Is the Healthcare Industry Ready for Digital Twins? Examining the Opportunities and Challenges

Srinivasini Sasitharasarma, Noor H. S. Alani () and Zazli Lily Wisker
Additional contact information
Srinivasini Sasitharasarma: School of Computing, Eastern Institute of Technology, Napier 4142, New Zealand
Noor H. S. Alani: School of Computing, Eastern Institute of Technology, Napier 4142, New Zealand
Zazli Lily Wisker: School of Business, Eastern Institute of Technology, Napier 4142, New Zealand

Future Internet, 2025, vol. 17, issue 9, 1-29

Abstract: Recent advancements in the healthcare sector have reached a pivotal juncture, catalysed by the emergence of Digital Twin (DT) technologies. These innovations facilitate the development of virtual replicas that accurately simulate real-world conditions, thereby transforming traditional approaches to medical analysis, diagnostics, and treatment planning. Although widely successful in manufacturing, the adoption of Digital Twins in healthcare is relatively limited, particularly regarding their impact on clinical efficiency and patient outcomes. This study addresses three primary research questions: (1) How does Digital Twin technology improve individualised patient treatments and care quality? (2) What is the role of Digital Twin technology in accurately predicting patient responses to medical interventions? (3) What are the significant challenges of integrating Digital Twin technology into healthcare? Synthesising findings from 70 peer-reviewed articles, this review identifies critical knowledge gaps and provides practical recommendations for healthcare stakeholders to effectively navigate these challenges. This research proposes a conceptual framework illustrating the lifecycle of Digital Twin implementation in healthcare and outlines essential strategies for successful adoption. It emphasises the importance of robust infrastructure, clear regulatory guidance, and ethical practices to fully leverage the advantages of DT technologies. Nevertheless, this review acknowledges its limitations, including reliance on secondary data and the absence of empirical validation. Future research should focus on practical applications, diverse healthcare contexts, and broader stakeholder perspectives to comprehensively assess real-world impacts.

Keywords: Digital Twin; healthcare; personalised treatment; virtual models; technology advancements; generative AI; digital impacts; patient treatment outcomes and applications; IoT in healthcare (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1999-5903/17/9/386/pdf (application/pdf)
https://www.mdpi.com/1999-5903/17/9/386/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:17:y:2025:i:9:p:386-:d:1733858

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().