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Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease
Author(s) -
Sendag Fatih,
Zeybek Burak,
Akdemir Ali,
Ozgurel Banu,
Oztekin Kemal
Publication year - 2014
Publication title -
the international journal of medical robotics and computer assisted surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 53
eISSN - 1478-596X
pISSN - 1478-5951
DOI - 10.1002/rcs.1567
Subject(s) - learning curve , laparotomy , hysterectomy , medicine , laparoscopy , receiver operating characteristic , chart , area under the curve , robotic surgery , surgery , general surgery , computer science , operating system , statistics , mathematics
Abstract Background The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease. Methods Thirty‐six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age, BMI, operating time, set‐up time, docking time, uterine weight, blood loss, intraoperative complications, postoperative complications, conversions to laparotomy and length of hospital stay. Results The mean operating, set‐up and docking times were 169 ± 54.5, 52.9 ± 12.4 and 7.8 ± 7.6 min, respectively. The learning curve analysis revealed a decrease in both docking and operating times, with both curves plateauing after case 9. Conclusions The learning curve analysis revealed a decrease in docking time and operating time after case 9, suggesting that there might be a fast, learning curve for experienced laparoscopic surgeons to master robotic hysterectomy, and that the docking process does not have a significant negative influence on the overall operating time. Copyright © 2013 John Wiley & Sons, Ltd.