title: Frequency and analysis of non-clinical errors made in radiology reports using the National Integrated Medical Imaging System voice recognition dictation software.
abstract: BACKGROUND
  Voice 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.
  
  
  OBJECTIVE
  Evaluate the frequency and nature of non-clinical transcription error using VR dictation software.
  
  
  METHODS
  Retrospective 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.
  
  
  RESULTS
  67 (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.
  
  
  CONCLUSIONS
  These 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.
authors.affiliation: Department of Radiology, The Adelaide and Meath Hospital, Dublin 24, Ireland. Ronanmotyer@gmail.com.
authors.forename: R E
authors.initials: RE
authors.lastname: Motyer
authors.affiliation: Department of Radiology, The Adelaide and Meath Hospital, Dublin 24, Ireland.
authors.forename: S
authors.initials: S
authors.lastname: Liddy
authors.affiliation: Department of Radiology, The Adelaide and Meath Hospital, Dublin 24, Ireland.
authors.forename: W C
authors.initials: WC
authors.lastname: Torreggiani
authors.affiliation: Department of Radiology, The Adelaide and Meath Hospital, Dublin 24, Ireland.
authors.forename: O
authors.initials: O
authors.lastname: Buckley
mesh_terms: D006801:Humans; D008499:Medical Records / Q000592:standards*; D011859:Radiography / Q000592:standards; D011871:Radiology / Q000592:standards; D011873:Radiology Information Systems / Q000592:standards*; D012189:Retrospective Studies; D049250:Speech Recognition Software / Q000592:standards*
keywords: Productivity; Radiology; Report dictation; Reporting error; Voice recognition; Workflow