We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Developing a robotic colorectal cancer surgery program: understanding institutional and individual learning curves.
- Authors
Guend, Hamza; Widmar, Maria; Patel, Sunil; Nash, Garrett; Paty, Philip; Guillem, José; Temple, Larissa; Garcia-Aguilar, Julio; Weiser, Martin; Nash, Garrett M; Paty, Philip B; Guillem, José G; Temple, Larissa K; Weiser, Martin R
- Abstract
<bold>Importance: </bold>Robotic colorectal resection continues to gain in popularity. However, limited data are available regarding how surgeons gain competency and institutions develop programs.<bold>Objective: </bold>To determine the number of cases required for establishing a robotic colorectal cancer surgery program.<bold>Design: </bold>Retrospective review.<bold>Setting: </bold>Cancer center.<bold>Patients: </bold>We reviewed 418 robotic-assisted resections for colorectal adenocarcinoma from January 1, 2009, to December 31, 2014, by surgeons at a single institution. The individual surgeon's and institutional learning curve were examined. The earliest adopter, Surgeon 1, had the highest volume. Surgeons 2-4 were later adopters. Surgeon 5 joined the group with robotic experience.<bold>Interventions: </bold>A cumulative summation technique (CUSUM) was used to construct learning curves and define the number of cases required for the initial learning phase. Perioperative variables were analyzed across learning phases.<bold>Main Outcome Measure: </bold>Case numbers for each stage of the learning curve.<bold>Results: </bold>The earliest adopter, Surgeon 1, performed 203 cases. CUSUM analysis of surgeons' experience defined three learning phases, the first requiring 74 cases. Later adopters required 23-30 cases for their initial learning phase. For Surgeon 1, operative time decreased from 250 to 213.6 min from phase 1-3 (P = 0.008), with no significant changes in intraoperative complication or leak rate. For Surgeons 2-4, operative time decreased from 418 to 361.9 min across the two phases (P = 0.004). Their intraoperative complication rate decreased from 7.8 to 0 % (P = 0.03); the leak rate was not significantly different (9.1 vs. 1.5 %, P = 0.07), though it may be underpowered given the small number of events.<bold>Conclusions: </bold>Our data suggest that establishing a robotic colorectal cancer surgery program requires approximately 75 cases. Once a program is well established, the learning curve is shorter and surgeons require fewer cases (25-30) to reach proficiency. These data suggest that the institutional learning curve extends beyond a single surgeon's learning experience.
- Subjects
PROCTOLOGY; LAPAROSCOPY; RECTAL cancer; COLON cancer treatment; MEDICAL robotics; SURGERY
- Publication
Surgical Endoscopy & Other Interventional Techniques, 2017, Vol 31, Issue 7, p2820
- ISSN
1866-6817
- Publication type
journal article
- DOI
10.1007/s00464-016-5292-0