Differentiating between novice and expert surgeons based on errors derived from task analysis

Motivation - To capture the salient aspects of decision making during the Laparoscopic Cholecystectomy procedure to differentiate between novice and expert surgeons. The output of this study is being used in the design of a computer based training system for surgical decision making using serious game technology. Research approach - A series of observations of a range of surgeons performing the Laparoscopic Cholecystectomy procedure was undertaken. These observations included video recordings, audio recordings, and textual observations of the procedures, and subsequent informal interviews. A task analysis was used, focusing on errors, to help identify key differences in expert and novice decision making in the Laparoscopic Cholecystectomy procedure. The occurrence and duration of these errors within video observations are examined. Findings/Design - The observations confirm that there is a clear distinction between novice and expert surgeons both in the rate of occurrence of certain errors and in the duration of errors. While some of the results are surprising they lend support to the utilisation of errors as a measurement of expertise in this domain. Research limitations/Implications - The observations were restricted to one teaching hospital, with a limited pool of surgeons. Originality/Value - This research makes a contribution to the field of computer based training for laparoscopic surgery, and to the differentiation between novice and expert surgeons. Take away message - Task analysis with an emphasis on measurements of error is a viable method for differentiating between novice and expert surgeons in the Laparoscopic Cholecystectomy procedure.