Robotic Surgery and Outcomes: The Moderating Role of Surgeon Skill Level and Clinical Experience

Abstract

Robotic surgery has emerged as a major advancement in modern healthcare, enabling minimally invasive procedures with enhanced precision, improved visualization, and reduced patient recovery time. Despite its technological sophistication, the clinical outcomes of robotic surgery vary significantly across hospitals and surgeons. This study examines the relationship between robotic surgery adoption and surgical outcomes, with a focus on the moderating roles of surgeon skill level and clinical experience. Drawing on Socio Technical Systems Theory, Skill Acquisition Theory, and Learning Curve Theory, the study proposes that robotic surgery improves surgical outcomes, while surgeon skill level and clinical experience strengthen this relationship by enhancing precision, decision making, and procedural efficiency. A quantitative cross sectional research design is proposed involving surgeons, surgical residents, operating room staff, and hospital administrators. Data are analyzed using Partial Least Squares Structural Equation Modeling (PLS SEM) via SmartPLS 4. The findings indicate that robotic surgery significantly improves surgical outcomes, while both surgeon skill level and clinical experience significantly moderate this relationship. The results suggest that highly skilled and experienced surgeons achieve superior outcomes when using robotic surgical systems compared to less experienced operators. This study contributes to surgical informatics and healthcare technology literature by identifying human performance boundaries in robotic assisted surgery. The findings offer practical implications for hospital administrators, surgical training programs, and policymakers aiming to optimize robotic surgery outcomes.