Securing Reproducibility and Accountability in Distributed Healthcare Analytics: A Framework Based on Blockchain and...

Area of Science:

• Biomedical Informatics
• Data Security
• Blockchain Technology

Background:

• Clinical study data requires secure storage for reliability and accountability.
• Current methods may not adequately prevent malicious misuse or verify data ownership.
• Ensuring data integrity and researcher accountability is crucial for scientific trust.

Purpose of the Study:

• To present a secure framework for storing clinical study metadata and results.
• To establish a mechanism for accountability for data owners and researchers.
• To enhance the reliability and verifiability of scientific research.

Main Methods:

• Development of a modular framework utilizing blockchain technology.
• Integration of cryptographic methods for secure data storage.
• Testing the framework within a privacy-preserving distributed analytics infrastructure.

Main Results:

• The framework successfully stores study results and metadata securely.
• Proof of accountability for data owners and researchers is established.
• The system was validated within a distributed analytics environment.

Conclusions:

• The proposed blockchain-based framework enhances the security and accountability of clinical research data.
• It provides a reliable method for verifying research results and methods.
• This approach fosters greater trust in the scientific community and protects researcher contributions.