Review of methods for objective surgical skill evaluation

Carol E. Reiley, Henry C. Lin, David D. Yuh, Gregory D. Hager

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)356-366
Number of pages11
JournalSurgical endoscopy
Volume25
Issue number2
DOIs
StatePublished - Feb 2011

Keywords

  • Human robotic training
  • Surgical training courses

ASJC Scopus subject areas

  • Surgery

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