Image rejects/retakes--radiographic challenges.
A general held position among radiological personnel prior to digitalisation was that the problem of image rejects/retakes should more or less vanish. However, rejects/retakes still impose several challenges within radiographic imaging; they occupy unnecessary resources, expose patients to unnecessary ionizing radiation and may also indicate suboptimal quality management. The latter is the main objective of this paper, which is based on a survey of international papers published both for screen/film and digital technology. The digital revolution in imaging seems to have reduced the percentage of image rejects/retakes from 10-15 to 3-5 %. The major contribution to the decrease appears to be the dramatic reduction of incorrect exposures. At the same time, rejects/retakes due to lack of operator competence (positioning, etc.) are almost unchanged, or perhaps slightly increased (due to lack of proper technical competence, incorrect organ coding, etc.). However, the causes of rejects/retakes are in many cases defined and reported with reference to radiographers' subjective evaluations. Thus, unless radiographers share common views on image quality and acceptance criteria, objective measurements and assessments of reject/retake rates are challenging tasks. Interestingly, none of the investigated papers employs image quality parameters such as 'too much noise' as categories for rejects/retakes. Surprisingly, no reject/retake analysis seems yet to have been conducted for direct digital radiography departments. An increased percentage of rejects/retakes is related to 'digital skills' of radiographers and therefore points to areas for extended education and training. Furthermore, there is a need to investigate the inter-subjectivity of radiographers' perception of, and attitude towards, both technical and clinical image quality criteria. Finally, there may be a need to validate whether reject/retake rate analysis is such an effective quality indicator as has been asserted.
Department of Health, Care and Nursing, Gjøvik University College, Gjøvik, Norway. dag.waaler@hig.no
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Hofmann
D003951:Diagnostic Errors / Q000517:prevention & control* / Q000706:statistics & numerical data*; D003952:Diagnostic Imaging / Q000706:statistics & numerical data*; D007090:Image Interpretation, Computer-Assisted