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

Competency-based neurosurgical training requires effective systems for longitudinal skill development and assessment.

To describe and evaluate a novel educational model-Recurrence Checkpoint: Knowledge and Skills(RCKaS)-for structured reinforcement of resident competencies.

The model was implemented in a 4-year residency program with quarterly checkpoints. Each checkpoint included cognitive tasks, technical simulations, and case-based evaluations, followed by faculty feedback.

The model facilitated early identification of skill gaps, enhanced resident confidence, and improved feedback quality. Faculty reported improved mentoring engagement and assessment clarity. The study employed a dual comparison strategy: (1) a within-subject analysis of entrustment progression across 3 structured checkpoints in the same cohort (n = 36); and (2) an exploratory comparison with a retrospective group of residents trained prior to RCKaS implementation (n = 14). RCKaS-trained residents demonstrated higher scores in clinical reasoning, procedural skills, and diagnostic accuracy.

Recurrence checkpoint offers a feasible and impactful tool for aligning training with core neurosurgical competencies. It supports personalized learning and prepares residents for progressive responsibility. This approach promotes sustained growth in clinical competence and may serve as a scalable model for other surgical training programs.

Prospective educational study with two-level comparisons (within-group and retrospective cohort).

Neurosurgical residency program at the National Center for Neurosurgery, Astana, Kazakhstan.

Thirty-six residents (PGY1-PGY4) enrolled between 2022 and 2024 and a retrospective cohort of fourteen residents enrolled between 2019 and 2021.