title: Error rates in breast imaging reports: comparison of automatic speech recognition and dictation transcription.
abstract: OBJECTIVE
  The purpose of this study was to compare the error rates in breast imaging reports generated with automated speech recognition (ASR) technology as opposed to conventional dictation transcription.
  
  
  METHODS
  Breast imaging reports reviewed from January 2009 to April 2010 during multidisciplinary tumor board meetings at two hospitals were scrutinized for minor and major errors.
  
  
  RESULTS
  Of 615 reports obtained, 308 were generated with ASR and 307 with conventional dictation transcription. At least one major error was found in 23% of ASR reports, as opposed to 4% of conventional dictation transcription reports (p < 0.01). Major errors were more common in breast MRI reports (35% of ASR and 7% of conventional reports), the lowest error rates occurring in reports of interventional procedures (13% of ASR and 4% of conventional reports) and mammography reports (15% of ASR and no conventional reports) (p < 0.01). The error rates did not differ substantially between reports generated by staff radiologists and trainees or between reports generated by speakers who spoke English as their first language and those whose native language was not English. After adjustment for academic rank, native language, and imaging modality, reports generated with ASR were 8 times as likely as conventional dictation transcription reports to contain major errors (p < 0.01).
  
  
  CONCLUSIONS
  Reports generated with ASR are associated with higher error rates than reports generated with conventional dictation transcription. The imaging modality used is a predictor of the occurrence of reporting errors. Conversely, native language and academic rank of the speaker do not have a significant influence on error rate.
authors.affiliation: Research and Development Division, Joint Department of Medical Imaging, Mount Sinai Hospital, University Health Network, Women's College Hospital, Toronto, ON, Canada.
authors.forename: Sarah
authors.initials: S
authors.lastname: Basma
authors.forename: Bridgette
authors.initials: B
authors.lastname: Lord
authors.forename: Lindsay M
authors.initials: LM
authors.lastname: Jacks
authors.forename: Mohamed
authors.initials: M
authors.lastname: Rizk
authors.forename: Anabel M
authors.initials: AM
authors.lastname: Scaranelo
mesh_terms: D001943:Breast Neoplasms / Q000175:diagnosis*; D005260:Female; D006801:Humans; D016015:Logistic Models; D008499:Medical Records / Q000592:standards*; D011872:Radiology Department, Hospital / Q000706:statistics & numerical data*; D011873:Radiology Information Systems / Q000592:standards / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D049250:Speech Recognition Software / Q000592:standards*