Assessing Surgical Skill in Orthopaedic Trauma Surgery Training: Behavioral Metrics for Digital Performance...

Area of Science:

• Orthopaedic surgery
• Surgical skill assessment
• Digital health technology

Background:

• Current orthopaedic trauma surgery skill assessment relies on subjective expert ratings, limiting consistency and scalability.
• Digitalization offers objective assessment but faces challenges in capturing the manual and haptic nature of surgery.
• This study introduces a digital assessment framework using tracked surgical tool motion to derive digital behavioral metrics (DBM).

Purpose of the Study:

• To identify which digital behavioral metrics (DBM) indicate technical proficiency in orthopaedic trauma surgery.
• To determine the predictive capability of DBM for expert-rated surgical performance.

Main Methods:

• Twenty-eight participants performed standardized fracture fixations on synthetic bone models.
• Surgical tool motion was captured to derive DBM like path length and smoothness.
• DBM were correlated with expert Global Rating Scale (GRS) scores, and a predictive model was trained.

Main Results:

• Several DBM, particularly tool path length and time per activity, strongly correlated with expert ratings (up to 0.6).
• The predictive model achieved a mean absolute difference of 3.8 points from the average GRS score, outperforming interexpert variability (4.6 points).

Conclusions:

• Digital behavioral metrics (DBM) are valid indicators of surgical skill in orthopaedic trauma surgery.
• DBM can objectively predict surgical performance, aligning better with average expert scores than individual ratings.
• This framework enables objective, expert-independent performance assessment for surgical training.