Eight Years’ Experience in Robotic Surgery: What Have We Learned?

Shireesh Saurabh, MD, Andres Castellanos, MD, Noah Saad, Wu S Andrew

Drexel University College of Medicine

Background: Robotic surgery is evolving into an important surgical approach in various fields of surgery. Its main advantage is that it can overcome deficiencies of conventional laparoscopic surgery. We aimed to evaluate our experience in robotic surgery over 8 years duration and to determine institutional learning curve among different surgical specialties.

Methods: A total of 817 robotic cases performed at our institution from 2004 – 2011 were included in our study. The cases were divided into 3 groups: General surgery, Urology, and Gynecology. Routinely collected intra – operative parameters like Docking time (DT), Surgeon console time (SCT) and Total robot time (TRT) were retrospectively analyzed. Most commonly performed surgeries in each group were further analyzed to identify a learning curve.

Results: Our study shows a statistically significant decline in docking time, surgeon console time, and total robot time in Robotic Nissen Fundoplication and Robotic Prostatectomy groups. There is no statistically significant decline in intra – operative times in the Robotic Assisted Abdominal Hysterectomy group. Surgeon console time learning curve for Robotic Nissen Fundoplication stabilizes at approximately 67 minutes after 20 cases while the Robotic Prostatectomy learning curve shows the steepest decline up to 40 cases and there after continues to gradually trend down as surgeons gain experience with time.

Conclusion: Robotic surgery is most commonly being performed by the urologists at our institution. As surgeons and hospital staff gain experience with time and case volume, there is an obvious decline in docking time, surgeon console time, and total robot time, which is comparable to outcomes from other published series. Frequent changing of hospital staff involved in robotic surgery, as noticed in the gynecology group, can prolong the institutional learning curve.

Session: Poster Presentation

Program Number: P632

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