title: The Impact of Robotic-Assisted Surgery on Training Gynecology Residents.
abstract: BACKGROUND
  To investigate the changes in surgical route of hysterectomy after implementation of robotics and to assess the impact on the surgical training of gynecology residents.
  
  
  METHODS
  This was an institutional review board-approved retrospective analysis at 2 large academic community hospitals. Subjects undergoing hysterectomy during 2005 and 2011 were identified. A stratified random sample representative of the overall number of hysterectomies, 20 per month for each year, was obtained. Charts were reviewed for route of hysterectomy and resident involvement. Chi-square analysis was used for main outcomes.
  
  
  RESULTS
  A total of 193 cases from 2005 and 146 cases from 2011 were included. A significant decline in vaginal hysterectomies was noted from 2005 to 2011: 62.2% (n = 120) to 27.4% (n = 40) (P < 0.001). Laparoscopic hysterectomies also declined from 30.1% to 19.9% during the same period (P < 0.026). In addition, although no robotic hysterectomies were performed in 2005, by 2011, this approach accounted for more than one fourth of all such surgeries. Of all cases examined, 40 in 2005 and 45 in 2011 were not attended by a resident. In 2005, 52% (21 of 40) of the uncovered cases were vaginal hysterectomies. However, in 2011, 55% (25 of 45) of the uncovered cases were robotic-assisted and only 11% (5 of 45) were vaginal hysterectomies.
  
  
  CONCLUSIONS
  The resultant decline in vaginal and laparoscopic hysterectomies coupled with an additional procedure to master places an increased burden on training programs. Although the impact of the changes on surgical competency is not yet known, our results identify potential areas for focus in training to ensure surgically competent physicians.
authors.affiliation: From the *TriHealth Obstetrics and Gynecology Residency; †Female Pelvic Medicine and Reconstructive Surgery Fellowship; and ‡TriHealth Hatton Research Institute, Cincinnati, OH.
authors.forename: Deepthi
authors.initials: D
authors.lastname: Moola
authors.forename: Lauren B
authors.initials: LB
authors.lastname: Westermann
authors.forename: Rachel
authors.initials: R
authors.lastname: Pauls
authors.forename: Michaela
authors.initials: M
authors.lastname: Eschenbacher
authors.forename: Catrina
authors.initials: C
authors.lastname: Crisp
mesh_terms: D000367:Age Factors; D003430:Cross-Sectional Studies; D005260:Female; D006176:Gynecology / Q000193:education* / Q000706:statistics & numerical data; D006764:Hospitals, Community / Q000706:statistics & numerical data; D006801:Humans; D007044:Hysterectomy / Q000193:education* / Q000706:statistics & numerical data; D007396:Internship and Residency / Q000379:methods* / Q000706:statistics & numerical data; D010535:Laparoscopy / Q000193:education / Q000706:statistics & numerical data; D008875:Middle Aged; D009820:Ohio; D012044:Regression Analysis; D012189:Retrospective Studies; D065287:Robotic Surgical Procedures / Q000193:education* / Q000706:statistics & numerical data