Literature DB >> 25484983

Objective evaluation of expert performance during human robotic surgical procedures.

Timothy N Judkins1, Dmitry Oleynikov2, Nick Stergiou3.   

Abstract

Robotic laparoscopic surgery has revolutionized minimally invasive surgery and has increased in popularity due to its important benefits. However, evaluation of surgical performance during human robotic laparoscopic procedures in the operating room is very limited. We previously developed quantitative measures to assess robotic surgical proficiency. In the current study, we want to determine if training task performance is equivalent to performance during human surgical procedures performed with robotic surgery. An expert with more than 5 years of robotic laparoscopic surgical experience performed two training tasks (needle passing and suture tying) and one human laparoscopic procedure (Nissan fundoplication) using the da Vinci™ Surgical System (dVSS). Segments of the human procedure that required needle passing and suture tying were extracted. Time to task completion, distance traveled, speed, curvature, and grip force were measured at the surgical instrument tips. Single-subject analysis was used to compare training task performance and human surgical performance. Nearly all objective measures (8 out of 13) were significantly different between training task performance and human surgical performance for both the needle passing and the suture tying tasks. The surgeon moved slower, made more curved movements, and used more grip force during human surgery. Even though it appears that the surgeon performed better in the training tasks, it is likely that during human surgical procedures, the surgeon is more cautious and meticulous in the movements performed in order to prevent tissue damage or other complications. The needle passing and the suture tying training tasks may be suitable to establish a foundation of surgical skill; however, further training may be necessary to improve transfer of learning to the operating room. We recommend that more realistic training tasks be developed to better predict performance during robotic surgical procedures and testing the transferability of basic skill acquisition to surgical performance.

Entities:  

Keywords:  Nissan fundoplication; Operating room; Performance; Quantitative; Robotic surgery

Year:  2008        PMID: 25484983      PMCID: PMC4247470          DOI: 10.1007/s11701-007-0067-1

Source DB:  PubMed          Journal:  J Robot Surg        ISSN: 1863-2483


  22 in total

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Journal:  Arch Surg       Date:  2001-10

2.  What is the value of telerobotic technology in gastrointestinal surgery?

Authors:  A Perez; M J Zinner; S W Ashley; D C Brooks; E E Whang
Journal:  Surg Endosc       Date:  2003-01-18       Impact factor: 4.584

3.  Robotic surgery and resident training.

Authors:  D A De Ugarte; D A Etzioni; C Gracia; J B Atkinson
Journal:  Surg Endosc       Date:  2003-03-28       Impact factor: 4.584

4.  Virtual reality training improves operating room performance: results of a randomized, double-blinded study.

Authors:  Neal E Seymour; Anthony G Gallagher; Sanziana A Roman; Michael K O'Brien; Vipin K Bansal; Dana K Andersen; Richard M Satava
Journal:  Ann Surg       Date:  2002-10       Impact factor: 12.969

5.  Robotic surgery: identifying the learning curve through objective measurement of skill.

Authors:  L Chang; R M Satava; C A Pellegrini; M N Sinanan
Journal:  Surg Endosc       Date:  2003-09-10       Impact factor: 4.584

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Authors:  K Moorthy; Y Munz; A Dosis; J Hernandez; S Martin; F Bello; T Rockall; A Darzi
Journal:  Surg Endosc       Date:  2004-04-06       Impact factor: 4.584

7.  Enhanced robotic surgical training using augmented visual feedback.

Authors:  Timothy N Judkins; Dmitry Oleynikov; Nick Stergiou
Journal:  Surg Innov       Date:  2008-03       Impact factor: 2.058

8.  Objective evaluation of expert and novice performance during robotic surgical training tasks.

Authors:  Timothy N Judkins; Dmitry Oleynikov; Nick Stergiou
Journal:  Surg Endosc       Date:  2008-04-29       Impact factor: 4.584

9.  Calculating confidence intervals for some non-parametric analyses.

Authors:  M J Campbell; M J Gardner
Journal:  Br Med J (Clin Res Ed)       Date:  1988-05-21

10.  Robotic surgery training and performance: identifying objective variables for quantifying the extent of proficiency.

Authors:  K Narazaki; D Oleynikov; N Stergiou
Journal:  Surg Endosc       Date:  2005-12-07       Impact factor: 3.453

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  3 in total

Review 1.  Review of methods for objective surgical skill evaluation.

Authors:  Carol E Reiley; Henry C Lin; David D Yuh; Gregory D Hager
Journal:  Surg Endosc       Date:  2010-07-07       Impact factor: 4.584

2.  A deep-learning model using automated performance metrics and clinical features to predict urinary continence recovery after robot-assisted radical prostatectomy.

Authors:  Andrew J Hung; Jian Chen; Saum Ghodoussipour; Paul J Oh; Zequn Liu; Jessica Nguyen; Sanjay Purushotham; Inderbir S Gill; Yan Liu
Journal:  BJU Int       Date:  2019-03-20       Impact factor: 5.588

3.  Application of Design Structure Matrix to Simulate Surgical Procedures and Predict Surgery Duration.

Authors:  Zhaoxuan Li; Derrick Tate; Thomas McGill; John Griswold; Ming-Chien Chyu
Journal:  Minim Invasive Surg       Date:  2021-12-06
  3 in total

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