title: Review of methods for objective surgical skill evaluation.
abstract: BACKGROUND
  Rising health and financial costs associated with iatrogenic errors have drawn increasing attention to the dexterity of surgeons. With the advent of new technologies, such as robotic surgical systems and medical simulators, researchers now have the tools to analyze surgical motion with the goal of differentiating the level of technical skill in surgeons.
  
  
  METHODS
  The review for this paper is obtained from a Google Scholar and PubMed search of the key words "objective surgical skill evaluation." Only studies that included motion analysis were used.
  
  
  RESULTS
  In this paper, we provide a clinical motivation for the importance of surgical skill evaluation. We review the current methods of tracking surgical motion and the available data-collection systems. We also survey current methods of surgical skill evaluation and show that most approaches fall into one of three methods: (1) structured human grading; (2) descriptive statistics; or (3) statistical language models of surgical motion. We discuss the need for an encompassing approach to model human skill through statistical models to allow for objective skill evaluation.
authors.affiliation: Laboratory of Computational Sensing and Robotics Department of Computer Science, Johns Hopkins University, 3400 N. Charles Street, Baltimore, MD 21218, USA. creiley@jhu.edu
authors.forename: Carol E
authors.initials: CE
authors.lastname: Reiley
authors.forename: Henry C
authors.initials: HC
authors.lastname: Lin
authors.forename: David D
authors.initials: DD
authors.lastname: Yuh
authors.forename: Gregory D
authors.initials: GD
authors.lastname: Hager
mesh_terms: D002983:Clinical Competence; D003198:Computer Simulation; D004502:Education, Medical, Continuing / Q000379:methods; D004503:Education, Medical, Graduate / Q000379:methods; D004724:Endoscopy / Q000193:education / Q000379:methods; D005069:Evaluation Studies as Topic; D005260:Female; D006801:Humans; D010535:Laparoscopy / Q000193:education* / Q000379:methods; D059032:Learning Curve; D008297:Male; D012371:Robotics / Q000193:education* / Q000379:methods; D013647:Task Performance and Analysis; D014481:United States