The Future of Digital Twins in Personalized Healthcare: A Systematic Review of Applications, Challenges, and Opportunities in Nursing and Radiology

Abstract

Background:
Digital twins virtual representations of physical entities—are rapidly emerging as transformative tools in healthcare, enabling real-time monitoring, simulation, and predictive analysis. In nursing and radiology, these technologies offer immense potential for personalized care, optimizing patient outcomes, and improving clinical decision-making.

Aim:
This systematic review aims to explore the future of digital twins in personalized healthcare, specifically focusing on their applications, challenges, and opportunities within nursing and radiology. The review examines how digital twins can enhance patient care and professional practice across these two critical healthcare domains.

Methods:
A comprehensive literature search was conducted across major databases, including PubMed, CINAHL, and Scopus, from inception to 2024. Studies were selected based on inclusion criteria that emphasized peer-reviewed articles discussing digital twin applications in healthcare, with a particular focus on nursing and radiology. Articles were critically appraised for quality and synthesized to identify key themes and insights related to personalized care.

Results:
The review identified 42 studies detailing diverse applications of digital twins in healthcare, ranging from personalized simulations for chronic disease management to real-time monitoring in critical care and radiological imaging. Key applications in nursing and radiology include predictive modeling for patient deterioration, enhancement of clinical workflows, precision medicine, and the integration of digital twins in diagnostic imaging. Challenges highlighted include data security, ethical concerns surrounding patient data, integration with existing healthcare infrastructure, and the need for specialized training for healthcare professionals. Despite these challenges, digital twins present substantial opportunities to enhance patient engagement, improve clinical decision-making, and foster the development of precision healthcare practices in both nursing and radiology.

Conclusion:
Digital twins represent a significant shift in the future of personalized healthcare delivery, with transformative implications for nursing and radiology. While challenges related to technology integration, ethics, and training remain, the potential for digital twins to enhance patient care, improve outcomes, and optimize professional practices is undeniable. Future research should address the barriers to implementation and investigate the long-term effects of digital twins on healthcare delivery, particularly in nursing and radiology.