The Role of Report Comparison, Analysis, and Discrepancy Categorization in Resident Education

Area of Science:

• Radiology
• Medical Education
• Health Informatics

Background:

• Radiology resident education relies on accurate and timely feedback.
• Discrepancies between preliminary and finalized radiology reports can impact patient care and learning.
• Automated analysis offers a novel approach to identify and categorize these discrepancies.

Purpose of the Study:

• To evaluate the utility of automated radiology report comparison for resident education.
• To provide qualitative and quantitative feedback on discrepancies between preliminary and finalized reports.
• To assess the impact of automated feedback on reporting accuracy.

Main Methods:

• Anonymous surveys were administered to radiology residents and faculty.
• A 4-week study analyzed 544 reports (preliminary and finalized) across all modalities.
• Discrepancies were automatically compared, categorized by clinical relevance, quality, or structure, and compared between junior and senior residents.

Main Results:

• 31% of reports were unchanged; no significant difference between junior and senior residents.
• Of 370 discrepancies, 21.9% were clinically relevant, 28.6% related to quality, and 49.5% to structure/syntax.
• Senior residents showed fewer clinical relevance discrepancies but more quality-related ones.

Conclusions:

• Categorizing report corrections is useful for individual feedback and assessing reporting accuracy.
• Quantitative report comparison and analysis show potential for programmatic resident education.
• Automated analysis can help tailor educational strategies based on cumulative data and trend analysis.