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This review introduces the National Hospital Organization (NHO) database in Japan. The NHO has maintained two databases through a system of data collection from 140 hospitals in the NHO. National Hospital Organization Clinical Data Archives (NCDA) is collecting clinical information in real time from the electronic medical records since January 2016, and Medical Information Analysis (MIA) databank is collecting daily insurance claims data since April 2010. The NHO database covers more than 8 million patients in 140 hospitals throughout Japan. The database consists of the information of patient profiles, hospital admission and discharge, diagnosis with ICD-10 codes, text data from medical chart, daily health insurance claims such as medical procedures, medications or surgeries, vital signs and laboratory data, and so on. The NHO database includes a wide variety of diseases and settings, including acute, chronic and intractable diseases, emergency medical services, disaster medicine, response to emerging infectious disease outbreaks, medical care according to health policies such as psychiatry, tuberculosis, or muscular dystrophy, and health systems in sparsely populated non-urban areas. Among several common diseases, the database has representativeness in terms of age distribution compared with the Patient Survey 2017 by the Ministry of Health, Labour and Welfare. Interested researchers can contact (700-dbproject@mail.hosp.go.jp) the NHO database division to obtain more information about the NHO database for utilization.

The potential antimicrobial and anti-inflammatory effectiveness of azithromycin against severe influenza is yet unclear. We retrospectively investigated the effect of intravenous azithromycin administration within 7 days of hospitalization in patients with influenza virus pneumonia and respiratory failure. Using Japan’s national administrative database, we enrolled and classified 5066 patients with influenza virus pneumonia into severe, moderate, and mild groups based on their respiratory status within 7 days of hospitalization. The primary endpoints were total, 30-day, and 90-day mortality rates. The secondary endpoints were the duration of intensive-care unit management, invasive mechanical ventilation, and hospital stay. The inverse probability of the treatment weighting method with estimated propensity scores was used to minimize data collection bias. Use of intravenous azithromycin was proportional to the severity of respiratory failure (mild: 1.0%, moderate: 3.1%, severe: 14.8%). In the severe group, the 30-day mortality rate was significantly lower with azithromycin (26.49% vs. 36.65%, p = 0.038). In the moderate group, the mean duration of invasive mechanical ventilation after day 8 was shorter with azithromycin; there were no significant differences in other endpoints between the severe and moderate groups. These results suggest that intravenous azithromycin has favorable effects in patients with influenza virus pneumonia using mechanical ventilation or oxygen.

Aims Heart failure is a significant disease, and its high readmission rate is a big concern. We must identify readmission risk factors and optimize outpatient management to prevent them. This study aims to investigate the readmission risk factors, including outpatient management represented by the number of outpatient visits, and to identify the factors related to frequent outpatient visits. Methods and results We used the diagnosis‐procedure‐combination database between April 2016 and March 2022. Based on the number of outpatient visits within 60 days after discharge, we categorized patients into <1 visits/month, (1<, ≦2) visits/month, and <2 visits/month and observed the occurrence of 60 days readmission. We performed multiple logistic regression analyses to reveal the readmission risk factors and the association between the number of outpatient visits and readmission. As a subgroup analysis, we conducted the same research in the low‐ and high‐readmission risk groups. We compared medical contents between (1<, ≦2) visits/month and <2 visits/month. We analysed 101 239 patients and identified the following factors as a risk of readmission: older age (P < 0.001), female (P = 0.009), longer length‐of‐hospital‐stay (P < 0.001), artificial ventilator (P < 0.001), tolvaptan (P < 0.001), top 50% dosage of loop diuretics (P = 0.036), bottom 50% dosage of class III antiarrhythmic agents (P < 0.001), hypertension (P = 0.005), atrial fibrillation (P < 0.001), dilated cardiomyopathy (P < 0.001), valvular disease (P = 0.021), myocardial infarction (P < 0.001), diabetes (P < 0.001), and renal disease (P < 0.001). We revealed that the risk of readmission increases in <2 visits/month compared to (1<, ≦2) visits/month (P < 0.001), whereas the risk of readmission decreases in ≦1 visits/month compared with (1<, ≦2) visits/month (P < 0.001). In the subgroup analysis, we found the possibility that some risk factors are specific to the subgroup. We identified that the following factors were related to frequent outpatient visits: older age (P < 0.001), home medical care (P = 0.007), tolvaptan (P < 0.001), top 50% dosage of loop diuretics (P < 0.001), diabetes (P < 0.001), renal disease (P = 0.009), 0–2 weeks follow‐up (P < 0.001), 2–4 weeks follow‐up (P < 0.001), cardiac rehabilitation (P < 0.001), and echocardiography (P < 0.001). Conclusions This study comprehensively identified risk factors for readmission and found outpatient visit is personalized by readmission risk. There is still room to optimize outpatient management. We suggest optimizing outpatient management according to our identified characteristics.

This study aimed to clarify the relationship between carbapenem consumption and clinical outcome using the diagnosis procedure combination (DPC) payment system database (2020) published by the Ministry of Health, Labour, and Welfare of Japan. This study divided 5316 medical facilities subject to aggregation into five facilities and calculated the median values, including facility characteristics, clinical outcomes, and carbapenem consumption. Next, a correlation analysis was performed between carbapenem consumption and clinical outcome, as well as a multiple regression analysis between carbapenem consumption as the dependent variable and clinical outcome, bed size, and proportion of patients by disease as independent variables. Additionally, three clinical outcomes available from the DPC payment system database were selected, including cure, readmission within 4 weeks, and the average length of stay. This study revealed no relationship between carbapenem consumption and clinical outcome in university hospitals and university hospital-equivalent community hospitals; however, a relationship was suggested in the community, DPC-prepared, and non-DPC hospitals. University hospitals and university hospital-equivalent community hospitals with a high consumption of carbapenems may need to reconsider the classification because of the limited number of facilities in this classification.

DPC, which is an acronym for “Diagnosis Procedure Combination,” is a patient classification method developed in Japan for inpatients in the acute phase of illness. It was developed as a measuring tool intended to make acute inpatient care transparent, aiming at standardization of Japanese medical care, as well as evaluation and improvement of its quality. Subsequently, this classification method came to be used in the Japanese medical service reimbursement system for acute inpatient care and appropriate allocation of medical resources. Furthermore, it has recently contributed to the development and maintenance of an appropriate medical care provision system at a regional level, which is accomplished based on DPC data used for patient classification. In this paper, we first provide an overview of DPC. Next, we will look back at over 15 years of DPC history; in particular, we will explore how DPC has been refined to become an appropriate medical service reimbursement system. Finally, we will introduce an outline of DPC-related research, starting with research using DPC data.

•Validation study on the diagnosis procedure combination database.•The database was linked with a hospital-based cancer registry as reference.•Total of 29,180 patients diagnosed with one of 15 types of cancer were eligible.•Concordance of cancer diagnosis was generally over 90 %.•Concordance of cancer stage was over 70 % in half of the eight common cancer types. In Japan, the Diagnosis Procedure Combination (DPC) data have been used as a nationwide administrative hospital discharge database for clinical studies. However, few studies have evaluated the validity of recorded diagnoses of cancer in the database. We compared the DPC data with hospital-based cancer registries in Osaka Prefecture, Japan to assess the validity of the recorded cancer diagnoses in the DPC data. Fifteen types of cancer were included in the analysis. Cancer stage with tumor-node-metastasis (TNM) classification was assessed for eight cancer types with >400 patients. We evaluated concordance and positive predictive value of cancer diagnosis, and concordance of cancer stage between the DPC data and the hospital-based cancer registry. In total, we identified 29,180 eligible patients. The five types of cancer with the highest number of patients were as follows: 6,765 (23.2 %) colorectal, 6,476 (22.2 %) stomach, 4,862 (16.7 %) breast, 4,445 (15.2 %) lung, and 2,257 (7.7 %) liver. Concordance of diagnosis ranged from 63.9 %–99.5 %, and twelve of the fifteen types of cancers had concordance of over 90 %. Positive predictive values of diagnosis ranged from 86.8 %–100 %. Regarding cancer stage, the overall degree of concordance was 67.2 % in all patients and the concordance was over 70 % in four types of cancers. The DPC data had high validity of cancer diagnosis. However, the potential impact of the misclassifications and low concordance in cancer stage among specific type of cancers in the DPC data should be considered.

Background In Japan, several large healthcare databases have become available for research since the early 2000’s. However, validation studies to examine the accuracy of these databases remain scarce. We conducted a validation study in order to estimate the positive predictive value (PPV) of local or ICD-10 codes for acute myocardial infarction (AMI) in Japanese claims. In particular, we examined whether the PPV differs between claims in the Diagnosis Procedure Combination case mix scheme (DPC claims) and in non-DPC claims. Methods We selected a random sample of 200 patients from all patients hospitalized at a large tertiary-care university hospital between January 1, 2009 and December 31, 2011 who had an inpatient claim assigned a local or ICD-10 code for AMI. We used a standardized data abstraction form to collect the relevant information from an electronic medical records system. Abstracted information was then categorized by a single cardiologist as being either definite or not having AMI. Results In a random sample of 200 patients, the average age was 67.7 years and the proportion of males was 78.0%. The PPV of the local or ICD-10 code for AMI was 82.5% in this sample of 200 patients. Further, of 178 patients who had an ICD-10 code for AMI based on any of the 7 types of condition codes in the DPC claims, the PPV was 89.3%, whereas of the 161 patients who had an ICD-10 code for AMI based on any of 3 major types of condition codes in the DPC claims, the PPV was 93.8%. Conclusion The PPV of the local or ICD-10 code for AMI was high for inpatient claims in Japan. The PPV was even higher for the ICD-10 code for AMI for those patients who received AMI care through the DPC case mix scheme. The current study was conducted in a single center, suggesting that a multi-center study involving different types of hospitals is needed in the future. The accuracy of condition codes for DPC claims in Japan may also be worth examining for conditions other than AMI such as stroke.

Intubation-related pneumonia negatively affects patient outcomes. Aspiration pneumonia occurring after extubation due to swallowing dysfunction, conceptualized as postextubation pneumonia (PEP), remains underrecognized as a distinct clinical entity. This single-center, retrospective study aimed to evaluate the incidence and risk factors for PEP using large-scale　diagnosis procedure combination (DPC) and administrative claims data. We reviewed all patients who underwent elective surgery under general anesthesia between April 2016 and March 2023. Patients undergoing emergency surgery or lacking data on activities of daily living (ADL) or body mass index (BMI) were excluded. Patients who developed pneumonia after extubation and required newly initiated antibiotic therapy were classified as PEP cases. Ventilator-associated pneumonia (VAP) cases were identified according to standard definitions. Among 31 828 eligible patients, 212 (0.67%) developed PEP, which occurred more frequently than VAP. Risk factors for PEP included advanced age, male sex, low BMI, impaired consciousness, and reduced ADL. Surgical sites associated with PEP included the gastrointestinal tract, respiratory system, thoracic cavity, cardiovascular and nervous systems, and head, neck, and face. Smoking status was not significantly associated with PEP. These findings highlight PEP as a clinically important and potentially preventable complication. Targeted dysphagia screening and perioperative multidisciplinary interventions may help reduce its incidence.

•Body mass index and rate of weight change associated with chronic kidney disease were studied.•A retrospective cohort study was performed.•Low body mass index and high weight change were associated with mortality.•High body mass index was associated with a smaller effect of weight change on mortality.•The increased weight gain and mortality in this study may be due to fluid overload. This study aimed to investigate body mass index (BMI) and rate of weight change associated with adverse outcomes in Asian patients with chronic kidney disease. A retrospective cohort study was performed between April 2014 and June 2022 using the administrative claims database compiled by the Japan Medical Data Center. Patients were defined as individuals with comorbidities with chronic kidney disease stages 3 to 5 on admission and were aged ≥40 y with BMI at admission and BMI information from a previous admission 3 to 12 mo earlier. Restricted cubic spline analysis and thin-plate smoothed spline analysis were performed. A total of 10 802 individuals were analyzed. The mean age was 74.6 ± 11.3 y, number of men was 7175 (66.4%), and 2115 (19.6%) deaths were recorded. Smoothed splines for BMI found that low BMI was associated with high hazard ratio (HR) (BMI = 18.5 kg/m2; HR = 1.3 [1.2–1.4]). Smoothed splines of weight change found higher HR with increasing rate of weight change for both weight gain and loss (weight change rate = –10%; HR = 1.4 [1.3–1.5]; weight change rate = 10%; HR = 1.2 [1.1–1.3]). In thin-plate smoothed spline analysis, the U-curve had a higher odds ratio as BMI decreased in patients with or without dialysis and as the degree of weight change increased. We found trends in BMI and rate of weight change associated with mortality in Asian patients with chronic kidney disease.

•Cancer cachexia plays a vital role in health complications.•Low body mass index and involuntary weight loss are the diagnostic markers of cancer cachexia.•Death risk in patients with cancer cachexia is predicted by low body mass index and involuntary weight loss. Conventional diagnostic criteria for cachexia are based on Western studies. The aim of this study was to investigate trends in body mass index (BMI) and the rate of weight change associated with adverse outcomes in Asian patients with advanced cancer. This retrospective cohort study was conducted using the administrative claims database compiled by the Japan Medical Data Center Inc. The study was conducted between April 2014 and September 2022 on patients with advanced cancer. A Cox regression model was used to perform a restricted cubic spline analysis with four knots for BMI and weight change. Additionally, thin-plate smoothed splines were used to generate contour plots of the odds ratios of BMI and weight change for mortality. The study analyzed 48 600 patients. The mean age was 71.9 ± 10 y. There were 33 051 men (68%) and 17 853 deaths (37%). The smoothed splines for BMI showed that low BMI was associated with high hazard ratio (HR, [95% confidence interval]; BMI = 18.5 kg/m2, HR, 1.2; [1.1–1.2]; BMI = 25 kg/m2, HR, 0.9; [0.9–0.9]). The smoothed spline of weight change showed a higher HR with an increasing rate of weight change (weight change rate –10%, HR, 1.1; [1.1–1.2]; weight change rate +10%, HR, 1; [1–1]). In the thin-plate smoothed spline analysis, patients with BMI <17 to 18.5 kg/m2 were at a higher risk for death regardless of weight change. Low BMI, a large degree of weight change, or a combination of both, predicted death in Asian patients with advanced cancer.