Literature DB >> 20976612

Non-clinical errors using voice recognition dictation software for radiology reports: a retrospective audit.

Chian A Chang1, Rodney Strahan, Damien Jolley.   

Abstract

The purpose of this study is to ascertain the error rates of using a voice recognition (VR) dictation system. We compared our results with several other articles and discussed the pros and cons of using such a system. The study was performed at the Southern Health Department of Diagnostic Imaging, Melbourne, Victoria using the GE RIS with Powerscribe 3.5 VR system. Fifty random finalized reports from 19 radiologists obtained between June 2008 and November 2008 were scrutinized for errors in six categories namely, wrong word substitution, deletion, punctuation, other, and nonsense phrase. Reports were also divided into two categories: computer radiography (CR = plain film) and non-CR (ultrasound, computed tomography, magnetic resonance imaging, nuclear medicine, and angiographic examinations). Errors were divided into two categories, significant but not likely to alter patient management and very significant with the meaning of the report affected, thus potentially affecting patient management (nonsense phrase). Three hundred seventy-nine finalized CR reports and 631 non-CR finalized reports were examined. Eleven percent of the reports in the CR group had errors. Two percent of these reports contained nonsense phrases. Thirty-six percent of the reports in the non-CR group had errors and out of these, 5% contained nonsense phrases. VR dictation system is like a double-edged sword. Whilst there are many benefits, there are also many pitfalls. We hope that raising the awareness of the error rates will help in our efforts to reduce error rates and strike a balance between quality and speed of reports generated.

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Mesh:

Year:  2011        PMID: 20976612      PMCID: PMC3138931          DOI: 10.1007/s10278-010-9344-z

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  4 in total

1.  Voice recognition dictation: radiologist as transcriptionist.

Authors:  John A Pezzullo; Glenn A Tung; Jeffrey M Rogg; Lawrence M Davis; Jeffrey M Brody; William W Mayo-Smith
Journal:  J Digit Imaging       Date:  2008-12       Impact factor: 4.056

2.  Frequency and spectrum of errors in final radiology reports generated with automatic speech recognition technology.

Authors:  Leslie E Quint; Douglas J Quint; James D Myles
Journal:  J Am Coll Radiol       Date:  2008-12       Impact factor: 5.532

3.  The effect of voice recognition software on comparative error rates in radiology reports.

Authors:  S McGurk; K Brauer; T V Macfarlane; K A Duncan
Journal:  Br J Radiol       Date:  2008-07-15       Impact factor: 3.039

4.  The pros and cons of implementing PACS and speech recognition systems.

Authors:  D B Hayt; S Alexander
Journal:  J Digit Imaging       Date:  2001-09       Impact factor: 4.056

  4 in total
  10 in total

1.  Learning curve of speech recognition.

Authors:  Tomi A Kauppinen; Johanna Kaipio; Mika P Koivikko
Journal:  J Digit Imaging       Date:  2013-12       Impact factor: 4.056

2.  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

3.  Detecting Technical Image Quality in Radiology Reports.

Authors:  Thusitha Mabotuwana; Varun S Bhandarkar; Christopher S Hall; Martin L Gunn
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

4.  Frequency and analysis of non-clinical errors made in radiology reports using the National Integrated Medical Imaging System voice recognition dictation software.

Authors:  R E Motyer; S Liddy; W C Torreggiani; O Buckley
Journal:  Ir J Med Sci       Date:  2016-10-01       Impact factor: 1.568

Review 5.  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

Review 6.  Medical errors, medical negligence and defensive medicine: A narrative review.

Authors:  Ivan Dieb Miziara; Carmen Silvia Molleis Galego Miziara
Journal:  Clinics (Sao Paulo)       Date:  2022-05-28       Impact factor: 2.898

Review 7.  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

8.  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

Review 9.  Clinical errors and medical negligence.

Authors:  Femi Oyebode
Journal:  Med Princ Pract       Date:  2013-01-18       Impact factor: 1.927

10.  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 in total

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