Search

Background A clinical diagnostic support system (CDSS) can support medical students and physicians in providing evidence-based care. In this study, we investigate diagnostic accuracy based on the history of present illness between groups of medical students using a CDSS, Google, and neither (control). Further, the degree of diagnostic accuracy of medical students using a CDSS is compared with that of residents using neither a CDSS nor Google. Methods This study is a randomized educational trial. The participants comprised 64 medical students and 13 residents who rotated in the Department of General Medicine at Chiba University Hospital from May to December 2020. The medical students were randomly divided into the CDSS group (n = 22), Google group (n = 22), and control group (n = 20). Participants were asked to provide the three most likely diagnoses for 20 cases, mainly a history of a present illness (10 common and 10 emergent diseases). Each correct diagnosis was awarded 1 point (maximum 20 points). The mean scores of the three medical student groups were compared using a one-way analysis of variance. Furthermore, the mean scores of the CDSS, Google, and residents’ (without CDSS or Google) groups were compared. Results The mean scores of the CDSS (12.0 ± 1.3) and Google (11.9 ± 1.1) groups were significantly higher than those of the control group (9.5 ± 1.7; p = 0.02 and p = 0.03, respectively). The residents’ group’s mean score (14.7 ± 1.4) was higher than the mean scores of the CDSS and Google groups (p = 0.01). Regarding common disease cases, the mean scores were 7.4 ± 0.7, 7.1 ± 0.7, and 8.2 ± 0.7 for the CDSS, Google, and residents’ groups, respectively. There were no significant differences in mean scores (p = 0.1). Conclusions Medical students who used the CDSS and Google were able to list differential diagnoses more accurately than those using neither. Furthermore, they could make the same level of differential diagnoses as residents in the context of common diseases. Trial registration This study was retrospectively registered with the University Hospital Medical Information Network Clinical Trials Registry on 24/12/2020 (unique trial number: UMIN000042831).

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 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 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).

There have been some studies of common primary care diseases in Japan, but no reports on which diseases it is difficult for general physicians to diagnose in daily practice. In this study, we identified diseases that provided a diagnostic challenge for Japanese general physicians in daily practice. The subjects were new undiagnosed patients referred to the General Outpatient Department of Chiba University Hospital during the one-year period from January 2008. We performed a retrospective chart review to identify the referring doctor, patient demographics, the duration of symptoms, the final diagnosis, and the outcome. Final diagnoses were classified according to the International Classification of Primary Care Second Edition (ICPC-2). In addition, the differences between referrals from general physicians and those from other physicians were assessed. Fisher’s exact test and the Bonferroni-Holm correction were used for statistical analysis. A total of 169 patients were referred by general physicians and 239 patients were referred by other physicians. The most common ICPC-2 diagnosis was “General & Unspecified” conditions (35 patients, 20.7%), followed by “Psychological” conditions (31 patients, 18.3%) and “Musculoskeletal” conditions (21 patients, 12.4%). No significant differences of the ICPC-2 category for the final diagnosis and each diagnosis were found between patients referred by general physicians and those referred by other physicians. The hospitalization rate was lower for patients referred by general physicians than for patients referred by other physicians (4 patients, 2.4% vs. 24 patients, 10.0%) (P = 0.002). Japanese general physicians found difficulty in diagnosing “Psychological” conditions, “Musculoskeletal” conditions, variations within the normal range, and viral infections that required diagnosis by exclusion. Because most of the patients referred by general physicians had mild conditions, further education at outpatient departments and clinics is required to improve diagnostic performance. Additionally, it is important to increase the gatekeeper role of general physicians and further development of the medical system by the government to distinguish the functions of clinics and hospitals is expected.