Digital twins in healthcare enable data-driven decision-making, enhancing operational efficiency through simulation and predictive analytics support.
Authors
Saroj Koul, Professor, Jindal Global Business School, O.P. Jindal Global University, Sonipat, Haryana, India
Vinaytosh Mishra, Gulf Medical University, Ajman, United Arab Emeritus
Ivan W. Taylor, Policy Dynamics Inc., Ontario, Canada
Summary
“Digital twins (DTs)” provide significant potential for data-driven decision-making in the healthcare sector. This chapter provides background, an implementation approach, advantages, challenges, and ethical issues related to using DTs in healthcare, focusing on operational efficiency. Through the case study approach and adoption of system dynamics modelling (SDM) for diabetes management, we provide an implementation framework for implementing DTs in healthcare and illustrate the learning from secondary and primary research. The approach demonstrates that the SDM is a valuable tool for simulation in healthcare settings where the policy environment is vaguely defined. The study concludes that DTs have immense potential to achieve operational efficiencies in healthcare. Future studies can evaluate the effectiveness of the six-step approach proposed to enhance hospital operations efficiency.
Published in: Blockchain and Digital Twin for Smart Hospitals
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