ArticleEmergency radiology2018
Pilot study of a new comprehensive radiology report categorization (RADCAT) system in the emergency department.
Article in Emergency radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Survey of radiologists and emergency department providers after implementation of a global radiology report categorization system.Emergency radiology · 2021Article
- Generalizable Inter-Institutional Classification of Abnormal Chest Radiographs Using Efficient Convolutional Neural Networks.Journal of digital imaging · 2019Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe purpose of this study was to describe a new, broadly applicable radiology report categorization (RADCAT) system that was developed collaboratively between radiologists and emergency department (ED) physicians, and to establish its usability and performance by interobserver variation.
methodsIn collaboration with our ED colleagues, we developed the RADCAT system for all imaging studies performed in our level-1 trauma center, including five categories that span the spectrum of normal through emergent life-threatening findings. During a pilot phase, four radiologists used the system real-time to categorize a minimum of 400 reports in the ED. From this pool of categorized studies, 58 reports were then selected semi-randomly, de-identified, stripped of their original categorization, and recategorized based on the narrative radiology report by 12 individual reviewers (6 radiologists, and 6 ED physicians). Interobserver variation between all reviewers, radiologists only, and ED physicians only was calculated using Cohen's Kappa statistic and Kendall's coefficient of concordance.
resultsAltogether, agreement among radiologists and ED physicians was substantial (κ = 0.73, p < 0.0001) and agreement for each category was substantial (all κ > 0.60, p < 0.0001). The lowest agreement was observed with RADCAT-3 (κ > 0.61, p < 0.0001) and the highest agreement with RADCAT-1 (κ > 0.85, p < 0.0001). A high trend in agreement was observed for radiologists and ED physicians and their combination (all W > 0.90, p < 0.0001).
conclusionsOur RADCAT system is understandable between radiologists and ED physicians for categorizing a wide range of imaging studies, and warrants further assessment and validation. Based upon these pilot results, we plan to adopt this RADCAT scheme and further assess its performance.
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