Adoption of Metaverse in Healthcare Sector: An Empirical Analysis of its Enablers

The emergence of novel innovations has disrupted multiple service sectors, and healthcare is one such sector that has seen significant changes since the inception of Internet. The incorporation of information communication and technology (ICT) in the healthcare sector has been introduced previously;...

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Veröffentlicht in:IEEE transactions on engineering management 2024, Vol.71, p.8671-8685
Hauptverfasser: Shardeo, Vipulesh, Sarkar, Bishal Dey, Mir, Umar Bashir, Kaushik, Prerna
Format: Artikel
Sprache:eng
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Zusammenfassung:The emergence of novel innovations has disrupted multiple service sectors, and healthcare is one such sector that has seen significant changes since the inception of Internet. The incorporation of information communication and technology (ICT) in the healthcare sector has been introduced previously; however, the recent COVID-19 pandemic has exponentially accelerated the use of ICT in the healthcare sector and the demand for contactless health services. The use of technology for online consultation, robot-assisted surgeries, training, and education are some of the common use cases of tech-driven healthcare. Metaverse, the latest innovation that is the amalgam of multiple technologies, like artificial intelligence, augmented reality, virtual reality, and robotics, holds massive potential to deliver high-quality healthcare services (HS) to the masses, eliminate bottlenecks between healthcare providers and patients, and eliminate the need of in-person interaction for availing HS. This article aims to identify the factors that drive the adoption of metaverse in the healthcare industry. Following a mixed-method approach, the article combines secondary academic literature data with primary data from domain experts. A total of 13 enablers are identified for adopting metaverse in the healthcare domain. Subsequently, a hierarchical model reflecting upon the relationship among these factors based on their significance is developed using grey-ordinal priority approach and modified total interpretive structural modeling methodology. The proposed hierarchical model provides valuable insights into these factors' dependencies and relative importance which could empower healthcare organizations and policymakers in making informed decisions and strategic planning for an effective and efficient healthcare system.
ISSN:0018-9391
1558-0040
DOI:10.1109/TEM.2024.3400401