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

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.