Tokenization techniques for privacy-preserving healthcare data: tokenization nuts and bolts.

Area of Science:

• Health Informatics
• Data Privacy
• Pharmacovigilance

Background:

• Healthcare data integration, including clinical records and social determinants of health (SDOH), necessitates robust patient data protection.
• Tokenization is essential for safeguarding sensitive information while improving data quality and analysis in research.
• Ensuring patient privacy is paramount in clinical research, pharmacovigilance, and drug safety monitoring.

Purpose of the Study:

• To highlight the critical role of tokenization in securing patient data within pharmacovigilance activities.
• To demonstrate how tokenization enhances the integration of diverse data sources for improved research rigor.
• To underscore tokenization's value in generating regulatory-grade evidence for pharmacovigilance.

Main Methods:

• Review of tokenization's application in pharmacovigilance, including safety monitoring and risk assessment.
• Analysis of referential tokenization's effectiveness in linking electronic health records (EHRs) and claims data.
• Examination of global applications and alignment with international data privacy frameworks.

Main Results:

• Tokenization is a foundational privacy-preserving technology for pharmacovigilance.
• Referential tokenization achieved over 99% linkage precision in a clinical trial, securely connecting EHRs and claims data.
• Tokenization supports the generation of regulatory-grade evidence for multinational research.

Conclusions:

• Tokenization is indispensable for protecting patient privacy in pharmacovigilance and clinical research.
• Effective tokenization allows for deeper insights into clinical and pharmacological research while maintaining data security.
• Tokenization facilitates compliance with evolving international data privacy regulations, potentially reducing consent requirements.