Data privacy and protection in AI-driven healthcare

Area of Science:

• Health Informatics
• Data Science
• Bioethics

Background:

• The definition of health data has expanded to include genomic data, medical records, and converted non-health data, forming a biomedical big data (BD) ecosystem.
• Biomedical big data is pivotal for artificial intelligence (AI) advancement in health research, often likened to 'new oil'.
• The healthcare sector faces a significant rise in data breaches, highlighting vulnerabilities in current data protection measures.

Purpose of the Study:

• To address the growing challenges in health data privacy.
• To emphasize the need for translating ethical and legal guidelines into practical data protection measures.
• To explore the strengthening of systems and ethico-legal frameworks for data processing in South Africa (SA).

Main Methods:

• Review of the evolving landscape of health data and its sources.
• Analysis of the implications of biomedical big data for AI and health research.
• Examination of the rise in healthcare data breaches.
• Assessment of the ethico-legal framework governing data processing in SA.

Main Results:

• Biomedical big data presents unprecedented opportunities for AI-driven health research.
• Data breaches are increasing, particularly within the healthcare sector.
• Existing ethico-legal frameworks require strengthening to address data misuse effectively.
• There is an urgent need for context-specific governance and adaptable infrastructure in SA.

Conclusions:

• Strengthening the ethico-legal framework is paramount for safeguarding health data privacy.
• Ethically sound practices, adaptable infrastructure, and robust, context-specific governance are crucial for SA.
• Proactive measures are needed to prevent data misuse and mitigate the impact of breaches in the era of big data.