-Beauvisage⁴

¹Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Universiteitsweg 100, 3584, CG, Utrecht, the Netherlands. s.kalkman@umcutrecht.nl.

BMC Medical Informatics and Decision Making

|January 1, 2020

Summary

This summary is machine-generated.

Ethical governance for health data sharing requires clear conditions. Analysis of the Innovative Medicines Initiative

Keywords:

Big data Data access Data sharing Ethics Governance

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Area of Science:

Health Research
Data Governance
Big Data

Background:

Responsible data sharing in health research necessitates ethical governance beyond the EU General Data Protection Regulation.
A framework for Big Data-driven research platforms must consider a priori conditions for individual datasets.
The Innovative Medicines Initiative's (IMI) BigData@Heart platform's data sharing conditions were analyzed.

Purpose of the Study:

To identify and analyze the conditions for data sharing within the BigData@Heart platform.
To inform the design of an ethical governance framework for Big Data research platforms.

Main Methods:

A descriptive case study was conducted on the conditions for data sharing in BigData@Heart.
Principle investigators of 56 databases were contacted for documentation on data sharing conditions.
Documents were qualitatively reviewed for data sharing and access conditions.

Main Results:

Qualitative content analysis of 55 documents revealed common conditions for data sharing.
Key conditions include sharing health data only for scientific research, in anonymized/coded form, with review committee approval, and ensuring data security and legal compliance.
Overlapping conditions were identified across participating datasets.

Conclusions:

Prespecified conditions, despite overlap, present challenges for data sharing.
These challenges offer insights for designing ethical governance frameworks for data sharing platforms.
Initiatives should focus on research scope, de-identification levels, review committee processes, policy alignment, and handling datasets without existing sharing systems.