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语音识别软件生成的临床访谈记录是否能提高模拟患者就诊中的临床推理表现?一项前瞻性观察研究。

Do clinical interview transcripts generated by speech recognition software improve clinical reasoning performance in mock patient encounters? A prospective observational study.

机构信息

Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.

Division of General Internal Medicine, Department of Internal Medicine, St. Marianna University School of Medicine Hospital, Kawasaki, Japan.

出版信息

BMC Med Educ. 2023 Apr 21;23(1):272. doi: 10.1186/s12909-023-04246-9.

Abstract

BACKGROUND

To investigate whether speech recognition software for generating interview transcripts can provide more specific and precise feedback for evaluating medical interviews.

METHODS

The effects of the two feedback methods on student performance in medical interviews were compared using a prospective observational trial. Seventy-nine medical students in a clinical clerkship were assigned to receive either speech-recognition feedback (n = 39; SRS feedback group) or voice-recording feedback (n = 40; IC recorder feedback group). All students' medical interviewing skills during mock patient encounters were assessed twice, first using a mini-clinical evaluation exercise (mini-CEX) and then a checklist. Medical students then made the most appropriate diagnoses based on medical interviews. The diagnostic accuracy, mini-CEX, and checklist scores of the two groups were compared.

RESULTS

According to the study results, the mean diagnostic accuracy rate (SRS feedback group:1st mock 51.3%, 2nd mock 89.7%; IC recorder feedback group, 57.5%-67.5%; F(1, 77) = 4.0; p = 0.049), mini-CEX scores for overall clinical competence (SRS feedback group: 1st mock 5.2 ± 1.1, 2nd mock 7.4 ± 0.9; IC recorder feedback group: 1st mock 5.6 ± 1.4, 2nd mock 6.1 ± 1.2; F(1, 77) = 35.7; p < 0.001), and checklist scores for clinical performance (SRS feedback group: 1st mock 12.2 ± 2.4, 2nd mock 16.1 ± 1.7; IC recorder feedback group: 1st mock 13.1 ± 2.5, 2nd mock 13.8 ± 2.6; F(1, 77) = 26.1; p < 0.001) were higher with speech recognition-based feedback.

CONCLUSIONS

Speech-recognition-based feedback leads to higher diagnostic accuracy rates and higher mini-CEX and checklist scores.

TRIAL REGISTRATION

This study was registered in the Japan Registry of Clinical Trials on June 14, 2022. Due to our misunderstanding of the trial registration requirements, we registered the trial retrospectively. This study was registered in the Japan Registry of Clinical Trials on 7/7/2022 (Clinical trial registration number: jRCT1030220188).

摘要

背景

为了探究语音识别软件在生成访谈记录方面是否能为评估医学访谈提供更具体、更准确的反馈。

方法

采用前瞻性观察性试验比较了两种反馈方法对医学生医学访谈表现的影响。79 名在临床科室实习的医学生被分配接受语音识别反馈(n=39;SRS 反馈组)或录音反馈(n=40;IC 记录器反馈组)。两次使用迷你临床评估练习(mini-CEX)和检查表评估所有学生在模拟患者就诊时的医学访谈技巧。然后,医学生根据医学访谈做出最恰当的诊断。比较了两组的诊断准确性、mini-CEX 和检查表评分。

结果

根据研究结果,平均诊断准确率(SRS 反馈组:第 1 次模拟 51.3%,第 2 次模拟 89.7%;IC 记录器反馈组,57.5%-67.5%;F(1,77)=4.0;p=0.049)、整体临床能力的 mini-CEX 评分(SRS 反馈组:第 1 次模拟 5.2±1.1,第 2 次模拟 7.4±0.9;IC 记录器反馈组:第 1 次模拟 5.6±1.4,第 2 次模拟 6.1±1.2;F(1,77)=35.7;p<0.001)和临床表现检查表评分(SRS 反馈组:第 1 次模拟 12.2±2.4,第 2 次模拟 16.1±1.7;IC 记录器反馈组:第 1 次模拟 13.1±2.5,第 2 次模拟 13.8±2.6;F(1,77)=26.1;p<0.001)在基于语音识别的反馈时更高。

结论

基于语音识别的反馈可提高诊断准确率和 mini-CEX 及检查表评分。

试验注册

本研究于 2022 年 6 月 14 日在日本临床试验注册处注册。由于我们对试验注册要求的误解,我们进行了回顾性注册。本研究于 2022 年 7 月 7 日在日本临床试验注册处注册(临床试验注册号:jRCT1030220188)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/690f/10120240/49480395d8d3/12909_2023_4246_Fig1_HTML.jpg

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