Digital Twin Technology for Personalized Healthcare: Transforming Preventive Care in Saudi Arabia

Digital Twin

The adoption of digital technologies is a catalyst for healthcare transformation. One promising technology being adopted within Saudi Arabia's healthcare system is the digital twin, a cutting-edge technology set to transform healthcare service delivery. A digital twin creates a dynamic, data-driven virtual model of a real-world entity — in this case, an individual patient — enabling continuous simulation, monitoring, and prediction of health outcomes.

As healthcare systems worldwide move toward precision medicine and preventive care, digital twins offer a powerful framework for understanding each patient's unique health trajectory. Rather than relying solely on population-level averages, digital twins enable clinicians and public health planners to tailor interventions at the individual level — a shift that aligns directly with Saudi Arabia's Vision 2030 and the Health Sector Transformation Program.

What did we do?

We introduced a digital twin solution focused on optimizing personalized healthcare. The digital twin is a virtual representation of an individual, built based on several of their health and demographic datapoints, implemented through the Sehhaty app. The digital twin simulates and monitors the individual's health status to provide insights for preventive measures and early intervention.

It provides multiple elements to optimize personalized healthcare, including health status visualization, body mass index assessment, biological age calculation, step tracking, vaccination guidance, and chronic disease risk prediction, with more innovative elements to be added in the future. By integrating real-time data from wearable devices and electronic health records, the digital twin continuously updates its model to reflect the patient's current health state.

What did we find?

The implementation of the digital twin within the Sehhaty app yielded several notable findings:

• Users who engaged with the digital twin features showed higher rates of adherence to preventive health recommendations, including vaccination schedules and chronic disease screenings.
• The biological age calculation proved to be a strong motivator for behavior change, with many users taking active steps to improve their lifestyle after seeing a gap between their biological and chronological ages.
• Chronic disease risk prediction models integrated into the digital twin identified at-risk individuals earlier than traditional screening methods, enabling timely interventions.
• Step tracking and physical activity monitoring contributed to measurable improvements in user engagement with their own health data, encouraging a proactive rather than reactive approach to wellness.

What does this mean?

The digital twin technology enhances both the model of care and value-based healthcare by facilitating personalized healthcare, optimizing risk prediction, and promoting preventive interventions, leading to improved patient experiences and better population health outcomes.

The integration of digital twin technology into Saudi Arabia's healthcare system represents a transformative leap toward realizing Vision 2030 and supporting the objectives of the Health Sector Transformation Program. By harnessing the power of digital twins, Saudi Arabia stands poised to revolutionize personalized healthcare, enabling a paradigm shift toward truly patient-centered, value-based care models.

Looking ahead, the digital twin framework is designed to be extensible. Future iterations will incorporate genomic data, mental health indicators, and environmental factors to build an even more comprehensive picture of individual health. As the underlying machine learning models are refined with larger datasets, the accuracy of risk predictions and the relevance of personalized recommendations will continue to improve — bringing Saudi Arabia closer to a truly predictive, preventive healthcare system.