Reject rate analysis in digital radiography: an Australian emergency imaging department case study. Issue 1 (18th July 2019) - Atkinson, Samantha; Neep, Michael; Starkey, Deborah
Abstract: Introduction: Reject analysis in digital radiography (DR) helps guide the education and training of staff, influences department workflow, reduces patient dose and improves department efficiency. The purpose of this study was to investigate rejected radiographs at a major metropolitan emergency imaging department to help form a benchmark of reject rates for DR and to assess what radiographs are being rejected and why. Methods: A retrospective longitudinal study was undertaken as an in‐depth clinical audit. The data were collected using automated reject analysis software from two digital x‐ray systems from June 2015 to April 2017. The overall reject rate, reasons for rejection as well as the reject rates for individual radiographers, examination types and projections were analysed. Results: A total of 90, 298 radiographic images were acquired and included in the analysis. The average reject rate was 9%, and the most frequent reasons for image rejection were positioning error (49%) and anatomy cut‐off (21%). The reject rate varied between radiographers as well as for individual examination types and projections. Conclusions: The variation in radiographer reject rates and the high reject rate for some projections indicate that reject analysis is still necessary as a quality assurance tool for DR. A feedback system between radiologists and radiographers may reduce the high percentage of positioning errors by standardising the technical factors used to assess image quality. Future reject analysis should be conducted regularly incorporating an exposure indicator analysis as well as retrospective assessment of individual rejected images. Abstract : Reject analysis in radiography is a valuable quality assurance tool that was used frequently in plain film and computed radiography to monitor patient dose, image quality and department efficiency. This in‐depth clinical audit assessed 90, 298 images acquired in a digital emergency imaging department from June 2015 to April 2017 with the aim of identifying a benchmark reject rate for digital radiography and to investigate what images were being rejected more frequently and why. The average reject rate was 9%; however, this varied significantly between individual projections as well as individual radiographers, highlighting the need to continue to incorporate reject analysis into a standard quality assurance program for digital radiography.