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.

IntroductionThe provision of a written comment on traumatic abnormalities of the musculoskeletal system detected by radiographers can assist referrers and may improve patient management, but the practice has not been widely adopted outside the United Kingdom. The purpose of this study was to investigate Australian radiographers' perceptions of their readiness for practice in a radiographer commenting system and their educational preferences in relation to two different delivery formats of image interpretation education, intensive and non-intensive.MethodsA cross-sectional web-based questionnaire was implemented between August and September 2012. Participants included radiographers with experience working in emergency settings at four Australian metropolitan hospitals. Conventional descriptive statistics, frequency histograms, and thematic analysis were undertaken. A Wilcoxon signed-rank test examined whether a difference in preference ratings between intensive and non-intensive education delivery was evident.ResultsThe questionnaire was completed by 73 radiographers (68% response rate). Radiographers reported higher confidence and self-perceived accuracy to detect traumatic abnormalities than to describe traumatic abnormalities of the musculoskeletal system. Radiographers frequently reported high desirability ratings for both the intensive and the non-intensive education delivery, no difference in desirability ratings for these two formats was evident (z = 1.66, P = 0.11).ConclusionsSome Australian radiographers perceive they are not ready to practise in a frontline radiographer commenting system. Overall, radiographers indicated mixed preferences for image interpretation education delivered via intensive and non-intensive formats. Further research, preferably randomised trials, investigating the effectiveness of intensive and non-intensive education formats of image interpretation education for radiographers is warranted.

The purpose of this commentary was to outline several key considerations and challenges for medical imaging departments during a global pandemic. Five public hospital medical imaging departments were identified in South‐East Queensland, Australia, to provide insight into their response to the COVID‐19 pandemic. Common themes were identified, with the four considered most pertinent documented in this commentary. Similar operational considerations and challenges were identified amongst all sites. This commentary intends to serve as a starting point for medical imaging departments in considering the planning and implementation of services in a pandemic scenario.

A range of factors are likely to contribute to the successful implementation of radiographer commenting in addition to abnormality detection in emergency settings. Effective image interpretation education amenable to completion by radiographers would likely prove valuable in preparing radiographers for participation in abnormality detection and commenting systems in emergency settings.

Introduction:The largest source of manmade ionising radiation exposure to the public stems from diagnostic medical imaging examinations. Reject analysis, a form of quality assurance, was introduced to minimise repeat exposures. The purpose of this study was to analyse projection-specific reject rates and radiographic examinations with multiple rejects. Methods: A retrospective audit of rejected radiographs was undertaken in a busy Australian metropolitan emergency digital X-ray room from March to June 2018. The data were collected by reject analysis software embedded within the X-ray unit. Reject rates, and reasons for rejection for each X-ray projection were analysed. Results: Data from 11, 596 images showed overall reject rate was 10.3% and the overall multiple reject rate was 1.3%. The projections with both a high number and high percentage of rejects were antero-posterior (AP) chest (175, 18.1%), AP pelvis (78, 22.5%), horizontal beam hip (61, 33.5%) and horizontal beam knee (116, 30.5%). The projections with both a high frequency and multiple reject rate were horizontal beam knee (32, 8.4%) and horizontal beam hip (17, 9.3%). The top reasons for multiple rejects were positioning (67.1%) and anatomy cut-off (8.4%). Conclusions: The findings of this study demonstrated that projection-specific reject and multiple reject analysis in digital radiography is necessary in identifying areas for quality improvement which will reduce radiation exposure to patients. Projections that were frequently repeated in this study were horizontal beam knee and horizontal beam hip. Future research could involve re-auditing the department following the implementation of improvement strategies to reduce unnecessary radiation exposure.

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IntroductionA Radiographer Abnormality Detection System (RADS), such as the ‘red dot system’, involves radiographers highlighting the presence of potential acute abnormalities on radiographs in the emergency setting. The literature suggests little additional training is required of radiographers to participate in such a system, posing little impact on current workflow while remaining a cost‐effective, easy‐to‐implement program. However, its use outside the United Kingdom is sporadic. The purpose of this study was to investigate the frequency of use of a RADS in Queensland public hospitals.MethodsA cross‐sectional web‐based questionnaire was developed and distributed to 28 medical imaging department directors throughout metropolitan, rural and remote Queensland (Australia) public hospitals. The results of this survey were analysed using conventional descriptive statistics of response frequencies and the percentage of the sample.ResultsThe questionnaire was completed by 25 radiography directors (89% response rate). Sixteen percent of respondents, all metropolitan‐based, indicated a RADS was in operation (n = 4/25; 16%). Respondents without a RADS (n = 21/21; 100%) expressed interest in a trial. Just over half (n = 13/25; 52%) of the respondents believed their staff members were not trained appropriately to implement a RADS successfully.ConclusionThis study found an infrequent use of RADSs in Queensland public hospitals. This finding presents a unique opportunity for medical imaging professionals to enhance communication between the facets of a multidisciplinary emergency team via the implementation of RADS complemented by a radiographer commenting system.