[Re-identification potential of structured health data].

Area of Science:

• Health Informatics
• Data Privacy
• Biomedical Research

Context:

• Broad access to health data fuels scientific advancement.
• Health data contains sensitive information requiring robust protection.
• Re-identification of anonymized health data poses significant privacy risks.

Purpose:

• To analyze the re-identification potential of health data.
• To discuss factors influencing re-identification and international privacy standards.
• To present mitigation strategies for safeguarding sensitive health information.

Summary:

• Defines terms and explores factors affecting health data re-identification.
• Reviews international privacy standards and the impact of background knowledge.
• Proposes mitigation strategies using the Five Safes concept and synthetic data generation.

Impact:

• Highlights the underestimation of re-identification risks in practice.
• Provides actionable strategies for data protection in health research.
• Informs future developments like the Health Data Lab for enhanced data security.