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Do clinical interview transcripts generated by speech recognition software improve clinical reasoning performance in mock patient encounters? A prospective observational study.
Shikino, Kiyoshi; Tsukamoto, Tomoko; Noda, Kazutaka; Ohira, Yoshiyuki; Yokokawa, Daiki; Hirose, Yuta; Sato, Eri; Mito, Tsutomu; Ota, Takahiro; Katsuyama, Yota; Uehara, Takanori; Ikusaka, Masatomi.
Afiliação
  • Shikino K; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan. kshikino@gmail.com.
  • Tsukamoto T; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Noda K; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Ohira Y; Division of General Internal Medicine, Department of Internal Medicine, St. Marianna University School of Medicine Hospital, Kawasaki, Japan.
  • Yokokawa D; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Hirose Y; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Sato E; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Mito T; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Ota T; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Katsuyama Y; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Uehara T; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
  • Ikusaka M; Department of General Medicine, Chiba University Hospital, 1-8-1, Inohana, Chuo-Ku, Chiba City, Chiba Pref, Japan.
BMC Med Educ ; 23(1): 272, 2023 Apr 21.
Article em En | MEDLINE | ID: mdl-37085837
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 group1st 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).
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estudantes de Medicina / Avaliação Educacional Tipo de estudo: Observational_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Estudantes de Medicina / Avaliação Educacional Tipo de estudo: Observational_studies / Qualitative_research Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article