title: Identification of Essential Components of Thoracoscopic Lobectomy and Targets for Simulation.
abstract: BACKGROUND
  Fewer than 50% of lobectomies for lung cancer are performed using thoracoscopic (video-assisted thoracic surgery [VATS]) techniques. This situation could be mitigated through the use of simulation training. Using a Delphi process, this study identified essential components of VATS right upper lobectomy most amenable to focused simulation.
  
  
  METHODS
  Experienced VATS surgeons were randomly selected for participation. A custom Internet interface permitted anonymous voting, commenting, and the ability to modify and propose new components. A component was declared essential when 80% or more of the study participants agreed or strongly agreed on this designation. Participants rated each component for difficulty and then voted for components that were most appropriate for simulation.
  
  
  RESULTS
  Thirty-five surgeons initially agreed to participate, and 30 completed the study. Twenty-four components were identified after three votes, and 21 of these components were considered essential. Procedural components that scored the highest for overall difficulty and that were deemed most appropriate for focused simulation included division of the truncus anterior, division of the posterior segmental artery, division of the upper lobe vein, and division of the upper lobe bronchus.
  
  
  CONCLUSIONS
  A Delphi approach enabled surgeons of disparate training backgrounds and experience to agree on essential components of a VATS lobectomy. There was agreement on the components that are most appropriate for simulation. These findings can be used to design simulation exercises for VATS lobectomy by using targeted anatomy.
authors.affiliation: Department of Surgery, University of Chicago, Chicago, Illinois; Comprehensive Cancer Center, University of Chicago, Chicago, Illinois. Electronic address: mferguso@surgery.bsd.uchicago.edu.
authors.forename: Mark K
authors.initials: MK
authors.lastname: Ferguson
authors.affiliation: Centre for Technology Enabled Health Research, Coventry University, Coventry, United Kingdom.
authors.forename: Cathy
authors.initials: C
authors.lastname: Bennett
mesh_terms: D001291:Attitude of Health Personnel; D002983:Clinical Competence; D003697:Delphi Technique; D006801:Humans; D008175:Lung Neoplasms / Q000601:surgery*; D011013:Pneumonectomy / Q000193:education* / Q000379:methods; D000066908:Simulation Training; D020775:Thoracic Surgery, Video-Assisted / Q000193:education* / Q000379:methods