No abstract

Objective Difficult patient encounters (DPEs) are defined as encounters with patients causing strong negative feelings in physicians. In primary care settings, DPEs account for approximately 15% of visits among outpatients. To our knowledge, this is the first epidemiological study of DPEs in Japan. Methods We conducted a survey of 8 physicians (5.0±2 years of clinical experience) who examined firstvisit patients " 15 years old with clinical symptoms at the Department of General Medicine in Chiba University Hospital and 4 community hospitals over a 2-month period since December 2015. Materials We evaluated 10-Item Difficult Doctor-Patient Relationship Questionnaire (DDPRQ-10) scores (DPE " 31 points; non-DPE ! 30 points) and patient age, sex, and presence of psychological or social problems. ResultsThe valid response rate was 98.9% (94/95) and 98.4% (189/192) in the university and community hospitals, respectively. The percentage of DPEs was 39.8% (37/93) and 15.0% (26/173) in the university and community hospitals, respectively; the percentage of DPEs was significantly higher at the university hospital than at the community hospitals (p<0.001). The proportion of patients with psychosocial problems was significantly higher in the DPE group than in the non-DPE group (93.7% vs. 40.4%, p<0.001). Conclusion Our findings were similar to those reported in primary care settings in other countries in community hospital outpatient and general internal medicine departments, where patients are mostly non-referrals, although the values were higher in university hospital general medicine departments, where patients were mostly referrals. Patients involved in DPEs have a high rate of psychological and social problems.

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).

A 60-year-old man was referred to us with high levels of aspartate aminotransferase and lactate dehydrogenase (LDH). He did not complain of any symptoms; however, he had been diagnosed with lumbar disc herniation, even though his back pain improved only to half of its previous level with pregabalin. Thus, we asked about the red flag of back pain and confirmed that he had involuntary body weight loss, which led us to diagnose truly non-secretory multiple myeloma, a variant of multiple myeloma that is associated with M-protein negativity and a normal serum free light chain level.