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

Overview of attention for article published in BMC Medical Imaging, March 2015
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2 tweeters

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9 Dimensions

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40 Mendeley
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Title
The accuracy of radiology speech recognition reports in a multilingual South African teaching hospital
Published in
BMC Medical Imaging, March 2015
DOI 10.1186/s12880-015-0048-1
Pubmed ID
Authors

Jacqueline du Toit, Retha Hattingh, Richard Pitcher

Abstract

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. 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. 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. 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.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 20%
Researcher 4 10%
Student > Bachelor 4 10%
Student > Doctoral Student 3 8%
Student > Ph. D. Student 3 8%
Other 6 15%
Unknown 12 30%
Readers by discipline Count As %
Medicine and Dentistry 9 23%
Computer Science 5 13%
Psychology 3 8%
Nursing and Health Professions 2 5%
Engineering 2 5%
Other 5 13%
Unknown 14 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 March 2015.
All research outputs
#2,312,239
of 5,033,220 outputs
Outputs from BMC Medical Imaging
#87
of 184 outputs
Outputs of similar age
#69,791
of 149,474 outputs
Outputs of similar age from BMC Medical Imaging
#5
of 10 outputs
Altmetric has tracked 5,033,220 research outputs across all sources so far. This one has received more attention than most of these and is in the 51st percentile.
So far Altmetric has tracked 184 research outputs from this source. They receive a mean Attention Score of 2.3. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 149,474 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.