The accuracy of radiology speech recognition reports in a multilingual South African teaching hospital
dc.contributor.author | Du Toit, Jacqueline | |
dc.contributor.author | Hattingh, Retha | |
dc.contributor.author | Pitcher, Richard | |
dc.contributor.other | Medical Imaging and Clinical Oncology: Radiodiagnosis | en_ZA |
dc.date.accessioned | 2015-10-15T09:20:56Z | |
dc.date.available | 2015-10-15T09:20:56Z | |
dc.date.issued | 2015-03 | |
dc.description | Publication of this article was funded by the Stellenbosch University Open Access Fund. | |
dc.description.abstract | Background Speech recognition (SR) technology, the process whereby spoken words are converted to digital text, has been used in radiology reporting since 1981. It was initially anticipated that SR would dominate radiology reporting, with claims of up to 99% accuracy, reduced turnaround times and significant cost savings. However, expectations have not yet been realised. The limited data available suggest SR reports have significantly higher levels of inaccuracy than traditional dictation transcription (DT) reports, as well as incurring greater aggregate costs. There has been little work on the clinical significance of such errorshowever, and little is known of the impact of reporter seniority on the generation of errors, or the influence of system familiarity on reducing error rates. Furthermore, there have been conflicting findings on the accuracy of SR amongst users with English as first- and second-language respectively. Methods The aim of the study was to compare the accuracy of SR and DT reports in a resource-limited setting. The first 300 SR and the first 300 DT reports generated during March 2010 were retrieved from the hospital’s PACS, and reviewed by a single observer. Text errors were identified, and then classified as either clinically significant or insignificant based on their potential impact on patient management. In addition, a follow-up analysis was conducted exactly 4 years later. Results Of the original 300 SR reports analysed, 25.6% contained errors, with 9.6% being clinically significant. Only 9.3% of the DT reports contained errors, 2.3% having potential clinical impact. Both the overall difference in SR and DT error rates, and the difference in ‘clinically significant’ error rates (9.6% vs. 2.3%) were statistically significant. In the follow-up study, the overall SR error rate was strikingly similar at 24.3%, 6% being clinically significant. Radiologists with second-language English were more likely to generate reports containing errors, but level of seniority had no bearing. Conclusion SR technology consistently increased inaccuracies in Tygerberg Hospital (TBH) radiology reports, thereby potentially compromising patient care. Awareness of increased error rates in SR reports, particularly amongst those transcribing in a second-language, is important for effective implementation of SR in a multilingual healthcare environment. | |
dc.description.uri | http://www.biomedcentral.com/content/pdf/s12880-015-0048-1.pdf | en_ZA |
dc.description.version | Background Speech recognition (SR) technology, the process whereby spoken words are converted to digital text, has been used in radiology reporting since 1981. It was initially anticipated that SR would dominate radiology reporting, with claims of up to 99% accuracy, reduced turnaround times and significant cost savings. However, expectations have not yet been realised. The limited data available suggest SR reports have significantly higher levels of inaccuracy than traditional dictation transcription (DT) reports, as well as incurring greater aggregate costs. There has been little work on the clinical significance of such errorshowever, and little is known of the impact of reporter seniority on the generation of errors, or the influence of system familiarity on reducing error rates. Furthermore, there have been conflicting findings on the accuracy of SR amongst users with English as first- and second-language respectively. Methods The aim of the study was to compare the accuracy of SR and DT reports in a resource-limited setting. The first 300 SR and the first 300 DT reports generated during March 2010 were retrieved from the hospital’s PACS, and reviewed by a single observer. Text errors were identified, and then classified as either clinically significant or insignificant based on their potential impact on patient management. In addition, a follow-up analysis was conducted exactly 4 years later. Results Of the original 300 SR reports analysed, 25.6% contained errors, with 9.6% being clinically significant. Only 9.3% of the DT reports contained errors, 2.3% having potential clinical impact. Both the overall difference in SR and DT error rates, and the difference in ‘clinically significant’ error rates (9.6% vs. 2.3%) were statistically significant. In the follow-up study, the overall SR error rate was strikingly similar at 24.3%, 6% being clinically significant. Radiologists with second-language English were more likely to generate reports containing errors, but level of seniority had no bearing. Conclusion SR technology consistently increased inaccuracies in Tygerberg Hospital (TBH) radiology reports, thereby potentially compromising patient care. Awareness of increased error rates in SR reports, particularly amongst those transcribing in a second-language, is important for effective implementation of SR in a multilingual healthcare environment. | en_ZA |
dc.identifier.citation | Du Toit, J., Hattingh, R., & Pitcher, R. 2015. The accuracy of radiology speech recognition reports in a multilingual South African teaching hospital. BMC Medical Imaging, 15(8), doi.org/10.1186/s12880-015-0048-1. | en_ZA |
dc.identifier.uri | http://hdl.handle.net/10019.1/97568 | |
dc.publisher | Springer Verlag | en_ZA |
dc.subject | Speech recognition | en_ZA |
dc.subject | Transcriptionist | en_ZA |
dc.subject | Error rate | en_ZA |
dc.subject | Radiology reporting | en_ZA |
dc.title | The accuracy of radiology speech recognition reports in a multilingual South African teaching hospital | en_ZA |
dc.type | Article | en_ZA |