Robotics is quickly becoming the new gold standard for minimally invasive colorectal surgery, with recent studies showing shorter postoperative courses , decreasing operative times, and improved conversion rates when compared to laparoscopy [1–5]. Operative times currently appear to be longer with robotic colectomy, in part because most published studies are retrospective and typically clump actual operative time with docking and repositioning the robot. While prospective databases like ROLARR (NCT01736072) mature, it is important to note that early meta-analysis and single surgeon analysis have shown that operative times approach that of laparoscopy as surgeon and staff experience grow [5, 6]. The benefits of robotic colorectal surgery are especially apparent with rectal cancer and low pelvic dissections, as operative times and rates of conversion to laparotomy are superior compared to laparoscopy [7, 8].

Minimally invasive colorectal surgical operative times and conversion rates are important to consider, as studies have shown benefits versus laparotomy but diminishing returns in patient outcomes as operative time surpasses 180 min [9, 10]. In MIS and laparoscopy in particular, longer operative times are usually a result of five factors: excessive tumor fixity, anatomic uncertainty, tumor clearance, patient obesity, and surgeon experience [11, 12]. Recently published data from Canada citing approximately 500 robotic and 8400 laparoscopic colectomies demonstrated no difference in mean operative time (190 versus 187 min, respectively) and a significantly lower incidence of conversion to laparotomy in the robotic group (9.5 % versus 13.7 %, respectively) [13].

With more than 30 % of the US population over the age of 20 having body mass index (BMI) values above 30 [14], the effects of BMI values on surgical outcomes have taken center stage. The visceral adiposity and larger abdominal wall can confound fine movements and make intraperitoneal manipulation of organs cumbersome. Multiple advanced laparoscopy studies have demonstrated direct links to complications related to obesity, including superficial and deep infections, longer operative times, and incisional hernia formation [15–17], as well as conversion from MIS to laparotomy [9, 18, 19]. Regarding infectious and hernia-related complications, the short-term outcomes of robotic colorectal surgery are similar to laparoscopy as BMI values increase [9, 18]. Other datasets suggest that while BMI values greater than 30 increase average operative times by up to 30 min, conversion rate, blood loss, leak rate, and overall complication rate are unchanged [13, 20, 21], supporting the claim that robotics are unaffected by BMI values. Resilience of robotic surgery outcomes to the effects of elevated BMI values is likely due in part to the fact that the robot mitigates the fulcrum effect of the trocar and the abdominal wall, stabilizing the instrument and camera and allowing for fine motion with minimal effort.

Generalizations can be made supposing that advanced tumors, prior radiation, and pathology resulting from inflammatory conditions like diverticulitis and inflammatory bowel disease lend themselves to increased anatomic fixity [22, 23] and increase the risk of unplanned conversion [13]. In fact, colon cancer (OR 1.810), Crohn’s (OR 2.194), and diverticular (OR 1.980) disease were shown to be independent risk factors for unplanned conversion. Robotic surgery, however, was found to be protective against conversion versus laparoscopy (OR 0.713) for the aforementioned pathologic processes [13]. Interestingly, ulcerative colitis was not found to be an independent risk factor for unplanned conversion. Other studies have also shown viability of robotic completion proctectomy and ileal pouch anal anastomosis for ulcerative colitis [24, 25] with improved conversion rates but longer operative times when compared to laparoscopy [26].

As in the early days of laparoscopy, there is a learning curve associated with robotics. Early studies investigated single surgeon progression using cumulative sum analysis for the experienced colorectal laparoscopist and discovered three distinct phases: a learning phase when docking the robot is mastered, a plateau phase when the surgeon consolidates his/her skills and confidence, and an mastery phase when the surgeon expands case variety [27, 28]. Multiple smaller studies report that approximately 25 cases were required to reach the “mastery” phase. However, a significantly larger Korean single surgeon study concurred with the general findings of three stages of learning robotics, but cited initial phases of 35 cases, plateau phases of 93 cases, and mastery phases of 69 cases. It is important to note that the demographics of the later phases of the Korean study included lower rectal lesions and neoadjuvant chemoradiation, while the first phase was comprised of a statistically higher number of tumors more than 8 cm from the anal verge without chemoradiation [29]. Most importantly, none of the studies showed a significant increase in intraoperative conversion or complication rate as the surgeon progressed through phases one and two, suggesting that learning robotic colorectal surgery does not place the patient at undue risk.