Literature DB >> 26635322

Syntactic and semantic errors in radiology reports associated with speech recognition software.

Michael D Ringler1, Brian C Goss1, Brian J Bartholmai1.   

Abstract

Speech recognition software can increase the frequency of errors in radiology reports, which may affect patient care. We retrieved 213,977 speech recognition software-generated reports from 147 different radiologists and proofread them for errors. Errors were classified as "material" if they were believed to alter interpretation of the report. "Immaterial" errors were subclassified as intrusion/omission or spelling errors. The proportion of errors and error type were compared among individual radiologists, imaging subspecialty, and time periods. In all, 20,759 reports (9.7%) contained errors, of which 3992 (1.9%) were material errors. Among immaterial errors, spelling errors were more common than intrusion/omission errors ( p < .001). Proportion of errors and fraction of material errors varied significantly among radiologists and between imaging subspecialties ( p < .001). Errors were more common in cross-sectional reports, reports reinterpreting results of outside examinations, and procedural studies (all p < .001). Error rate decreased over time ( p < .001), which suggests that a quality control program with regular feedback may reduce errors.

Entities:  

Keywords:  PowerScribe; quality control; radiology report; report errors; speech recognition

Mesh:

Year:  2016        PMID: 26635322     DOI: 10.1177/1460458215613614

Source DB:  PubMed          Journal:  Health Informatics J        ISSN: 1460-4582            Impact factor:   2.681


  5 in total

1.  Asynchronous Speech Recognition Affects Physician Editing of Notes.

Authors:  Kevin J Lybarger; Mari Ostendorf; Eve Riskin; Thomas H Payne; Andrew A White; Meliha Yetisgen
Journal:  Appl Clin Inform       Date:  2018-10-17       Impact factor: 2.342

2.  Automated Misspelling Detection and Correction in Persian Clinical Text.

Authors:  Azita Yazdani; Marjan Ghazisaeedi; Nasrin Ahmadinejad; Masoumeh Giti; Habibe Amjadi; Azin Nahvijou
Journal:  J Digit Imaging       Date:  2020-06       Impact factor: 4.056

3.  Application of a Domain-specific BERT for Detection of Speech Recognition Errors in Radiology Reports.

Authors:  Gunvant R Chaudhari; Tengxiao Liu; Timothy L Chen; Gabby B Joseph; Maya Vella; Yoo Jin Lee; Thienkhai H Vu; Youngho Seo; Andreas M Rauschecker; Charles E McCulloch; Jae Ho Sohn
Journal:  Radiol Artif Intell       Date:  2022-05-25

4.  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

5.  Revealing the most common reporting errors through data mining of the report proofreading process.

Authors:  Jan Vosshenrich; Ivan Nesic; Joshy Cyriac; Daniel T Boll; Elmar M Merkle; Tobias Heye
Journal:  Eur Radiol       Date:  2020-09-30       Impact factor: 5.315

  5 in total

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