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

Area of Science:

• Surgical Oncology
• Minimally Invasive Surgery
• Medical Education

Background:

• Robotic colorectal resection is increasingly popular, but data on surgeon competency and program development are limited.
• Understanding the learning curve is crucial for establishing efficient and safe robotic surgery programs.

Purpose of the Study:

• To determine the number of cases required to establish a robotic colorectal cancer surgery program.
• To analyze the learning curve for individual surgeons and the institution.

Main Methods:

• Retrospective review of 418 robotic-assisted colorectal adenocarcinoma resections.
• Cumulative summation (CUSUM) technique to construct learning curves and define learning phases.
• Analysis of perioperative variables across learning phases.

Main Results:

• The initial learning phase for the institution required approximately 74 cases.
• Later adopting surgeons required 23-30 cases for their initial learning phase.
• Operative times decreased significantly for all surgeons, and complication rates decreased for later adopters.

Conclusions:

• Establishing a robotic colorectal cancer surgery program requires around 75 cases.
• Individual surgeons require fewer cases (25-30) to achieve proficiency once a program is established.
• The institutional learning curve is a distinct entity that extends beyond individual surgeon learning.