HUS Medical Imaging Center, Helsinki University Central Hospital, PO Box 750, 00029, Helsinki, Finland,
J Digit Imaging. 2013 Dec;26(6):1020-4. doi: 10.1007/s10278-013-9614-7.
Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR's dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users' reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support.
语音识别 (SR) 通过缩短报告周转时间来加快患者护理流程。然而,人们对放射科医生需要进行长时间的培训以及增加秘书负担表示担忧。我们评估了具有多年 SR 经验的放射科医生和新接触 SR 的放射科医生必须进行多少校对,以及新用户需要多长时间才能达到有经验用户的水平。我们研究了来自 154 名放射科医生的 250 万份报告的语音识别日志记录,经过仔细排除后,定义了一组 11 名有经验的放射科医生和 71 名新接触 SR 的放射科医生(分别为 24833 份和 122093 份报告)。我们分析了语音文件和报告的长度、基于字符的错误率以及语音识别字典中不包含的单词。有经验的放射科医生对每份报告纠正了 6 个字符,而新用户则纠正了 11 个字符。一些用户的学习曲线非常不利,错误率没有像预期的那样下降。新用户的报告更长,而有经验用户的数据表明,他们的报告最初长度相等,但在几年内缩短了。对于大多数放射科医生来说,只需要对口述报告进行少量的修改。虽然新用户很快就适应了语音识别,但有一部分用户从一开始就表现优于有经验的用户,识别出使用语音识别存在困难的用户将有助于解决问题和提供支持。