Abstract

BackgroundSpeech 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 errors, however, 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.MethodsThe 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.ResultsOf 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.ConclusionSR 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.

Highlights

  • Speech recognition (SR) technology, the process whereby spoken words are converted to digital text, has been used in radiology reporting since 1981

  • Effective communication plays a pivotal role in modern radiological practice, with the generation of accurate reports being integral to optimal patient care [1]

  • Speech recognition (SR) technology, the process whereby the spoken word is converted to digital text, has been used in radiology reporting since 1981 [3]

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Summary

Introduction

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. There has been little work on the clinical significance of such errors, 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. Speech recognition (SR) technology, the process whereby the spoken word is converted to digital text, has been used in radiology reporting since 1981 [3]. With on-going software development, the first continuous speech programmes evolved in 1994 and by 1999, state of the art systems were claiming up to 99% accuracy [4], reduced report turnaround times [5], and significant cost savings [6,7,8,9]. It appeared that SR was destined to dominate radiology reporting

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