du Toit Jacqueline, Hattingh Retha, Pitcher Richard
Department of Diagnostic Radiology, Tygerberg Academic Hospital, Stellenbosch University, Francie van Zyl Avenue, Cape Town, 7700, South Africa.
BMC Med Imaging. 2015 Mar 4;15:8. doi: 10.1186/s12880-015-0048-1.
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 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.
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.
语音识别（SR）技术，即将口语转换为数字文本的过程，自1981年以来已用于放射学报告。最初预计SR将主导放射学报告，据称准确率高达99%，周转时间缩短且成本大幅节省。然而，这些期望尚未实现。现有有限数据表明，SR报告的不准确程度明显高于传统听写转录（DT）报告，且总成本更高。然而，关于此类错误的临床意义的研究很少，对于报告者资历对错误产生的影响，或系统熟悉程度对降低错误率的影响也知之甚少。此外，分别以英语为第一语言和第二语言的用户在SR准确性方面的研究结果相互矛盾。
本研究的目的是在资源有限的环境中比较SR报告和DT报告的准确性。从医院的PACS中检索了2010年3月生成的前300份SR报告和前300份DT报告，并由一名观察者进行审查。识别文本错误，然后根据其对患者管理的潜在影响将其分类为具有临床意义或无临床意义。此外，在整整4年后进行了随访分析。
在最初分析的300份SR报告中，25.6%包含错误，其中9.6%具有临床意义。只有9.3%的DT报告包含错误，2.3%具有潜在临床影响。SR和DT错误率的总体差异以及“具有临床意义”的错误率差异（9.6%对2.3%）均具有统计学意义。在随访研究中，总体SR错误率惊人地相似，为24.3%，其中6%具有临床意义。以英语为第二语言的放射科医生更有可能生成包含错误的报告，但资历水平无关紧要。
SR技术持续增加了泰格堡医院（TBH）放射学报告中的不准确之处，从而可能损害患者护理。意识到SR报告中错误率的增加，特别是在那些使用第二语言进行转录的报告中，对于在多语言医疗环境中有效实施SR很重要。
