REAL-WORLD ADOPTION, BARRIERS, ARTIFICIAL INTELLIGENCE INTEGRATION, AND FUTURE READINESS OF ROBOTIC-ASSISTED SURGERY (RAS) IN CHINA
Author(s)
Baldwin Y. Chia, BSc;
Holden Data, Market Research, Shanghai, China
Holden Data, Market Research, Shanghai, China
OBJECTIVES: Robotic-assisted surgery (RAS) was first introduced into China in the early 2000s, and did not gain traction until after 2015. Since then, RAS and interest in AI have had a turning point. Led by imported RAS systems, primarily western technologies, China has catapulted development of such systems. As real-world evidence comparing imported and domestic RAS platforms remain limited, this study explored surgeon perspectives on current adoption, platform maturity and expectations for AI integration in China.
METHODS: Semi-structured in-depth interviews were conducted with RAS surgeons of varying specialisations, city development tiers, and seniority in tertiary hospitals in China. The surgeons had direct experience with imported and domestic RAS platforms. The interviews examined platform selection, case complexity, operational barriers, training requirements, institutional access models, and perceptions of AI-enabled features. Analysis incorporated demographic contexts.
RESULTS: Surgeons reported high acceptance and extremely favourable perception of RAS across specialities, with imported platforms being perceived as more mature and stable - highly important especially for the more complex, low tolerance procedures. Domestic platforms while improving rapidly and generally more feature rich, had limitations in responsiveness and reliability. Adoption was driven primarily by affordability, economics, and availability and less by clinical preference. Some AI features such as image recognition and surgeon guidance are widely accepted and in use and is expected to be further enhanced to cover end-to-end integration to optimise outcomes and minimise surgical risk. High demand for adoption and surgeon training for lower tiered cities.
CONCLUSIONS: In China, imported RAS platforms are still preferred currently but are very likely to see increased adoption from domestic Chinese manufacturers due to access and scalability. AI is seen as an enabler of efficiency rather than autonomy. These findings highlight the importance of accessibility and scalability as well as surgeon training infrastructure to address adoption in lower tiered cities in China.
METHODS: Semi-structured in-depth interviews were conducted with RAS surgeons of varying specialisations, city development tiers, and seniority in tertiary hospitals in China. The surgeons had direct experience with imported and domestic RAS platforms. The interviews examined platform selection, case complexity, operational barriers, training requirements, institutional access models, and perceptions of AI-enabled features. Analysis incorporated demographic contexts.
RESULTS: Surgeons reported high acceptance and extremely favourable perception of RAS across specialities, with imported platforms being perceived as more mature and stable - highly important especially for the more complex, low tolerance procedures. Domestic platforms while improving rapidly and generally more feature rich, had limitations in responsiveness and reliability. Adoption was driven primarily by affordability, economics, and availability and less by clinical preference. Some AI features such as image recognition and surgeon guidance are widely accepted and in use and is expected to be further enhanced to cover end-to-end integration to optimise outcomes and minimise surgical risk. High demand for adoption and surgeon training for lower tiered cities.
CONCLUSIONS: In China, imported RAS platforms are still preferred currently but are very likely to see increased adoption from domestic Chinese manufacturers due to access and scalability. AI is seen as an enabler of efficiency rather than autonomy. These findings highlight the importance of accessibility and scalability as well as surgeon training infrastructure to address adoption in lower tiered cities in China.
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
MT36
Topic
Medical Technologies
Disease
SDC: Cardiovascular Disorders (including MI, Stroke, Circulatory), SDC: Urinary/Kidney Disorders, STA: Surgery