Abstract / Summary
Background: Robust evidence linking individual surgeon technical performance to patient outcomes in complex minimally invasive surgery remains scarce. Crowd-sourced video assessment offers a scalable alternative to expert review, but its clinical relevance in complex oncologic procedures such as robot-assisted minimally invasive esophagectomy (RAMIE) is unestablished. Methods: In this exploratory study, video recordings of 60 consecutive RAMIE procedures performed by 7 surgeons (2018-2023) were segmented into five representative surgical steps and rated by 93 blinded crowd-raters per segment using a modified GEARS instrument. Tertiles were used to compare top-performing operations and steps against the remaining two terciles for overall and step-specific performance, and associations with perioperative outcomes were analyzed. Results: Top-tercile overall performance was associated with significantly shorter operative time (abdominal, thoracic, and total) and less intraoperative blood loss (all p<0.05), without differences in postoperative outcomes. In exploratory step-specific analyses, top-tertile performance during infracarinal lymphadenectomy was associated with significantly fewer surgical complications (30.0% vs 60.0%; p=0.028), fewer severe surgical complications (25.0% vs 52.5%; p=0.043), and higher lymph node yield (22.8 vs 18.9; p=0.037), while the purse-string suture step showed the broadest operative-time benefit. These step-specific findings are hypothesis-generating and were not adjusted for multiple testing. Conclusion: Crowd-sourced video assessment enables scalable, step-specific evaluation of surgical performance in RAMIE associated with intraoperative blood loss and operative time. Exploratory analyses suggest that the relationship between technical performance and clinical outcomes might be step-specific, with infracarinal lymphadenectomy emerging as risky step linked to postoperative morbidity. These findings support further investigation of individualized performance assessment for quality improvement and risk stratification.