Digital twin

Health Management Glossary

Digital Health and AI

Definition. A digital twin is a dynamic virtual model of a physical object, process or person that is updated with real data and used to simulate, monitor and optimise the real counterpart.

Explanation

The concept matured in industry, where digital twins support design and operations (Tao et al., 2018). In health care, proposals include patient-level twins for early disease detection, such as Parkinson disease (Abirami & Karthikeyan, 2023), and system-level twins that use discrete-event simulation to optimise critical care workflows (Appuhamilage et al., 2025).

Health digital twins raise questions about data integration, validation, privacy and the gap between technical promise and organisational value. They are best treated as decision-support tools whose assumptions must be made explicit.

Related concepts

Discrete-event simulation Artificial intelligence (AI) Patient flow Cybersecurity Data governance

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References

Abirami, L., & Karthikeyan, J. (2023). Digital Twin-Based Healthcare System (DTHS) for Earlier Parkinson Disease Identification. IEEE Access, 11. https://doi.org/10.1109/ACCESS.2023.3312278

Appuhamilage, G. D. K. K., Hussain, M., Zaman, M., & Khan, W. A. (2025). A health digital twin framework for discrete event simulation based optimised critical care workflows. NPJ Digital Medicine, 8 (1), Article 376. https://doi.org/10.1038/s41746-025-01738-4

Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2018). Digital Twin in Industry: State-of-the-Art. IEEE Transactions on Industrial Informatics, 14 (4), 1722–1731. https://doi.org/10.1109/TII.2018.2873186

Cite this entry: Kurutkan, M. N. (2026). Digital twin. In The Health Topics glossary. https://healthtopic.org/glossary/digital-twin/

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