Learning curves for endobronchial ultrasound using cusum analysis.

Area of Science:

• Medical Education
• Pulmonology
• Quality Control

Background:

• Medical trainee assessment faces subjectivity and bias challenges.
• Cusum analysis, a quality control tool, is being adapted for medical training.
• Endobronchial ultrasound (EBUS) is crucial for lung cancer diagnosis, necessitating accurate competency assessment for trainees.

Purpose of the Study:

• To evaluate the learning curve for endobronchial ultrasound (EBUS) using cusum analysis.
• To assess trainee competence in EBUS procedures for lung cancer diagnosis and staging.

Main Methods:

• Retrospective review of 500 patients undergoing EBUS across five tertiary referral centers.
• Cusum analysis applied to the first 100 cases per center, with each operator starting anew.
• Data presented as learning curves to visualize competence acquisition.

Main Results:

• Significant variability in the time required to achieve EBUS competence was observed.
• Pooled sensitivity for EBUS-guided transbronchial needle aspiration (TBNA) was 67.4%.

Conclusions:

• Cusum analysis is suitable for assessing binary outcome procedures like EBUS.
• Establishing appropriate performance standards is crucial for accurate underperformance identification.
• The learning curve for EBUS appears longer than previously reported, with individual learning speeds varying.