ObjectivesWe aimed to investigate the impact of the first and second waves of the COVID-19 pandemic on healthcare service use by non-COVID-19 patients.DesignRetrospective cohort study.SettingHospital-based claims database from anonymised hospitals in Japan.ParticipantsPatients (n=785 495) who visited and/or were hospitalised in 26 anonymised hospitals in Japan between January 2017 and November 2020.Outcome measuresWe compared changes in the monthly number of hospitalisations (overall or by diagnosis), outpatient visits, endoscopic fibrescopies (EFs), rehabilitations, outpatient chemotherapy treatments, maintenance haemodialysis treatments and outpatient prescriptions between pre-COVID-19 years and the same period in 2020.ResultsThe overall number of hospitalisations and outpatient visits decreased by 27% and 22%, respectively, in May 2020, of which the most substantial decrease was observed in the paediatrics department (65% and 51%, respectively). The number of hospitalisations for respiratory diseases, circulatory diseases, malignant neoplasms and digestive diseases decreased by a maximum of 55%, 32%, 10% and 26%, respectively, in 2020. The number of hospitalisations for non-COVID-19 pneumonia in patients aged <16 years, patients aged ≥16 years and patients with asthma decreased by 93%, 43% and 80%, respectively, in May 2020. EFs and outpatient rehabilitations decreased by >30%. In contrast, outpatient chemotherapy and maintenance haemodialysis treatments decreased by <10%, if at all. Outpatient prescriptions decreased by a maximum of 20% in 2020, with the largest decrease observed in drugs for obstructive airway diseases and cough and cold preparations.ConclusionsThe use of healthcare services by non-COVID-19 patients was most affected during the first wave of the COVID-19 pandemic in May 2020. The number of hospitalisations for respiratory diseases, particularly non-COVID-19 pneumonia and asthma, drastically decreased, while the number of hospitalisations and outpatient chemotherapies for malignant neoplasms or maintenance haemodialysis was less affected.
Context Insulinoma is the most common pancreatic functional neuroendocrine neoplasm, yet little information on recent clinical practice in patients with insulinoma, especially malignant insulinoma, is available. Objective To clarify the characteristics and practice patterns in patients with insulinoma using a national inpatient database. Methods Using the Japanese Diagnosis Procedure Combination database, we retrospectively identified patients with insulinoma admitted between 2010 and 2018. We compared background characteristics and therapeutic interventions between patients with benign and malignant insulinoma. We also estimated the incidence of insulinoma using the number of patients with newly diagnosed insulinoma in 2012. Results We identified 844 patients with benign insulinoma and 102 patients with malignant insulinoma. Patients with malignant insulinoma were younger (median, 55.5 vs. 66.0 years, P < 0.001) and less likely to be female (55.9% vs. 65.3%, P = 0.061) than patients with benign insulinoma. Analysis of therapeutic interventions revealed that patients with malignant insulinoma more frequently received medications (71.6% vs. 49.6%, P < 0.001) but less frequently underwent pancreatic surgery (57.8% vs. 72.0%, P = 0.003). Older patients were a smaller proportion of those undergoing surgery and a larger proportion of those managed with medications without surgery (P < 0.001). The incidence of insulinoma was estimated to be 3.27 (95% confidence interval, 2.93–3.61) persons per million Japanese adult population per year. Conclusions The present study using a nationwide database had a larger sample size than previous studies and revealed definitive differences in patient characteristics and therapeutic patterns between benign and malignant insulinoma.
Aims/Introduction: Discontinuation of diabetes care has been studied mostly in patients with prevalent diabetes and not in patients with newly diagnosed diabetes, whose dropout risk is highest. Because enrolling patients in a prospective study will influence adherence, we retrospectively examined whether guideline-recommended practices, defined as nutritional guidance or ophthalmological examination, can prevent patient discontinuation of diabetes care after its initiation. Materials and Methods: We retrospectively identified adults with newly screened diabetes during checkups using a large Japanese administrative claims database (JMDC, Tokyo, Japan) that contains laboratory data and lifestyle questionnaires. We defined discontinuation of physician visits as a follow-up interval exceeding 6 months. We divided the patients into those who received guideline-recommended practices (nutritional guidance or ophthalmology consultation) within the same month as the first visit and those who did not. We calculated propensity scores and carried out inverse probability of treatment weighting analyses to compare discontinuation between the two groups. Results: We identified 6,508 patients with at least one physician consultation for diabetes care within 3 months after their checkup, including 4,574 patients without and 1,934 with guideline-recommended practices. After inverse probability of treatment weighting, patients with guideline-recommended practices had a significantly lower proportion of discontinuation than those without (17.2% vs 21.8%; relative risk 0.79, 95% confidence interval 0.69-0.91). Conclusions: This study is the first to show that after adjustment for both patient and healthcare provider factors, guideline-recommended practices within the first month of physician consultation for diabetes care can decrease subsequent discontinuation of physician visits in patients with newly diagnosed diabetes.
Objectives Acute pancreatitis (AP) guidelines for adult patients do not recommend routine prophylactic use of antibiotics because of no clinical merit on mortality, infectious complications, or length of stay. Although the mortality of pediatric AP is low, no studies have explored the rationale for antibiotic use in pediatric patients. The aim of this study was to evaluate the effects of early prophylactic antibiotics on length of stay and total costs in pediatric patients. Methods Using the Japanese Diagnosis Procedure Combination database from 2010 to 2017, we used the stabilized inverse probability of treatment weighting method using propensity scores to balance the background characteristics in the antibiotics group and the control group, and compared length of stay and total costs between the groups. Results We found significant differences between the antibiotics group (n = 652) and the control group (n = 467) in length of stay (11 days vs 9 days; percent difference, 15.4%; 95% confidence interval, 5.0%–26.8%) and total costs (US $4085 vs US $3648; percent difference, 19.8%; 95% confidence interval, 8.0%–32.9%). Conclusions Prophylactic antibiotics were associated with longer length of stay and higher total costs. Our results do not support routine use of prophylactic antibiotics in pediatric AP populations.
OBJECTIVE Reportedly, two-thirds of the patients who were positive for diabetes during screening failed to attend a follow-up visit for diabetes care in Japan. We aimed to develop a machine-learning model for predicting people’s failure to attend a follow-up visit. RESEARCH DESIGN AND METHODS We conducted a retrospective cohort study of adults with newly screened diabetes at a national screening program using a large Japanese insurance claims database (JMDC, Tokyo, Japan). We defined failure to attend a follow-up visit for diabetes care as no physician consultation during the 6 months after the screening. The candidate predictors were patient demographics, comorbidities, and medication history. In the training set (randomly selected 80% of the sample), we developed two models (previously reported logistic regression model and Lasso regression model). In the test set (remaining 20%), prediction performance was examined. RESULTS We identified 10,645 patients, including 5,450 patients who failed to attend follow-up visits for diabetes care. The Lasso regression model using four predictors had a better discrimination ability than the previously reported logistic regression model using 13 predictors (C-statistic: 0.71 [95% CI 0.69–0.73] vs. 0.67 [0.65–0.69]; P < 0.001). The four selected predictors in the Lasso regression model were lower frequency of physician visits in the previous year, lower HbA1c levels, and negative history of antidyslipidemic or antihypertensive treatment. CONCLUSIONS The developed machine-learning model using four predictors had a good predictive ability to identify patients who failed to attend a follow-up visit for diabetes care after a screening program.
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