What are the ethical implications of creating a digital twin for every patient?

Creating a digital twin for every patient—defined as a virtual representation of a physical asset enabled through data and simulators for real-time prediction, optimization, monitoring, controlling, and improved decision-making ^[1]—brings transformative potential to personalized healthcare ^[2], but it also raises a myriad of complex ethical issues across every phase of data processing ^[3].

Key Ethical Dilemmas and Risks

• Privacy and Data Processing Risks: Digital twins rely on continuous high-dimensional data collection from sensors and artificial intelligence pipelines ^[4][5]. Mapping studies examining personalized health care services indicate that ethical risks emerge systematically as raw health data is transformed into predictive insights, requiring proactive identification during the development stage ^[6].
• Informed Consent Challenges: Traditional paper-based informed consent for medical procedures faces significant limitations such as low comprehensibility, lack of customization, and constrained time for patient discussions ^[7]. While digitalizing the consent process through interactive technologies offers potential to enhance patient understanding of clinical procedures, risks, benefits, and alternatives, current evidence indicates that artificial intelligence tools are not yet suitable for autonomous use without medical oversight ^[8].
• Systematic Risk Analysis: Because personalized health care digital twins integrate artificial intelligence and information technologies, addressing operational problems and associated ethical risks requires structured conceptual frameworks like process-oriented ethical mapping rather than ad-hoc evaluations ^[9].

Would you also like to know more about the specific operational problems identified in digital twin healthcare mapping?