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Developing a robotic colorectal cancer surgery program: understanding institutional and individual learning curves

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TLDR
The data suggest that establishing a robotic colorectal cancer surgery program requires approximately 75 cases, and suggest that the institutional learning curve extends beyond a single surgeon’s learning experience.
Abstract
Robotic colorectal resection continues to gain in popularity. However, limited data are available regarding how surgeons gain competency and institutions develop programs. To determine the number of cases required for establishing a robotic colorectal cancer surgery program. Retrospective review. Cancer center. 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. 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. Case numbers for each stage of the learning curve. 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. 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.

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Citations
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Systematic review of learning curves in robot‐assisted surgery

TL;DR: A systematic review was conducted to identify the available evidence investigating surgeon learning curves in robot‐assisted surgery and concluded that there is insufficient evidence to recommend a specific curve for each procedure.
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A Multicenter Matched Comparison of Transanal and Robotic Total Mesorectal Excision for Mid and Low-rectal Adenocarcinoma.

TL;DR: High-quality TME for patients with rectal adenocarcinoma of the mid and low rectum can be equally achieved by transanal or robotic approaches in skilled hands, but attention should be paid to the distal margin.

Is the learning curve of robotic low anterior resection shorter than laparoscopic low anterior resection for rectal cancer?: a comparative analysis of clinicopathologic outcomes between robotic and laparoscopic surgeries.

TL;DR: In this article, the learning curve of robotic low anterior resection (LAR) with laparoscopic LAR for rectal cancer was compared retrospectively, and the cumulative sum (CUSUM) was used to evaluate the learning curves.
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A systematic review of the learning curve in robotic surgery: range and heterogeneity

TL;DR: The outcomes reported in studies assessing LC in robotic surgery are extremely heterogeneous and are most often technical indicators of surgical performance rather than clinical and patient-centered outcomes.
Journal ArticleDOI

Learning curve in robotic colorectal surgery

TL;DR: There was a downward trend in total operative time and postoperative complication rates, and these findings may help guide the stepwise training and credentialing of new robotic surgeons.
References
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Journal ArticleDOI

Robotic Surgery: A Current Perspective

TL;DR: Robotic surgery is still in its infancy and its niche has not yet been well defined, so its current practical uses are mostly confined to smaller surgical procedures.
Journal ArticleDOI

Telerobotic-assisted laparoscopic right and sigmoid colectomies for benign disease.

TL;DR: The first two reported cases of telerobotic-assisted laparoscopic colectomy are presented and it is found that the Da Vinci system adequately replaced the camera holder and the three-dimensional virtual operative field helped to maintain the surgeon's orientation during the operation.
Journal ArticleDOI

Robotic versus laparoscopic low anterior resection of rectal cancer: short-term outcome of a prospective comparative study.

TL;DR: R-LAR was performed safely and effectively, using the da Vinci® Surgical System, and the use of the system resulted in acceptable perioperative outcomes compared to L-L AR.
Journal ArticleDOI

Learning curve for robotic-assisted laparoscopic colorectal surgery

TL;DR: The three phases identified with CUSUM analysis of surgeon console time represented characteristic stages of the learning curve for robotic colorectal procedures, suggesting that the learning phase was achieved after 15 to 25 cases.
Journal ArticleDOI

Robotic-assisted laparoscopic low anterior resection with total mesorectal excision for rectal cancer

TL;DR: Robotic-assisted low anterior resection with total mesorectal excision for rectal cancer is feasible in experienced hands and may facilitate minimally invasive radical rectal surgery.
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