A future scenario

Ulma, a 52-year-old woman, an early adopter using lifestyle and environmental tracking devices, recently went through a knee replacement. Ulma’s health insurance offers the possibility to connect her lifestyle and well-being results she gathers daily to her healthcare Digital Twin (DT). The healthcare Digital Twin integrates her Electronic Health Record from the hospital with her medical history from her general practitioner.

Through her healthcare DT, Ulma receives personalized guidance for her recovery. She is provided with daily exercise plans and progress updates tailored to her situation. Her DT also draws on anonymized data from others who underwent the same surgery, offering comparative insights and predictions. Together with her general practitioner, Ulma reviews these insights and co-decides on the next steps in her recovery plan, taking into account her strengths and vulnerabilities.

This is a possible scenario on how patients could use healthcare DTs in conjunction with medical professionals.

Healthcare Digital Twins have recently been defined as “a virtual representation of a person which allows dynamic simulation of potential treatment strategy, monitoring and prediction of health trajectory, and early intervention and prevention, based on multi-scale modeling of multi-modal data such as clinical, genetic, molecular, environmental, and social factors, etc.”.

A key element in these systems is the integration of lifestyle data, gathered via mobile apps, wearables, and smart home (IoT) devices. Data on physical activity, sleep, diet, and stress levels contribute to a comprehensive health profile, allowing for personalized care. As Ulma’s case shows, such data can play a vital role in rehabilitation, prompting necessary lifestyle adjustments if needed.
 

The Expert Perspective: Opportunities and Challenges

From a medical perspective, healthcare DTs present interesting advantages. They offer prevention through forecasting (detecting illnesses earlier, revealing patterns and anomalies). Allowing for dynamic simulations for personalized treatment plans (e.g., adjusting medical doses based on historical and current data sources, including patient’s lifestyle components) that first can be simulated in a virtual world before applying them to the patient. Further, healthcare DTs allow for close monitoring of certain biomarkers in controlled lab environments (e.g., Intensive Care Units), also allowing for simulations of trial and error in a virtual environment before applying to a patient.

In general, healthcare DTs can shift focus from cure to preventive care.

However, challenges remain. The accuracy of healthcare DTs relies on high-quality, diverse, and continuously updated data. Integrating personal lifestyle and health data with clinical information requires robust infrastructure, it demands standardization (today data is stored in silos), and interoperability (there is no connection to create context, for example, a period of low physical activity could be misinterpreted if contextual data, such as illness, isn't linked).

Moreover, ethical and legal considerations surrounding data privacy and ownership must be addressed. Who owns the data? Which norms and values are embedded in these systems? Technologies developed in different geopolitical contexts reflect varying priorities., for example, there is a U.S. dominance in technology, questioning our European digital sovereignty, and 92% of our data is stored in the U.S., where data regulation (privacy and ownership) is different than in Europe. For example, abortion laws are different in the U.S. than in Europe.

Furthermore, who controls the DT? Who is at risk, and who benefits? Are data sets inclusive? Is there attention for minority groups such as gender, race, religion, and low-income groups?

These questions highlight the importance of transparency and trust in the development of healthcare DT systems, especially since it concerns a forecasted representation of an individual holding highly sensitive information and is considered a high-risk AI application.
 

The Patient Perspective: Autonomy and Engagement

We can envision healthcare DTs as health information platforms in a home setting. Healthcare DTs can be effective in a home setting; they can be designed with patient engagement and autonomy in mind. Rather than serving merely as passive data collectors, these systems should function as interactive health companions—guiding users toward healthier choices without overwhelming them with medical complexity. Here, the concept of ‘Reflective Care’ comes into play: a model in which patients can interact with their Digital Twin to receive insights tailored to their health makeup, preferences, and needs.

A major concern from a patient’s perspective is the potential for DTs to impose standardized health goals—like 10,000 steps a day or eight hours of sleep—without considering individual differences. Additionally, there is the risk of digital twins becoming a tool for surveillance rather than empowerment if not designed with clear user consent mechanisms and data protection safeguards.
 

To conclude

A successful implementation of healthcare DTs in a home setting requires a balanced approach. Medical professionals should serve as advisors and watchers, ensuring that these systems prioritize patient well-being rather than becoming tools for commercialization or external control. Regular check-ins between patients and healthcare providers can help maintain trust and provide human oversight where automated models fall short.

Ultimately, the evolution of healthcare DTs should move beyond purely technical advancements and medical efficiency. They must foster patient trust, respect autonomy, and promote holistic well-being, ensuring that digital health technologies serve as tools for empowerment rather than instruments of control.

As this field advances, integrating expert-driven innovation with patient-centered design will be key to achieving a truly reflective and effective digital healthcare ecosystem.