Validation of a Novel Simulation-Based Test in Robot-Assisted Radical Prostatectomy

Area of Science:

• Surgical Simulation
• Medical Education Technology
• Robotic Surgery Training

Background:

• Robot-assisted radical prostatectomy (RARP) requires specialized skills.
• Assessing surgical competency is crucial for patient safety.
• Current assessment methods for RARP may not fully capture skill acquisition.

Purpose of the Study:

• To establish validity evidence for a simulator-based test in RARP.
• To evaluate the ability of the simulator test to discriminate between surgeons of varying experience levels.
• To determine a reliable pass/fail threshold for RARP competency assessment.

Main Methods:

• A VR simulator test with three modules (Bladder Neck Dissection, Neurovascular Bundle Dissection, Ureterovesical Anastomosis) was used.
• Participants included novices, intermediates, and experienced RARP surgeons.
• Statistical analyses included Cronbach's alpha, generalizability theory, mixed-model ANOVA, and Pearson correlation.

Main Results:

• Six simulator metrics demonstrated acceptable internal consistency (Cronbach's alpha = 0.49) and discriminated between surgeon groups.
• Test-retest reliability ranged from 0.75 to 0.90.
• A combined simulator score significantly correlated with RARP experience (Pearson's r = 0.74) and differentiated all three experience levels.

Conclusions:

• The simulator-based test provides strong validity evidence for assessing RARP skills.
• The established pass/fail score can ensure surgeon competency prior to supervised clinical practice.
• This tool can enhance the safety and effectiveness of RARP training programs.