These results suggest that these models might quantify contributions of specific climate conditions and other seasonal factors on the number of emergency visits per night for childhood asthma attack in Tokyo, Japan.

A 67-year-old man was admitted due to weakness, coughing, shortness of breath and fever. He had decreased breath sounds in the left lung and muscle weakness in the lower and upper extremities. Chest imaging showed a mass in the left lung, and a biopsy revealed small cell lung cancer. The nerve conduction velocity was decreased, and anti-GM1 IgG antibodies were positive. The patient showed a temporary neurologic recovery following the administration of cancer chemotherapy, although he eventually died of progression of lung cancer. As a result of the almost simultaneous symptomatic development of lung cancer and Guillain-Barré syndrome, this case may be considered to involve a paraneoplastic neurologic syndrome.

ObjectivesThere is lack of evidence for the association between multimorbidity and diagnostic errors. Information on diagnostic errors from patients’ perspectives is crucial to improve the diagnostic process. In this study, we aimed to investigate patient-reported diagnostic errors and to examine the relationship between multimorbidity and patient-reported diagnostic errors in the primary care setting.DesignMulticentre cross-sectional study.SettingA primary care practice-based research network in Japan (25 primary care facilities).ParticipantsAdult outpatients filled out a standardised questionnaire.Primary outcome measurePatient-reported diagnostic errors.ResultsData collected from 1474 primary care outpatients were analysed. The number of participants who reported diagnostic errors was 57 (3.9%). Most of the missed diagnoses were common conditions in primary care, such as cancer, dermatitis and hypertension. After adjustment for possible confounders and clustering within facilities, multimorbidity was positively associated with patient-reported diagnostic errors (adjusted OR=1.83, 95% CI 1.01 to 3.31). The results of the sensitivity analysis were consistent with those of the primary analysis.ConclusionsThe present study showed a lower proportion of patients reporting experiences of diagnostic errors in primary care than those reported in previous studies in other countries. However, patients with multimorbidity are more likely to report diagnostic errors in primary care; thus, further research is necessary to improve the diagnostic process for patients with multimorbidity.

Lower gastrointestinal perforation is rare and challenging to diagnose in patients presenting with an acute abdomen. However, no study has examined the frequency and associated factors of diagnostic errors related to lower gastrointestinal perforation. This large-scale multicenter retrospective study investigated the frequency of diagnostic errors and identified the associated factors. Factors at the level of the patient, symptoms, situation, and physician were included in the analysis. Data were collected from nine institutions, between January 1, 2015 and December 31, 2019. Timely diagnosis was defined as diagnosis at the first visit in computed tomography (CT)-capable facilities or referral to an appropriate medical institution immediately following the first visit to a non-CT-capable facility. Cases not meeting this definition were defined as diagnostic errors that resulted in delayed diagnosis. Of the 439 cases of lower gastrointestinal perforation identified, delayed diagnosis occurred in 138 cases (31.4%). Multivariate logistic regression analysis revealed a significant association between examination by a non-generalist and delayed diagnosis. Other factors showing a tendency with delayed diagnosis included presence of fever, absence of abdominal tenderness, and unavailability of urgent radiology reports. Initial misdiagnoses were mainly gastroenteritis, constipation, and small bowel obstruction. In conclusion, diagnostic errors occurred in about one-third of patients with a lower gastrointestinal perforation.

Artificial intelligence (AI) has made great contributions to the healthcare industry. However, its effect on medical diagnosis has not been well explored. Here, we examined a trial comparing the thinking process between a computer and a master in diagnosis at a clinical conference in Japan, with a focus on general diagnosis. Consequently, not only was AI unable to exhibit its thinking process, it also failed to include the final diagnosis. The following issues were highlighted: (1) input information to AI could not be weighted in order of importance for diagnosis; (2) AI could not deal with comorbidities (see Hickam’s dictum); (3) AI was unable to consider the timeline of the illness (depending on the tool); (4) AI was unable to consider patient context; (5) AI could not obtain input information by themselves. This comparison of the thinking process uncovered a future perspective on the use of diagnostic support tools.

Objectives Despite existing patient safety measures, both outside and inside hospitals, barriers to patient safety prevail. We aimed to identify the current contributory factors to patient safety in Japan. Methods This qualitative study included nine expert Japanese health care providers working both inside and outside hospitals. These participants, who included six physicians, one nurse, one pharmacist, and one physical therapist, work across a broad spectrum in government policy and public health, academia, and safety management. Root cause analysis using the online Kawakita Jiro method (KJ method or affinity diagram) was conducted. We labeled and summarized the classification in a fishbone diagram to elucidate barriers to patient safety in Japan. Results We identified specific factors in six main groups: the hospital system, education, law and policy, culture and society, patient centricity, and multidisciplinary cooperation. Quality of care, patient engagement, and shortage of patient safety specialists were crucial factors for multiple groups. Conclusions This study clarifies components of patient safety in Japan and provides basic data for promoting comprehensive patient safety in the future. Periodic root cause analysis of comprehensive patient safety issues can help develop strategies to promote patient safety at both the hospital and national levels.

Diagnostic errors are a serious problem in healthcare. The diagnostic process is highly susceptible to cognitive bias and the current COVID-19 pandemic may cause normally accurate healthcare workers to make incorrect decisions. We report a case of aseptic meningitis that required five healthcare visits before it was correctly diagnosed. This case highlights the risk of anchoring bias and the importance of carefully assessing diagnostic processes during the COVID-19 pandemic.

The view of Tokyo GIM Conference.