Barriers to Efficiency in Robotic Surgery: The Resident Effect

• Published in: The Journal of surgical research 2016-10, Vol.205 (2), p.296-304
• Main Authors: Jain, Monica, Fry, Brian T, Hess, Luke W, Anger, Jennifer T, Gewertz, Bruce L, Catchpole, Ken
• Format: Article
• Language: English
• Subjects: Efficiency, Organizational; Error; Human factors; Humans; Internship and Residency; Linear Models; Nephrectomy - education; Nephrectomy - methods; Nephrectomy - statistics & numerical data; Operative Time; Patient Care Team - organization & administration; Prospective Studies; Prostatectomy - education; Prostatectomy - methods; Prostatectomy - statistics & numerical data; Robotic Surgical Procedures - education; Robotic Surgical Procedures - statistics & numerical data; Safety; Surgeons - education; Surgeons - organization & administration; Surgery; Teamwork; United States
• ISSN: 0022-4804; 1095-8673
• DOI: 10.1016/j.jss.2016.06.092

Background Robotic surgery offers advantages over conventional operative approaches, but may also be associated with higher costs and additional risks. Analyzing surgical flow disruptions (FDs), defined as “deviations from the natural progression of an operation,” can help target training techniques and identify opportunities for improvement. Materials and methods Thirty-two Robotic Surgery operations were observed over a six-week period at one 900-bed surgical center. FDs were recorded in detail and classified into one of 11 different categories. Procedure type, robot model, and resident involvement were also recorded. Linear regression analyses were used to evaluate the effects of these parameters on FDs and operative duration. Results Twenty-one prostatectomies, 8 sacrocolpopexies, and 3 nephrectomies were observed. The mean number of FDs was 48.2 (95% CI 38.6-54.8 FDs), and mean operative duration was 163 minutes (95% CI 148-179 minutes). Each FD added 2.4 minutes (p=0.025) to a case’s total operative duration. The number and rate of FDs were significantly affected by resident involvement (p=0.008 and p=0.006, respectively). Resident cases demonstrated mostly Training, Equipment, and Robot Switch FDs, whereas non-resident cases demonstrated mostly Equipment, Instrument Changes, and External Factors FDs. Conclusions Though the FDs encountered in resident training are more frequent, they may not significantly increase operative duration. Other FDs, such as Equipment or External Factors, may be more impactful. Limiting these specific FDs should be the focus of performance improvement efforts.