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Retained surgical item identification on imaging studies: a training module for radiology residents
Kristin Kelly Porter1, Paul D Bailey2, Ryan Woods2
1Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins Medical Institutions, 1800 Orleans Street, Body MRI, Room 143, Baltimore, MD, 21287, USA. kporte14@jhmi.edu.
Purpose:
Many hospitals experience one or more retained surgical item events per year, with risk of patient morbidity and medicolegal consequences. We hypothesized that the confidence and performance of the radiologist would be enhanced by prior training in retained surgical item detection and by prior exposure to commonly employed surgical instruments and devices.
Methods:
A training module for radiology residents was created through literature review, expert consultation, and imaging of commonly employed surgical instruments and devices. A survey assessing resident command of background knowledge, policy, and image-based retained surgical item questions was created. Additionally resident confidence for hospital policy and retained surgical item identification was assessed. A pre-module survey and confidence questionnaire were administered to first- through fourth- year residents. For one month, the training module was available online for independent review. Subsequently, a post-module survey and confidence questionnaire were completed by participants. T tests were performed to evaluate pre- and posttest means for survey performance and confidence questions.
Results:
Mean post-module survey performance significantly improved compared with pre-module performance. Mean confidence levels for ability to incidentally identify a retained surgical item on a radiograph obtained for another indication and current understanding of the institution's policy regarding retained surgical items were also significantly increased.
Conclusion:
The knowledge base, diagnostic performance, and confidence of radiology residents were significantly enhanced by online teaching module training in retained surgical item detection.
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