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16 March 2020 Effect of time of day on radiology image interpretations
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Abstract
Numerous factors contribute to radiologist image reading discrepancy and interpretive errors. However, a factor often overlooked is how interpretations might be impacted by the time of day when the image reading takes place—a factor that other disciplines have shown to be a determinant of competency. This study therefore seeks to investigate whether radiologists’ reading performances vary according to the time of the day at which the readings take place. We evaluated 197 mammographic reading assessments collected from the BreastScreen Reader Assessment Strategy (BREAST) database, which included reading timestamps and radiologists’ demographic data, and conducted an analysis of covariance to determine whether time of day influenced the radiologists’ specificity, lesion sensitivity, and jackknife alternative free-response receiver operating characteristic (JAFROC). After adjusting for radiologist experience and fellowship, we found a significant effect of the time of day of the readings on specificity but none on lesion sensitivity or JAFROC. Radiologist specificity was significantly lower in the late morning (10 am–12 pm) and late afternoon (4 pm–6 pm) than in the early morning (8 am–10 am) or early afternoon (2 pm–4 pm), indicating a higher rate of false-positive interpretations in the late morning and late afternoon. Thus, the time of day mammographic image readings take place may influence radiologists’ performances, specifically their ability to identify normal images correctly. These findings present significant implications for radiologic clinicians.
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© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Abdulaziz S. Alshabibi, Moayyad E. Suleiman, Kriscia A. Tapia, Robert Heard, and Patrick C. Brennan "Effect of time of day on radiology image interpretations", Proc. SPIE 11316, Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, 1131608 (16 March 2020); https://doi.org/10.1117/12.2543503
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