Learning Curves and Proficiency Milestones in Robotic Ventral Hernia Repair: A Systematic Review by Surgical Technique

Aim: Robotic ventral hernia repair (VHR) has enabled minimally invasive management of complex abdominal wall hernias. As robotic procedures involve distinct technical demands and require progressive skill acquisition, understanding learning curves (LCs) is essential to define proficiency thresholds, optimize surgical training, and ensure safe implementation of these techniques. This systematic review compared LCs in robotic VHR across surgical techniques. Methods: A systematic review was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. A comprehensive search of major medical databases (PubMed/MEDLINE, EMBASE, Web of Science, Lilacs, and the Cochrane Library) was performed through August 2025, including cohort studies on adult patients undergoing elective robotic VHR. Results: Seven retrospective cohort studies were included, comprising six single-surgeon series: one robotic intraperitoneal underlay mesh (rIPUM), one robotic transversus abdominis release (rTAR), one robotic transabdominal preperitoneal (rTAPP), three robotic enhanced-view totally extraperitoneal (r-eTEP), and one population-based analysis including 12,609 cases. The single-surgeon series predominantly involved patients with class I obesity (mean body mass index range: 31.0–33.0 kg/m 2 ). LC assessment was heterogeneous, employing cumulative sum (CUSUM), risk-adjusted CUSUM (RA-CUSUM), chronological case grouping, and multivariable regression modeling. Across single-surgeon studies, operative efficiency improved earlier than complication-adjusted or technical quality outcomes. Operative-time (OT) proficiency thresholds were reported at 26 cases for rIPUM, 29–38 for r-eTEP, 46 for rTAPP, and 49 cases for rTAR. However, stabilization of complication-adjusted performance required higher volumes, ranging from 51 to 64 cases. Prior experience substantially shortened the LC, reducing OT proficiency for r-eTEP to just 8 cases. In contrast, population-level analysis suggested that 16–19 robotic cases were required to achieve recurrence-related reoperation rates comparable to open or laparoscopic repair. Conclusion: LCs in robotic VHR follow a two-phase, technique-dependent pattern. While operative efficiency is achieved earlier, optimal patient outcomes require higher case volumes.