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Reject rate analysis in digital radiography: an Australian emergency imaging department case study
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| Zeitschriftentitel: | Journal of Medical Radiation Sciences |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Journal of Medical Radiation Sciences, 67, 2020, 1, S. 72-79 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Wiley
|
| Schlagwörter: |
| author_facet |
Atkinson, Samantha Neep, Michael Starkey, Deborah Atkinson, Samantha Neep, Michael Starkey, Deborah |
|---|---|
| author |
Atkinson, Samantha Neep, Michael Starkey, Deborah |
| spellingShingle |
Atkinson, Samantha Neep, Michael Starkey, Deborah Journal of Medical Radiation Sciences Reject rate analysis in digital radiography: an Australian emergency imaging department case study Radiology, Nuclear Medicine and imaging Radiological and Ultrasound Technology |
| author_sort |
atkinson, samantha |
| spelling |
Atkinson, Samantha Neep, Michael Starkey, Deborah 2051-3895 2051-3909 Wiley Radiology, Nuclear Medicine and imaging Radiological and Ultrasound Technology http://dx.doi.org/10.1002/jmrs.343 <jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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.</jats:p></jats:sec> Reject rate analysis in digital radiography: an Australian emergency imaging department case study Journal of Medical Radiation Sciences |
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Wiley, 2020 |
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Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
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Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_full |
Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
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Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_full_unstemmed |
Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_short |
Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_sort |
reject rate analysis in digital radiography: an australian emergency imaging department case study |
| topic |
Radiology, Nuclear Medicine and imaging Radiological and Ultrasound Technology |
| url |
http://dx.doi.org/10.1002/jmrs.343 |
| publishDate |
2020 |
| physical |
72-79 |
| description |
<jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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.</jats:p></jats:sec> |
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| author | Atkinson, Samantha, Neep, Michael, Starkey, Deborah |
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| author_sort | atkinson, samantha |
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| description | <jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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.</jats:p></jats:sec> |
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| spelling | Atkinson, Samantha Neep, Michael Starkey, Deborah 2051-3895 2051-3909 Wiley Radiology, Nuclear Medicine and imaging Radiological and Ultrasound Technology http://dx.doi.org/10.1002/jmrs.343 <jats:title>Abstract</jats:title><jats:sec><jats:title>Introduction</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusions</jats:title><jats:p>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.</jats:p></jats:sec> Reject rate analysis in digital radiography: an Australian emergency imaging department case study Journal of Medical Radiation Sciences |
| spellingShingle | Atkinson, Samantha, Neep, Michael, Starkey, Deborah, Journal of Medical Radiation Sciences, Reject rate analysis in digital radiography: an Australian emergency imaging department case study, Radiology, Nuclear Medicine and imaging, Radiological and Ultrasound Technology |
| title | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_full | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_fullStr | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_full_unstemmed | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_short | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| title_sort | reject rate analysis in digital radiography: an australian emergency imaging department case study |
| title_unstemmed | Reject rate analysis in digital radiography: an Australian emergency imaging department case study |
| topic | Radiology, Nuclear Medicine and imaging, Radiological and Ultrasound Technology |
| url | http://dx.doi.org/10.1002/jmrs.343 |