Literature DB >> 21940580

Error rates in breast imaging reports: comparison of automatic speech recognition and dictation transcription.

Sarah Basma1, Bridgette Lord, Lindsay M Jacks, Mohamed Rizk, Anabel M Scaranelo.   

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.
MATERIALS AND 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).
CONCLUSION: 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.

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Mesh:

Year:  2011        PMID: 21940580     DOI: 10.2214/AJR.11.6691

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  10 in total

1.  Improving Radiology Report Quality by Rapidly Notifying Radiologist of Report Errors.

Authors:  Matthew J Minn; Arash R Zandieh; Ross W Filice
Journal:  J Digit Imaging       Date:  2015-08       Impact factor: 4.056

Review 2.  Electronic Health Record Interactions through Voice: A Review.

Authors:  Yaa A Kumah-Crystal; Claude J Pirtle; Harrison M Whyte; Edward S Goode; Shilo H Anders; Christoph U Lehmann
Journal:  Appl Clin Inform       Date:  2018-07-18       Impact factor: 2.342

3.  Incidence of speech recognition errors in the emergency department.

Authors:  Foster R Goss; Li Zhou; Scott G Weiner
Journal:  Int J Med Inform       Date:  2016-05-26       Impact factor: 4.046

Review 4.  Risks and benefits of speech recognition for clinical documentation: a systematic review.

Authors:  Tobias Hodgson; Enrico Coiera
Journal:  J Am Med Inform Assoc       Date:  2015-11-17       Impact factor: 4.497

5.  Detecting insertion, substitution, and deletion errors in radiology reports using neural sequence-to-sequence models.

Authors:  John Zech; Jessica Forde; Joseph J Titano; Deepak Kaji; Anthony Costa; Eric Karl Oermann
Journal:  Ann Transl Med       Date:  2019-06

6.  The accuracy of radiology speech recognition reports in a multilingual South African teaching hospital.

Authors:  Jacqueline du Toit; Retha Hattingh; Richard Pitcher
Journal:  BMC Med Imaging       Date:  2015-03-04       Impact factor: 1.930

7.  Evaluation and comparison of errors on nursing notes created by online and offline speech recognition technology and handwritten: an interventional study.

Authors:  Sahar Peivandi; Leila Ahmadian; Jamileh Farokhzadian; Yunes Jahani
Journal:  BMC Med Inform Decis Mak       Date:  2022-04-08       Impact factor: 2.796

8.  Accuracy of Cloud-Based Speech Recognition Open Application Programming Interface for Medical Terms of Korean.

Authors:  Seung-Hwa Lee; Jungchan Park; Kwangmo Yang; Jeongwon Min; Jinwook Choi
Journal:  J Korean Med Sci       Date:  2022-05-09       Impact factor: 2.153

9.  Retrospective Analysis of Clinical Performance of an Estonian Speech Recognition System for Radiology: Effects of Different Acoustic and Language Models.

Authors:  A Paats; T Alumäe; E Meister; I Fridolin
Journal:  J Digit Imaging       Date:  2018-10       Impact factor: 4.056

10.  Analysis of Errors in Dictated Clinical Documents Assisted by Speech Recognition Software and Professional Transcriptionists.

Authors:  Li Zhou; Suzanne V Blackley; Leigh Kowalski; Raymond Doan; Warren W Acker; Adam B Landman; Evgeni Kontrient; David Mack; Marie Meteer; David W Bates; Foster R Goss
Journal:  JAMA Netw Open       Date:  2018-07-06
  10 in total

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