Utilization of a Novel Web Based Performance Feedback Application (Case Curve) in Neurosurgical Trainee Cadaveric Simulation of the Retrosigmoid Approach

Introduction: There has been increased focus on developing ways to improve and track surgical education through simulations, cadaveric dissections, and more recently, focused surgical performance evaluation programs. A novel web-based feedback application (Case Curve) was instituted at a neurosurgical residency program to track resident cognitive and technical performance.

Methods: Nine neurosurgical residents were evaluated for technical skills and knowledge fund specific to performing retrosigmoid craniotomies. Each resident took a 15-question quiz and performed a video-recorded retrosigmoid approach on a cadaveric specimen in a laboratory. Residents then used Case Curve to self-evaluate their performance in seven skill categories. All dissection videos were blindly reviewed by six skull base neurosurgeons from two different institutions who also scored the residents with Case Curve in each skill category. Feedback was given from Case Curve evaluations, and dissections and quizzes were subsequently repeated by the same residents. Self and staff evaluations were again performed.

Results: Each resident demonstrated significant improvement after structured Case Curve feedback. There was an improvement of 20.7% in mean written quiz scores (p < 0.03), and 37% improvement in mean blinded staff overall score totals (p < 0.01). Microvascular dissection was the skill that saw the least improvement. There was an inverse relationship between self-assessment scores and objective blinded staff scores.

Conclusion : Structured feedback for neurosurgical trainees allows supervising neurosurgeons to reinforce good habits, while also identifying and correcting improper technique. The simple Case Curve mechanism for feedback has potential to serve as a good model for intentional surgical education for targeted improvement with measurable results.