Transoral robotic surgery: simulation-based standardized training.

Ning Zhang, Baran D Sumer
Author Information
  1. Ning Zhang: Department of Otolaryngology-Head and Neck Surgery, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas.

Abstract

IMPORTANCE: Simulation-based standardized training is important for the clinical training of physicians practicing robotic surgery.
OBJECTIVE: To train robotic surgery-naïve student volunteers using the da Vinci Skills Simulator (dVSS) for transoral robotic surgery (TORS).
DESIGN: Prospective inception cohort in 2012.
SETTING: Academic referral center.
PARTICIPANTS: Sixteen medical student volunteers lacking experience in robotic surgery.
INTERVENTIONS: Participants trained with the dVSS in 12 exercises until competent, defined as an overall score of at least 91%. After a 1-, 3-, 5-, or 7-week postinitial training hiatus (n = 4 per group), participants reachieved competence on follow-up.
MAIN OUTCOMES AND MEASURES: Total training time (TTT) to achieve competency, total follow-up time (TFT) to reachieve competency, and performance metrics.
RESULTS: All participants became competent. The TTT distribution was normal based on the Anderson-Darling normality test (P > .50), but our sample was divided into a short training time (STT) group (n = 10 [63%]) and long training time (LTT) group (n = 6 [37%]). The mean (SD) TTT was 2.4 (0.6) hours for the STT group and 4.7 (0.5) hours for the LTT group. All participants reachieved competence with a mean TFT that was significantly shorter than TTT. There was no significant difference between STT and LTT in mean TFT at 1 and 3 weeks (P = .79), but the LTT group had a longer TFT at 5 and 7 weeks (P = .04) but with no difference in final follow-up scores (P = .12).
CONCLUSIONS AND RELEVANCE: Physicians in training can acquire robotic surgery competency. Participants who acquire skills faster regain robotic skills faster after a training hiatus, but, on retraining, all participants can regain equivalent competence. This information provides a benchmark for a simulator training program.

MeSH Term

Computer Simulation
Education, Medical, Continuing
Humans
Mouth
Natural Orifice Endoscopic Surgery
Oropharyngeal Neoplasms
Prospective Studies
Robotics
United States

Word Cloud

Created with Highcharts 10.0.0trainingrobotic=groupsurgeryparticipantstimeTTTTFTPLTTn4competencefollow-upcompetencySTTmeanstandardizedstudentvolunteersdVSSParticipants12competenthiatusreachievedAND60hours75differenceweekscanacquireskillsfasterregainIMPORTANCE:Simulation-basedimportantclinicalphysicianspracticingOBJECTIVE:trainsurgery-naïveusingdaVinciSkillsSimulatortransoralTORSDESIGN:Prospectiveinceptioncohort2012SETTING:AcademicreferralcenterPARTICIPANTS:SixteenmedicallackingexperienceINTERVENTIONS:trainedexercisesdefinedoverallscoreleast91%1-3-5-7-weekpostinitialperMAINOUTCOMESMEASURES:TotalachievetotalreachieveperformancemetricsRESULTS:becamedistributionnormalbasedAnderson-Darlingnormalitytest>50sampledividedshort10[63%]long[37%]SD2significantlyshortersignificant1379longer04finalscoresCONCLUSIONSRELEVANCE:PhysiciansretrainingequivalentinformationprovidesbenchmarksimulatorprogramTransoralsurgery:simulation-based

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