Evaluation of a Novel Surgical Skills Training Course: are Cadavers Still the Gold Standard for Surgical Skills Training?

Department

neurosurgery

Document Type

Article

Abstract

Background: An increasing body of literature describing use of high-fidelity surgical training models is challenging long-held dogma that cadavers provide the best medium for postgraduate surgical skills training. The purpose of this study was to describe a surgical skills course comprising entirely synthetic training models developed by resident and attending neurosurgeons and to evaluate their perceptions of the overall usefulness of this course and its usefulness compared with cadaveric courses. Methods: Ten high-fidelity neurosurgical training models were developed. A neurosurgical skills course for residents was structured to include 7 spinal and 3 cranial learning stations, each with its own model and assigned attending expert. Resident and attending neurosurgeons were asked to complete surveys on their overall impressions of the course and models and on workload comparisons between models and real cases. Student t tests were used for statistical comparisons. Results: Survey responses were collected from 9 of 16 participating residents (56.3%) and 3 of 10 attending neurosurgeons (30.0%). Both groups believed that the course was very helpful overall to resident education. Respondents furthermore believed that the course was more helpful overall than cadaveric courses. Task load index testing showed no significant workload difference between models and real cases (P ≥ 0.17), except in temporal demand (P < 0.001). Conclusions: Resident and attending neurosurgeons subjectively believe that high-fidelity synthetic models were superior to cadavers as a surgical skills teaching platform. This study raises the question of whether cadavers should remain the gold standard for surgical skills courses. Expanded use of these teaching models and further study are warranted.

Publication Date

2019

Publication Title

World Neurosurgery

ISSN

1878-8750

Volume

127

First Page

63

Last Page

71

Digital Object Identifier (DOI)

10.1016/j.wneu.2019.03.230

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