Reflections on training and management of junior radiologists through analysis of correction rates in emergency radiology reports
Year: 2025
Type: article
Study design: Observational Study
Abstract: PURPOSE: Numerous studies have examined factors affecting junior radiologists' interpretation accuracy, mostly focusing on Western countries. This study investigates the accuracy of radiology reports during emergency shifts in a Chinese hospital, considering shift times, examination types, radiologist experience, and patient factors. MATERIALS AND METHODS: From January 2023 to March 2024, we randomly selected emergency shifts and analyzed radiology reports initially interpreted by junior radiologists and reviewed by senior radiologists. This study compared the corrected rates between day (8 AM to 3:59 PM) and night shifts (8 PM to 7:59 AM), as well as between the first and second halves of each shift. Additionally, we examined the relationships between examination type and quantity, radiologist experience, patient age, and correction rates. RESULTS: In 19 day shifts and 18 night shifts, 14 junior radiologists initially interpreted 8,338 reports. The corrected rate for daytime emergency reports (25.09%) was higher than for nighttime reports (21.91%, p = 0.236). Corrected rate in the second half of shifts was lower than in the first half, regardless of day (28.89% vs. 22.15%, p < 0.001) or night (22.89% vs. 19.05%, p = 0.008). Radiologist experience is significantly associated with corrected rates (p < 0.001), with elderly patients (29.85%) showing a higher rate of corrections compared to children (22.03%) and middle-aged patients (18.85%, p < 0.001). CONCLUSION: Correction rates of radiology reports vary under different training, different working hours, and different working models. Customizing management practices and training programs based on research findings is essential to improve accuracy and develop specific guidelines.
Source: BMC Medical Education
Authors: Hong Wu, Ming Li, Jingwen Chen, Xuhui Fan, Meijuan He, Zaixiong Ji, Han Wang, Xiaorui Yin
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,990
Award: G8701876509
OpenAlex ID: W4411903870
