Recurrence Checkpoint Knowledge and Skills Methodology for Continuous Development in Neurosurgical Residency

Area of Science:

• Medical Education
• Neurosurgery
• Surgical Training

Background:

• Competency-based neurosurgical training necessitates robust systems for ongoing skill development and evaluation.
• Effective assessment tools are crucial for tracking resident progress and ensuring patient safety.

Purpose of the Study:

• To introduce and assess the Recurrence Checkpoint: Knowledge and Skills (RCKaS) model, a novel educational framework designed for structured reinforcement of neurosurgical resident competencies.
• To evaluate the impact of the RCKaS model on resident skill acquisition and faculty engagement in training.

Main Methods:

• Implementation of the RCKaS model in a 4-year neurosurgical residency program, featuring quarterly cognitive, simulation, and case-based evaluations with faculty feedback.
• A prospective educational study utilizing a dual comparison strategy: within-subject analysis of 36 residents' entrustment progression and comparison with a retrospective cohort of 14 residents.
• Utilized cognitive tasks, technical simulations, and case-based evaluations for comprehensive assessment.

Main Results:

• The RCKaS model facilitated early identification of resident skill deficits and improved the quality of feedback provided.
• RCKaS-trained residents exhibited enhanced confidence, superior clinical reasoning, improved procedural skills, and greater diagnostic accuracy compared to the retrospective cohort.
• Faculty reported increased mentoring engagement and clearer assessment criteria.

Conclusions:

• The Recurrence Checkpoint model is a feasible and effective method for aligning neurosurgical training with core competencies.
• This approach supports personalized learning pathways and prepares residents for increasing levels of responsibility, fostering sustained competence.
• The RCKaS model demonstrates potential as a scalable framework for enhancing surgical residency programs globally.