From Evaluation to Implementation: A Delphi Consensus Framework with Domain-Weighted Decision Models for Robotic Surgery Adoption
Kenneth Chen, Tsi Yu Poon, Wai Chye Cheong, May Anne Cheong, Yvonne Ying Ru Ng, Alvin Yuanming Lee, Ye Xin Koh, Meihuan Chang, Kenny Wei-Tsen Loh, Christine Gaik Yie Neoh, Shirlena Tieu Kwee Wong, Pin Sun Chang, Shu Hui Yeang, An Lui Wang, Kelvin Ghim Chuan Tan, Wai Ching Lee, Jeremy Chon Wai Aw, Carol Siow Yen Ang, Emile John Kwong Wei Tan, Brian Kim Poh Goh, Song Tar Toh, John Shyi Peng Yuen, Henry Sun Sien HoBackground: Adoption of surgical robotic systems is accelerating globally, driven by advances in clinical capability, ergonomics, and workflow efficiency. However, robotic surgery programs introduce complex organizational challenges related to patient safety, workforce capability, infrastructure readiness, governance, vendor dependency, procurement, and long-term sustainability. Hospitals often lack structured, leadership-oriented frameworks to support systematic, context-appropriate evaluation, adoption, and governance of these technologies. Objective: To develop a multidisciplinary, consensus-based framework to support leadership-level evaluation, organizational readiness assessment, adoption, and governance of surgical robotic systems. Methods: A two-round modified Delphi study was conducted at Singapore General Hospital involving eleven stakeholder groups spanning clinical, perioperative, technical, operational, governance, and executive domains. Department-level consensus responses were generated. In Round 1, stakeholders completed role-specific questionnaires comprising Likert-scale items and open-ended questions. Items rated as low importance were excluded, while items of moderate importance were refined through thematic analysis. In Round 2, refined and newly generated items were re-evaluated. Items achieving ≥70% agreement for high importance within each stakeholder group were retained. Results: A total of 417 consensus-derived items were identified and organized into nine thematic domains encompassing patient safety and risk management, technical capability and surgical performance, workflow integration, training and credentialing, governance and sustainability, vendor support, infrastructure, logistics, and operational readiness. The framework was operationalized through category-specific interpretive scoring rubrics and three domain-weighted decision models reflecting clinician, safety, and procurement perspectives. Conclusions: This study presents a leadership-oriented, multi-stakeholder framework to support the risk-aware evaluation, adoption, implementation, and governance of surgical robotic systems. By integrating considerations across institutional readiness, comparative robotic platform assessment, and program governance, the framework provides a structured approach to decision-making throughout the robotic surgery lifecycle. While it may serve as a useful starting point for institutions seeking to establish or expand robotic surgery programs, the framework was developed and evaluated within a single academic tertiary healthcare institution. Further validation across diverse healthcare settings, including community hospitals, non-academic institutions, specialty centers, and resource-constrained environments, is required before broader adoption can be recommended.