Christine Lamoureux1, Tarek N Hanna2, Devin Sprecher3, Scott Weber3, Edward Callaway3. 1. Virtual Radiologic, 11995 Singletree Ln #500, Eden Prairie, MN, 55344, USA. christine.lamoureux@vrad.com. 2. Division of Emergency Radiology, Department of Radiology and Imaging Sciences, Emory University, 550 Peachtree Rd, Atlanta, GA, 30308, USA. 3. Virtual Radiologic, 11995 Singletree Ln #500, Eden Prairie, MN, 55344, USA.
Abstract
PURPOSE: To evaluate the feasibility of adding pathology to recent radiologist error characterization schemes of modality and anatomic region and the potential of this data to more specifically inform peer review and peer learning. METHODS: Quality assurance data originating from 349 radiologists in a national teleradiology practice were collected for 2019. Interpretive errors were simply categorized as major or minor. Reporting or communication errors were classified as administrative errors. Interpretive errors were then divided by modality, anatomic region and placed into one of 64 pathologic categories. RESULTS: Out of 1,628,464 studies, the discrepancy rate was 0.5% (8181/1,634,201). The 8181 total errors consisted of 2992 major errors (0.18%) and 5189 minor errors (0.32%). Precisely, 3.1% (257/8181) of total errors were administrative. Of major interpretive errors, 75.5% occurred on CT, with CT abdomen and pelvis accounting for 40.4%. The most common pathologic discrepancy for all exams was in the category of mass, nodule, or adenopathy (1583/8181), the majority of which were minor (1315/1583). The most common pathologic discrepancy for the 2937 major interpretive errors was fracture or dislocation (27%; 793/2937), followed by bleed (10.7%; 315/2937). CONCLUSION: The addition of error-related pathology to peer review is both feasible and practical and provides a more detailed guide to targeted individual and practice-wide peer learning quality improvement efforts. Future research is needed to determine if there are measurable improvements in detection or interpretation of specific pathologies following error feedback and educational interventions.
PURPOSE: To evaluate the feasibility of adding pathology to recent radiologist error characterization schemes of modality and anatomic region and the potential of this data to more specifically inform peer review and peer learning. METHODS: Quality assurance data originating from 349 radiologists in a national teleradiology practice were collected for 2019. Interpretive errors were simply categorized as major or minor. Reporting or communication errors were classified as administrative errors. Interpretive errors were then divided by modality, anatomic region and placed into one of 64 pathologic categories. RESULTS: Out of 1,628,464 studies, the discrepancy rate was 0.5% (8181/1,634,201). The 8181 total errors consisted of 2992 major errors (0.18%) and 5189 minor errors (0.32%). Precisely, 3.1% (257/8181) of total errors were administrative. Of major interpretive errors, 75.5% occurred on CT, with CT abdomen and pelvis accounting for 40.4%. The most common pathologic discrepancy for all exams was in the category of mass, nodule, or adenopathy (1583/8181), the majority of which were minor (1315/1583). The most common pathologic discrepancy for the 2937 major interpretive errors was fracture or dislocation (27%; 793/2937), followed by bleed (10.7%; 315/2937). CONCLUSION: The addition of error-related pathology to peer review is both feasible and practical and provides a more detailed guide to targeted individual and practice-wide peer learning quality improvement efforts. Future research is needed to determine if there are measurable improvements in detection or interpretation of specific pathologies following error feedback and educational interventions.