Abstract

Robotic surgery has experienced exponential growth in the past decade. Few studies have evaluated the impact of robotics within minimally invasive surgery (MIS) fellowship training programs. The purpose of our study was to examine and characterize recent trends in robotic surgery within MIS fellowship training programs. De-identified case log data from the Fellowship Council from 2010 to 2021 were evaluated. Percentage of operations performed with robot assistance over time was assessed and compared to the laparoscopic and open experience. Case logs were further stratified by operative category (e.g., bariatric, hernia, foregut), and robotic experience over time was evaluated for each category. Programs were stratified by percent robot use and the experience over time within each quartile was evaluated. MIS fellowship training programs with a robotic platform increased from 45.1% (51/113) to 90.4% (123/136) over the study period. The percentage of robotic cases increased from 2.0% (1127/56,033) to 23.2% (16,139/69,496) while laparoscopic cases decreased from 80.2% (44,954/56,033) to 65.3% (45,356/69,496). Hernia and colorectal case categories had the largest increase in robot usage [hernia: 0.7% (62/8614) to 38.4% (4661/12,135); colorectal 4.2% (116/2747) to 31.8% (666/2094)]. When stratified by percentage of robot utilization, current (2020-2021) programs in the > 95th percentile performed 21.8% (3523/16,139) of robotic operations and programs in the > 50th percentile performed 90.0% (14,533/16,139) of all robotic cases. The median number of robotic cases performed per MIS fellow significantly increased from 2010 to 2021 [0 (0-6) to 72.5 (17.8-171.5), p < 0.01]. Robotic use in MIS fellowship training programs has grown substantially in the past decade, but the laparoscopic and open experience remains robust. There remains an imbalance with the top 50% of busiest robotic programs performing over 90% of robot trainee cases. The experience in MIS programs varies widely and trainees should examine program case logs closely to confirm parallel interests.

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