ArticleIrish journal of medical science2016
Frequency and analysis of non-clinical errors made in radiology reports using the National Integrated Medical Imaging System voice recognition dictation software.
Article in Irish journal of medical science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
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Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Speech recognition for clinical documentation from 1990 to 2018: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2019Pooled it
- Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.Journal of medical systems · 2018Pooled it
- Cutting Edge to Cutting Time: Can ChatGPT Improve the Radiologist's Reporting?Journal of imaging informatics in medicine · 2025Article
- Nursing Analysis Based on Medical Imaging Technology before and after Coronary Angiography in Cardiovascular Medicine.Applied bionics and biomechanics · 2022Article
- Review
- Physician experience with speech recognition software in psychiatry: usage and perspective.BMC research notes · 2018Article
- Electronic Health Record Interactions through Voice: A Review.Applied clinical informatics · 2018Review
- Radiology reporting-from Hemingway to HAL?Insights into imaging · 2018Review
- Detecting Technical Image Quality in Radiology Reports.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2018Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVoice recognition (VR) dictation of radiology reports has become the mainstay of reporting in many institutions worldwide. Despite benefit, such software is not without limitations, and transcription errors have been widely reported.
aimEvaluate the frequency and nature of non-clinical transcription error using VR dictation software.
methodsRetrospective audit of 378 finalised radiology reports. Errors were counted and categorised by significance, error type and sub-type. Data regarding imaging modality, report length and dictation time was collected.
results67 (17.72 %) reports contained ≥1 errors, with 7 (1.85 %) containing 'significant' and 9 (2.38 %) containing 'very significant' errors. A total of 90 errors were identified from the 378 reports analysed, with 74 (82.22 %) classified as 'insignificant', 7 (7.78 %) as 'significant', 9 (10 %) as 'very significant'. 68 (75.56 %) errors were 'spelling and grammar', 20 (22.22 %) 'missense' and 2 (2.22 %) 'nonsense'. 'Punctuation' error was most common sub-type, accounting for 27 errors (30 %). Complex imaging modalities had higher error rates per report and sentence. Computed tomography contained 0.040 errors per sentence compared to plain film with 0.030. Longer reports had a higher error rate, with reports >25 sentences containing an average of 1.23 errors per report compared to 0-5 sentences containing 0.09.
conclusionThese findings highlight the limitations of VR dictation software. While most error was deemed insignificant, there were occurrences of error with potential to alter report interpretation and patient management. Longer reports and reports on more complex imaging had higher error rates and this should be taken into account by the reporting radiologist.
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