SS-MIX: A Ministry Project to Promote Standardized Healthcare Information Exchange

Factors affecting the sodium-glucose cotransporter 2 inhibitors-related initial decline in glomerular filtration rate and its possible effect on kidney outcome in chronic kidney disease with type 2 diabetes: The Japan Chronic Kidney Disease Database

AIM

Sodium-glucose cotransporter 2 (SGLT2) inhibitors often cause a transient decrease in glomerular filtration rate (GFR) shortly after the initiation, referred to as the 'initial drop'. However, the clinical significance of this initial drop in real-world practice remains unclear.

MATERIALS AND METHODS

Using the nationwide Japan Chronic Kidney Disease Database, we examined factors that affected the initial drop, in patients with chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). We also evaluated the effects of the initial drop on a composite kidney outcome (a decline in GFR of ≥50% or progression to end-stage kidney disease).

RESULTS

Data from 2053 patients with CKD and T2DM newly prescribed an SGLT2 inhibitor were analysed. The follow-up period after SGLT2 inhibitor administration was 1015 days (interquartile range: 532, 1678). Multivariate linear regression models revealed that the concomitant use of the renin-angiotensin system inhibitors and diuretics, urinary protein levels ≥2+, and changes in GFR before the initiation of the SGLT2 inhibitor were associated with a larger initial GFR decline (β = -0.609, p = .039; β = -2.298, p < .001; β = -0.936, p = .048; β = -0.079, p < .001, respectively). Patients in the quartile with the largest initial GFR decline experienced a higher incidence of the subsequent composite kidney outcome than those in the other quartiles (p < .001).

CONCLUSIONS

The concomitant use of renin-angiotensin system inhibitors and diuretics, higher urine protein levels and pre-treatment GFR changes were associated with a larger initial GFR decline. Of these factors, the use of a diuretic had the largest effect. Furthermore, patients with CKD and T2DM experiencing an excessive initial GFR drop might be at a higher risk of adverse kidney outcomes.

Detection Algorithms for Gastrointestinal Perforation Cases in the Medical Information Database Network (MID-NET®) in Japan

BACKGROUND

The Medical Information Database Network (MID-NET®) in Japan is a vast repository providing an essential pharmacovigilance tool. Gastrointestinal perforation (GIP) is a critical adverse drug event, yet no well-established GIP identification algorithm exists in MID-NET®.

METHODS

This study evaluated 12 identification algorithms by combining ICD-10 codes with GIP therapeutic procedures. Two sites contributed 200 inpatients with GIP-suggestive ICD-10 codes (100 inpatients each), while a third site contributed 165 inpatients with GIP-suggestive ICD-10 codes and antimicrobial prescriptions. The positive predictive values (PPVs) of the algorithms were determined, and the relative sensitivity (rSn) among the 165 inpatients at the third institution was evaluated.

RESULTS

A trade-off between PPV and rSn was observed. For instance, ICD-10 code-based definitions yielded PPVs of 59.5%, whereas ICD-10 codes with CT scan and antimicrobial information gave PPVs of 56.0% and an rSn of 97.0%, and ICD-10 codes with CT scan and antimicrobial information as well as three types of operation codes produced PPVs of 84.2% and an rSn of 24.2%. The same algorithms produced statistically significant differences in PPVs among the three institutions. Combining diagnostic and procedure codes improved the PPVs. The algorithm combining ICD-10 codes with CT scan and antimicrobial information and 80 different operation codes offered the optimal balance (PPV: 61.6%, rSn: 92.4%).

CONCLUSION

This study developed valuable GIP identification algorithms for MID-NET®, revealing the trade-offs between accuracy and sensitivity. The algorithm with the most reasonable balance was determined. These findings enhance pharmacovigilance efforts and facilitate further research to optimize adverse event detection algorithms.

Kidney outcomes of SGLT2 inhibitors among older patients with diabetic kidney disease in real-world clinical practice: the Japan Chronic Kidney Disease Database Ex

INTRODUCTION

We compared the kidney outcomes between patients with diabetic kidney disease (DKD) aged ≥75 years initiating sodium-glucose cotransporter 2 (SGLT2) inhibitors versus other glucose-lowering drugs, additionally presenting with or without proteinuria.

RESEARCH DESIGN AND METHODS

Using the Japan Chronic Kidney Disease Database, we developed propensity scores, implementing a 1:1 matching protocol. The primary outcome included the decline rate in estimated glomerular filtration rate (eGFR), and secondary outcomes incorporated a composite of a 40% reduction in eGFR or progression to end-stage kidney disease.

RESULTS

At baseline, the mean age at initiation of SGLT2 inhibitors (n=348) or other glucose-lowering medications (n=348) was 77.7 years. The mean eGFR was 59.3 mL/min/1.73m2 and proteinuria was 230 (33.0%) patients. Throughout the follow-up period, the mean annual rate of eGFR change was -0.80 mL/min/1.73 m2/year (95% CI -1.05 to -0.54) among SGLT2 inhibitors group and -1.78 mL/min/1.73 m2/year (95% CI -2.08 to -1.49) in other glucose-lowering drugs group (difference in the rate of eGFR decline between the groups was 0.99 mL/min/1.73 m2/year (95% CI 0.5 to 1.38)), favoring SGLT2 inhibitors (p<0.001). Composite renal outcomes were observed 38 in the SGLT2 inhibitors group and 57 in the other glucose-lowering medications group (HR 0.64, 95% CI 0.42 to 0.97). There was no evidence of an interaction between SGLT2 inhibitors initiation and proteinuria.

CONCLUSIONS

The benefits of SGLT2 inhibitors on renal outcomes are also applicable to older patients with DKD aged≥75 years.

Evaluating the associations between compliance with CKD guideline component metrics and renal outcomes

Understanding the association between compliance to the Chronic Kidney Disease (CKD) guidelines in real-world clinical settings and renal outcomes remains a critical gap in knowledge. A comprehensive analysis was conducted using data from a national, multicenter CKD registry. This study included 4,455 patients with an estimated glomerular filtration rate (eGFR) measurement on the index date and eight additional metrics recorded within six months. These metrics comprised serum electrolyte levels, low-density lipoprotein cholesterol, hemoglobin, and the use of renin-angiotensin system inhibitors. The primary outcome was a composite of renal events, defined by a decline in eGFR to < 15 mL/min/1.73 m2 or a reduction of ≥ 30% in eGFR, confirmed by follow-up tests. Over a median follow-up of 513 days, 838 renal events were observed. High serum potassium levels (> 5.4 mmol/L) were associated with increased event rates compared to lower levels. Similarly, low serum sodium-chloride levels (< 33) correlated with higher event rates. Usage of renin-angiotensin system inhibitors, low serum calcium (< 8.4 mg/dL), and high uric acid levels (> 7.0 mg/dL) were also linked to increased events. Conversely, higher hemoglobin levels (≥ 13 g/dL) were associated with lower event rates. Compliance to guidelines, categorized into quartiles based on the number of met metrics, revealed a significantly reduced risk of events in the highest compliance group (meeting 8 metrics) compared to the lowest (0-5 metrics). Compliance to CKD guidelines in clinical practice is significantly associated with improved renal outcomes, emphasizing the need for guideline-concordant care in the management of CKD.

Kidney outcomes associated with haematuria and proteinuria trajectories among patients with IgA nephropathy in real-world clinical practice: The Japan Chronic Kidney Disease Database

AIM

Among patients with Immunoglobulin A (IgA) nephropathy, we aimed to identify trajectory patterns stratified by the magnitude of haematuria and proteinuria using repeated urine dipstick tests, and assess whether the trajectories were associated with kidney events.

METHODS

Using a nationwide multicentre chronic kidney disease (CKD) registry, we analysed data from 889 patients with IgA nephropathy (mean age 49.3 years). The primary outcome was a sustained reduction in eGFR of 50% or more from the index date and thereafter. During follow-up (median 49.0 months), we identified four trajectories (low-stable, moderate-decreasing, moderate-stable, and high-stable) in both urine dipstick haematuria and proteinuria measurements, respectively.

RESULTS

In haematuria trajectory analyses, compared to the low-stable group, the adjusted hazard ratios (HRs) (95% confidence interval [CI]) for kidney events were 2.59 (95% CI, 1.48-4.51) for the high-stable, 2.31 (95% CI, 1.19-4.50) for the moderate-stable, and 1.43 (95% CI, (0.72-2.82) for the moderate-decreasing groups, respectively. When each proteinuria trajectory group was subcategorized according to haematuria trajectories, the proteinuria group with high-stable and with modest-stable haematuria trajectories had approximately 2-times higher risk for eGFR reduction ≥50% compared to that with low-stable haematuria trajectory.

CONCLUSION

Assessments of both haematuria and proteinuria trajectories using urine dipstick could identify high-risk IgA nephropathy patients.

Sex Differences in Long-Term Outcomes in Patients With Chronic Coronary Syndrome After Percutaneous Coronary Intervention - Insights From a Japanese Real-World Database Using a Storage System

BACKGROUND

Several studies have reported some sex differences in patients with coronary artery diseases. However, the results regarding long-term outcomes in patients with chronic coronary syndrome (CCS) are inconsistent. Therefore, the present study investigated sex differences in long-term outcomes in patients with CCS after percutaneous coronary intervention (PCI).Methods and Results: This was a retrospective, multicenter cohort study. We enrolled patients with CCS who underwent PCI between April 2013 and March 2019 using the Clinical Deep Data Accumulation System (CLIDAS) database. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, or hospitalization for heart failure. In all, 5,555 patients with CCS after PCI were included in the analysis (4,354 (78.4%) men, 1,201 (21.6%) women). The median follow-up duration was 917 days (interquartile range 312-1,508 days). The incidence of MACE was not significantly different between the 2 groups (hazard ratio [HR] 1.20; 95% confidential interval [CI] 0.97-1.47; log-rank P=0.087). After performing multivariable Cox regression analyses on 4 different models, there were still no differences in the incidence of MACE between women and men.

CONCLUSIONS

There were no significant sex differences in MACE in patients with CCS who underwent PCI and underwent multidisciplinary treatments.

Relationships Among Heart Rate, β-Blocker Dosage, and Prognosis in Patients With Coronary Artery Disease in a Real-World Database Using a Multimodal Data Acquisition System

BACKGROUND

The optimal heart rate (HR) and optimal dose of β-blockers (BBs) in patients with coronary artery disease (CAD) have been unclear. We sought to clarify the relationships among HR, BB dose, and prognosis in patients with CAD using a multimodal data acquisition system.Methods and Results: We evaluated the data for 8,744 CAD patients who underwent cardiac catheterization from 6 university hospitals and the National Cerebral and Cardiovascular Center and who were registered using the Clinical Deep Data Accumulation System. Patients were divided into quartile groups based on their HR at discharge: Q1 (HR <60 beats/min), Q2 (HR 60-66 beats/min), Q3 (HR 67-74 beats/min), and Q4 (HR ≥75 beats/min). Among patients with acute coronary syndrome (ACS) and patients with chronic coronary syndrome (CCS), those in Q4 (HR ≥75 beats/min) had a significantly greater incidence of major adverse cardiac and cerebral events (MACCE) compared with those in Q1 (ACS patients: hazard ratio 1.65, P=0.001; CCS patients: hazard ratio 1.45, P=0.019). Regarding the use of BBs (n=4,964), low-dose administration was significantly associated with MACCE in the ACS group (hazard ratio 1.41, P=0.012), but not in patients with CCS after adjustment for covariates.

CONCLUSIONS

HR ≥75 beats/min was associated with worse outcomes in patients with CCS or ACS.

Hyperuricemia predicts increased cardiovascular events in patients with chronic coronary syndrome after percutaneous coronary intervention: A nationwide cohort study from Japan

Background

The causal relationship between hyperuricemia and cardiovascular diseases is still unknown. We hypothesized that hyperuricemic patients after percutaneous coronary intervention (PCI) had a higher risk of major adverse cardiovascular events (MACE).

Methods

This was a large-scale multicenter cohort study. We enrolled patients with chronic coronary syndrome (CCS) after PCI between April 2013 and March 2019 using the database from the Clinical Deep Data Accumulation System (CLIDAS), and compared the incidence of MACE, defined as a composite of cardiovascular death, myocardial infarction, and hospitalization for heart failure, between hyperuricemia and non-hyperuricemia groups.

Results

In total, 9,936 patients underwent PCI during the study period. Of these, 5,138 patients with CCS after PCI were divided into two group (1,724 and 3,414 in the hyperuricemia and non-hyperuricemia groups, respectively). The hyperuricemia group had a higher prevalence of hypertension, atrial fibrillation, history of previous hospitalization for heart failure, and baseline creatinine, and a lower prevalence of diabetes than the non-hyperuricemia group, but the proportion of men and age were similar between the two groups. The incidence of MACE in the hyperuricemia group was significantly higher than that in the non-hyperuricemia group (13.1 vs. 6.4%, log-rank P < 0.001). Multivariable Cox regression analyses revealed that hyperuricemia was significantly associated with increased MACE [hazard ratio (HR), 1.52; 95% confidential interval (CI), 1.23-1.86] after multiple adjustments for age, sex, body mass index, estimated glomerular filtration rate, left main disease or three-vessel disease, hypertension, diabetes mellitus, dyslipidemia, history of myocardial infarction, and history of hospitalization for heart failure. Moreover, hyperuricemia was independently associated with increased hospitalization for heart failure (HR, 2.19; 95% CI, 1.69-2.83), but not cardiovascular death or myocardial infarction after multiple adjustments. Sensitive analyses by sex and diuretic use, B-type natriuretic peptide level, and left ventricular ejection fraction showed similar results.

Conclusion

CLIDAS revealed that hyperuricemia was associated with increased MACE in patients with CCS after PCI. Further clinical trials are needed whether treating hyperuricemia could reduce cardiovascular events or not.

Medical Image Sharing in Japan

This paper reports the history, background including politics, current status of Japan’s health imaging study and other information sharing. Its realization was slow until the Ministry of Health, Labour and Welfare (MHLW) started paying digital image storage at the same rate as films in 2008. Information sharing was initiated in early 2010s, which was before vendors became ready for Integrating the Healthcare Enterprise (IHE) cross-enterprise document sharing (XDS), with the result that most of 34 large regional sharing systems are in non-standardized protocol. One standardized example is the Hamamatsu area where inexpensive online PDI (portable data for imaging) was introduced.

Existing Data Sources for Clinical Epidemiology: Database of the National Hospital Organization in Japan

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.

Machine learning for classification of postoperative patient status using standardized medical data

BACKGROUND AND OBJECTIVE

Real-world evidence is defined as clinical evidence regarding the use and potential benefits or risks of a medical product derived from real-world data analyses. Standardization and structuring of data are necessary to analyze medical real-world data collected from different medical institutions. An electronic message and repository have been developed to link electronic medical records in this research project, which has simplified the data integration. Therefore, this paper proposes an analysis method and learning health systems to determine the priority of clinical intervention by clustering and visualizing time-series and prioritizing patient outcomes and status during hospitalization.

METHODS

Common data items for reimbursement (Diagnosis Procedure Combination [DPC]) and clinical pathway data were examined in this project at each participating institution that runs the verification test. Long-term hospitalization data were analyzed using the data stored in the cloud platform of the institutions' repositories using multiple machine learning methods for classification, visualization, and interpretation.

RESULTS

The ePath platform contributed to integrate the standardized data from multiple institutions. The distribution of DPC items or variances could be confirmed by clustering, temporal tendency through the directed graph, and extracting variables that contributed to the prediction and evaluation of SHapley Additive Explanation effects. Constipation was determined to be the risk factor most strongly related to long-term hospitalization. Drainage management was identified as a factor that can improve long-term hospitalization. These analyses effectively extracted patient status to provide feedback to the learning health system.

CONCLUSIONS

We successfully generated evidence of medical processes by gathering patient status, medical purposes, and patient outcomes with high data quality from multiple institutions, which were difficult with conventional electronic medical records. Regarding the significant analysis results, the learning health system will be used on this project to provide feedback to each institution, operate it for a certain period, and analyze and re-evaluate it.

Kidney Outcomes Associated With SGLT2 Inhibitors Versus Other Glucose-Lowering Drugs in Real-world Clinical Practice: The Japan Chronic Kidney Disease Database

OBJECTIVE

Randomized controlled trials have shown kidney-protective effects of sodium-glucose cotransporter 2 (SGLT2) inhibitors, and clinical practice databases have suggested that these effects translate to clinical practice. However, long-term efficacy, as well as whether the presence or absence of proteinuria and the rate of estimated glomerular filtration rates (eGFR) decline prior to SGLT2 inhibitor initiation modify treatment efficacy among type 2 diabetes mellitus (T2DM) and chronic kidney disease (CKD) patients, is unknown.

RESEARCH DESIGN AND METHODS

Using the Japan Chronic Kidney Disease Database (J-CKD-DB), a nationwide multicenter CKD registry, we developed propensity scores for SGLT2 inhibitor initiation, with 1:1 matching with patients who were initiated on other glucose-lowering drugs. The primary outcome included rate of eGFR decline, and the secondary outcomes included a composite outcome of 50% eGFR decline or end-stage kidney disease.

RESULTS

At baseline, mean age at initiation of the SGLT2 inhibitor (n = 1,033) or other glucose-lowering drug (n = 1,033) was 64.4 years, mean eGFR was 68.1 mL/min per 1.73 m², and proteinuria was apparent in 578 (28.0%) of included patients. During follow-up, SGLT2 inhibitor initiation was associated with reduced eGFR decline (difference in slope for SGLT2 inhibitors vs. other drugs 0.75 mL/min/1.73 m² per year [0.51 to 1.00]). During a mean follow-up of 24 months, 103 composite kidney outcomes occurred: 30 (14 events per 1,000 patient-years) among the SGLT2 inhibitors group and 73 (36 events per 1,000 patient-years) among the other drugs group (hazard ratio 0.40, 95% CI 0.26-0.61). The benefit provided by SGLT2 inhibitors was consistent irrespective of proteinuria and rate of eGFR decline before initiation of SGLT2 inhibitors (P _{heterogeneity} ≥ 0.35).

CONCLUSIONS

The benefits of SGLT2 inhibitors on kidney function as observed in clinical trials translate to patients treated in clinical practice with no evidence that the effects are modified by the underlying rate of kidney function decline or the presence of proteinuria.

MIHARI project, a preceding study of MID-NET, adverse event detection database of Ministry Health of Japan-Validation study of the signal detection of adverse events of drugs using export data from EMR and medical claim data

We studied the effectiveness of the direct data collection from electronic medical records (EMR) when it is used for monitoring adverse drug events and also detection of already known adverse events. In this study, medical claim data and SS-MIX2 standardized storage data were used to identify four diseases (diabetes, dyslipidemia, hyperthyroidism, and acute renal failure) and the validity of the outcome definitions was evaluated by calculating positive predictive values (PPV). The maximum positive predictive value (PPV) for diabetes based on medical claim data was 40.7% and that based on prescription data from SS-MIX2 Standardized Storage was 44.7%. The PPV for dyslipidemia was 50% or higher under either of the conditions. The PPV for hyperthyroidism based on disease name data alone was 20–30%, but exceeded 60% when prescription data was included in the evaluation. Acute renal failure was evaluated using information from medical records in addition to the data. The PPV for acute renal failure based on the data of disease names and laboratory examination results was slightly higher at 53.7% and increased to 80–90% when patients who previously had a high serum creatinine (Cre) level were excluded. When defining a disease, it is important to include the condition specific to the disease; furthermore, it is very useful if laboratory examination results are also included. Therefore, the inclusion of laboratory examination results in the definitions, as in the present study, was considered very useful for the analysis of multi-center SS-MIX2 standardized storage data.

Development of an application concerning fast healthcare interoperability resources based on standardized structured medical information exchange version 2 data

BACKGROUND AND OBJECTIVE

A mobile application for personal health records (PHR) would allow patients to access their clinical data easily. When PHR connects with multiple electronic health records (EHRs), doctors and patients can exchange large quantities of patient data from the EHR (e.g., medication list, diagnoses, allergies, and laboratory data). Furthermore, personal daily records can also be retrieved from PHR (e.g., blood pressure, pulse, dietary habits, and exercise). However, no standard interoperability between EHRs and PHR has been established. This study aims to convert clinical data in EHRs into the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) data format while developing a PHR application to present the FHIR data.

METHODS

In Japan, Standardized Structured Medical Information eXchange version 2 (SS-MIX2) is typically utilized as a health information exchange to preserve and elicit clinical data from EHRs. We converted clinical data in the SS-MIX2 storage at Tohoku University Hospital into the FHIR repository server using the R4 standard. Additionally, we used the Swift programming language to build a PHR application.

RESULTS

We converted patients' basic information, disease names, diagnostic reports, prescriptions, and injection data from the SS-MIX2 to the FHIR server. Besides, we launched a PHR application that could retrieve data from the FHIR server to display patients' clinical information.

CONCLUSIONS

Our work demonstrated the conversion of SS-MIX2 data into the FHIR and presented them with our PHR application. This mechanism may be useful to accelerate the sharing of clinical information among doctors and patients.

Health Information Exchange between Specialists and General Practitioners Benefits Rural Patients

BACKGROUND

Health information exchange (HIE) may improve diagnostic accuracy, treatment efficacy, and safety by providing treating physicians with expert advice. However, most previous studies on HIE have been observational in nature.

OBJECTIVES

To examine whether collaboration between specialists and general practitioners (GPs) in rural areas via HIE can improve outcomes among patients at low-to-moderate risk of cardiovascular disease, kidney disease, and stroke.

METHODS

In this randomized controlled trial, the Miyagi Medical and Welfare Information Network was used for HIE. We evaluated the clinical data of 1,092 patients aged ≥65 years living in the rural areas of the Miyagi Prefecture and receiving care from GPs only. High-risk patients were immediately referred to specialists, whereas low-to-moderate risk patients were randomly assigned to an intervention group in which GPs were advised by specialists through HIE (n = 518, 38% male, mean age = 76 ± 7 years) or a control group in which GPs received no advice by specialists (n = 521, 39% male, mean age = 75 ± 7 years).

RESULTS

In the intention-to-treat analysis, all-cause mortality and cumulative incidence of serious adverse events (e.g., hospital admission or unexpected referral to specialists) did not differ between the groups. However, per-protocol analysis controlling for GP adherence with specialist recommendations revealed significantly reduced all-cause mortality (p = 0.04) and cumulative serious adverse event incidence (p = 0.04) in the intervention group compared with the control group.

CONCLUSION

HIE systems may improve outcomes among low-to-moderate risk patients by promoting greater collaboration between specialists and GPs, particularly in rural areas with few local specialists.

Machine learning-based prediction of in-hospital mortality using admission laboratory data: A retrospective, single-site study using electronic health record data

Risk assessment of in-hospital mortality of patients at the time of hospitalization is necessary for determining the scale of required medical resources for the patient depending on the patient's severity. Because recent machine learning application in the clinical area has been shown to enhance prediction ability, applying this technique to this issue can lead to an accurate prediction model for in-hospital mortality prediction. In this study, we aimed to generate an accurate prediction model of in-hospital mortality using machine learning techniques. Patients 18 years of age or older admitted to the University of Tokyo Hospital between January 1, 2009 and December 26, 2017 were used in this study. The data were divided into a training/validation data set (n = 119,160) and a test data set (n = 33,970) according to the time of admission. The prediction target of the model was the in-hospital mortality within 14 days. To generate the prediction model, 25 variables (age, sex, 21 laboratory test items, length of stay, and mortality) were used to predict in-hospital mortality. Logistic regression, random forests, multilayer perceptron, and gradient boost decision trees were performed to generate the prediction models. To evaluate the prediction capability of the model, the model was tested using a test data set. Mean probabilities obtained from trained models with five-fold cross-validation were used to calculate the area under the receiver operating characteristic (AUROC) curve. In a test stage using the test data set, prediction models of in-hospital mortality within 14 days showed AUROC values of 0.936, 0.942, 0.942, and 0.938 for logistic regression, random forests, multilayer perceptron, and gradient boosting decision trees, respectively. Machine learning-based prediction of short-term in-hospital mortality using admission laboratory data showed outstanding prediction capability and, therefore, has the potential to be useful for the risk assessment of patients at the time of hospitalization.

Prevalences of hyperuricemia and electrolyte abnormalities in patients with chronic kidney disease in Japan: A nationwide, cross-sectional cohort study using data from the Japan Chronic Kidney Disease Database (J-CKD-DB)

BACKGROUND

The Japan Chronic Kidney Disease Database (J-CKD-DB) is a nationwide clinical database of patients with chronic kidney disease (CKD) based on electronic health records. The objective of this study was to assess the prevalences of hyperuricemia and electrolyte abnormalities in Japanese patients with CKD.

METHODS

In total, 35,508 adult outpatients with estimated glomerular filtration rates of 5-60 ml/min/1.73 m2 in seven university hospitals were included this analysis. The proportions of patients with CKD stages G3b, G4, and G5 were 23.5%, 7.6%, and 3.1%, respectively.

RESULTS

Logistic regression analysis showed that prevalence of hyperuricemia was associated with CKD stages G3b (adjusted odds ratio [95% confidence interval]: 2.12 [1.90-2.37]), G4 (4.57 [3.92-5.32]), and G5 (2.25 [1.80-2.80]). The respective prevalences of hyponatremia, hypercalcemia, hyperphosphatemia, and narrower difference between serum sodium and chloride concentrations were elevated in patients with CKD stages G3b, G4, and G5, compared with those prevalences in patients with CKD stage G3a. The prevalences of hyperkalemia were 8.3% and 11.6% in patients with CKD stages G4 and G5, respectively. In patients with CKD stage G5, the proportions of patients with optimal ranges of serum uric acid, potassium, corrected calcium, and phosphate were 49.6%, 73.5%, 81.9%, and 56.1%, respectively.

CONCLUSIONS

We determined the prevalences of hyperuricemia and electrolyte abnormalities in Japanese patients with CKD using data from a nationwide cohort study.

Prevalence of anemia in patients with chronic kidney disease in Japan: A nationwide, cross-sectional cohort study using data from the Japan Chronic Kidney Disease Database (J-CKD-DB)

BACKGROUND

The Japan Chronic Kidney Disease Database (J-CKD-DB) is a nationwide clinical database of patients with chronic kidney disease (CKD) based on electronic health records. The objective of this study was to assess the prevalence of anemia and the utilization rate of erythropoiesis-stimulating agents (ESAs) in Japanese patients with CKD.

METHODS

In total, 31,082 adult outpatients with estimated glomerular filtration rates of 5-60 ml/min/1.73 m2 in seven university hospitals were included this analysis. The proportions of patients with CKD stages G3b, G4, and G5 were 23.5%, 7.6%, and 3.1%, respectively.

RESULTS

The mean (standard deviation) hemoglobin level of male patients was 13.6 (1.9) g/dl, which was significantly higher than the mean hemoglobin level of female patients (12.4 (1.6) g/dl). The mean (standard deviation) hemoglobin levels were 11.4 (2.1) g/dl in patients with CKD stage G4 and 11.2 (1.8) g/dl in patients with CKD stage G5. The prevalences of anemia were 40.1% in patients with CKD stage G4 and 60.3% in patients with CKD stage G5. Logistic regression analysis showed that diagnoses of CKD stage G3b (adjusted odds ratio [95% confidence interval]: 2.32 [2.09-2.58]), G4 (5.50 [4.80-6.31]), and G5 (9.75 [8.13-11.7]) were associated with increased prevalence of anemia. The utilization rates of ESAs were 7.9% in patients with CKD stage G4 and 22.4% in patients with CKD stage G5.

CONCLUSIONS

We determined the prevalence of anemia and utilization rate of ESAs in Japanese patients with CKD using data from a nationwide cohort study.

The dawning of the digital era in the management of hypertension

Awareness, treatment, and control of hypertension are of the utmost importance in conquering stroke and cardiovascular disease. To reduce the global burden of hypertension, the Japanese Society of Hypertension (JSH) established the "JSH Future Plan" based on an increasing need to transform the strategy for combating hypertension. In addition to energizing conventional approaches in basic, translational, and clinical research, the application of rapidly evolving digital health technologies and artificial intelligence to hypertension healthcare and research (digital hypertension) holds promise for providing further insights into the pathophysiology and therapeutic targets and implementing predictive, personalized, and preemptive approaches in clinical practice. With great potential to revolutionize the landscape of hypertension, digital hypertension has some technical, legal, ethical, social, and financial issues to overcome. Given the multidisciplinary framework, digital hypertension requires comprehensive and strategic collaboration among industry, academia, and government to move forward toward the goal of "Future Medicine".

The Development of Medical Markup Language Version 4 as a Clinical Document Exchange Format for Nationwide EHR Systems

Medical Markup Language (MML) is a standard format for exchange of healthcare data among healthcare providers. Following the last major update (version 3), we developed new modules and discussed the requirements for the next major updates. Subsequently, in 2016 we released MML version 4 and used it to obtain clinical data from healthcare providers for a nationwide electronic health records (EHR) system. In this article we provide an overview of this major update of MML version 4 and discuss its interoperability for clinical data.

Establishment of the MID-NET® medical information database network as a reliable and valuable database for drug safety assessments in Japan

Purpose

To establish a new medical information database network (designated MID‐NET^®) to provide real‐world data for drug safety assessments in Japan.

Methods

This network was designed and developed by the Ministry of Health, Labour and Welfare and the Pharmaceuticals and Medical Devices Agency in collaboration with 23 hospitals from 10 healthcare organizations across Japan. MID‐NET^® is a distributed and closed network system that connects all collaborative organizations through a central data center. A wide variety of data are available for analyses, including clinical and administrative information. Several coding standards are used to standardize the data stored in MID‐NET^® to allow the integration of information originating from different hospitals. A rigorous and consistent quality management system was implemented to ensure that MID‐NET^® data are of high quality and meet Japanese regulatory standards (good post‐marketing study practice and related guidelines).

Results

MID‐NET^® was successfully established as a reliable and valuable medical information database and was officially launched in April 2018. High data quality with almost 100% consistency was confirmed between original data in hospitals and the data stored in MID‐NET^®. A major advantage is that approximately 260 clinical laboratory test results are available for analysis.

Conclusions

MID‐NET^® is expected to be a major data source for drug safety assessments in Japan. Experiences and best practices established in MID‐NET^® may provide a model for the future development of similar database networks.

Evaluating the impact of regulatory action on denosumab-induced hypocalcaemia in Japan

WHAT IS KNOWN AND OBJECTIVE

Since its introduction in April 2012, denosumab has been administered to approximately 7,300 patients as of August 2012, and 32 cases of serious hypocalcaemia after denosumab administration, including two deaths, have been reported in Japan. A Dear Healthcare Professional Letter of Rapid Safety Communication ('Blue letter') was released to warn about the risks of hypocalcaemia associated with denosumab. The goal of this study therefore was to measure the impact of regulatory action on denosumab-induced hypocalcaemia in Japan by using an electronic medical information database (MID).

METHODS

We used two different aggregated data sets based on MIDs (data sets one and two). The patients studied were those who were newly prescribed denosumab or zoledronic acid between April 2012 and September 2014. We assessed four indicators: (a) the proportion of patients with calcium supplementation at the initial denosumab treatment, (b) the proportion of patients who underwent a serum calcium test, (c) the average number of serum calcium tests performed and (d) the prevalence of hypocalcaemia. All indices were aggregated by every 3 months. To evaluate the impact of regulatory action, we used difference in difference (DID) analysis.

RESULTS AND DISCUSSION

The proportion of patients with calcium supplementation at the initial denosumab treatment increased year by year in both data sets. The average number of serum calcium tests increased year by year in data set two. There was a significant difference in the prevalence of hypocalcaemia in data set two. This suggests that the estimate of impact of the regulatory action may vary according to the database. In DID analysis, however, significant influences of the regulatory action on combination use with a calcium supplement were detected in both data sets.

WHAT IS NEW AND CONCLUSION

There was a significant influence on combination use of denosumab with vitamin D and/or calcium supplement in both data sets. That there was no apparent increase in the prevalence of denosumab-induced hypocalcaemia, suggests that the regulatory action had an impact in the clinical setting studied. Such regulatory actions may play an important role in the promotion of drug safety.

Comparing the Trends of Electronic Health Record Adoption Among Hospitals of the United States and Japan

The goal of this study is to examine the trends of Electronic Health Record (EHR) adoption among hospitals in Japan compared to those in the United States. Japan's nationwide survey of hospitals was utilized to extract the EHR adoption rates among Japanese hospitals. Comparable datasets from the Healthcare Information and Management System Society (HIMSS) and the American Hospital Association (AHA) were utilized to extract EHR adoption rates among U.S. hospitals. The trends of EHR adoption were stratified and analyzed by hospital size and hospital ownership status. As of 2014, the U.S. hospitals had a wider adoption of 'basic with clinical notes' EHRs compared to Japan (45.6% vs. 27.3%), but large hospitals (400+ beds) in Japan have shown a similar adoption rate of EHR systems than those of U.S. (65.6% vs. 68.5%). Governmental hospitals tend to be more advanced in EHR adoption than non-profit hospitals in Japan (53.0% vs. 21.5%). Non-profit hospitals show the highest adoption rate of 'basic' EHR systems in the U.S. as of 2014 (63.3%). Using the 'certified' definition of EHRs, the EHR adoption rate was close to 96% among U.S. hospitals as of 2016; however, updated EHR adoption data from Japanese hospitals has yet to be collected and published. U.S. and Japan have considerably increased EHR adoption among hospitals; however, this analysis indicates different trends of EHR adoption among hospitals by size and ownership status in both countries. Learnings from government programs supporting EHR adoption in the U.S. and Japan can be helpful in planning useful strategies for future hospital-oriented health IT policies in other developed nations.

Recommended configuration for personal health records by standardized data item sets for diabetes mellitus and associated chronic diseases: a report from a collaborative initiative by six Japanese associations

It is expected that a large amount of data related to diabetes and other chronic diseases will be generated. However, databases constructed without standardized data item sets can be limited in their usefulness. To address this, the Collaborative Committee of Clinical Informatization in Diabetes Mellitus was established in 2011 by the Japan Diabetes Society and Japan Association for Medical Informatics. The committee has developed core item sets and self-management item sets for diabetes mellitus, hypertension, dyslipidemia, and chronic kidney disease in collaboration with the Japanese Society of Hypertension, Japan Atherosclerosis Society, Japanese Society of Nephrology, and Japanese Society of Laboratory Medicine, as well as a mapping table that aligns the self-management item sets with the Japanese standardized codes for laboratory testing. The committee also determined detailed specifications for implementing the four self-management item sets in personal health record applications to facilitate risk stratification, the generation of alerts using information and communications technology systems, the avoidance of data input errors, and the generation of reminders to input the self-management item set data. The approach developed by the committee may be useful for combining databases for various purposes (such as for clinical studies, patient education, and electronic medical record systems) and for facilitating collaboration between personal health record administrators.

Recommended configuration for personal health records by standardized data item sets for diabetes mellitus and associated chronic diseases: A report from Collaborative Initiative by six Japanese Associations

It is expected that a large amount of data related to diabetes and other chronic diseases will be generated. However, databases constructed without standardized data item sets can be limited in their usefulness. To address this, the Collaborative Committee of Clinical Informatization in Diabetes Mellitus was established in 2011 by the Japan Diabetes Society and Japan Association for Medical Informatics. The committee has developed core item sets and self-management item sets for diabetes mellitus, hypertension, dyslipidemia, and chronic kidney disease in collaboration with the Japanese Society of Hypertension, Japan Atherosclerosis Society, Japanese Society of Nephrology, and Japanese Society of Laboratory Medicine, as well as a mapping table that aligns the self-management item sets with the Japanese standardized codes for laboratory testing. The committee also determined detailed specifications for implementing the four self-management item sets in personal health record (PHR) applications to facilitate risk stratification, the generation of alerts using information and communications technology systems, the avoidance of data input errors, and the generation of reminders to input the self-management item set data. The approach developed by the committee may be useful for combining databases for various purposes (such as for clinical studies, patient education, and electronic medical record systems) and for facilitating collaboration between PHR administrators.

Architecture of the Japan Ischemic Heart Disease Multimodal Prospective Data Acquisition for Precision Treatment (J-IMPACT) System

The utilization of electronic medical records and multimodal medical data is an ideal approach to build a real-time and precision registry type study with a smaller effort and cost, which may fill a gap between evidence-based medicine and the real-world clinical practice. The Japan Ischemic heart disease Multimodal Prospective data Acquisition for preCision Treatment (J-IMPACT) project aimed to build an clinical data registry system that electronically collects not only medical records, but also multimodal data, including coronary angiography and percutaneous coronary intervention (PCI) report, in standardized data formats for clinical studies.The J-IMPACT system comprises the standardized structured medical information exchange (SS-MIX), coronary angiography and intervention reporting system (CAIRS), and multi-purpose clinical data repository system (MCDRS) interconnected within the institutional network. In order to prove the concept, we acquired multimodal medical data of 6 consecutive cases that underwent PCI through the J-IMPACT system in a single center. Data items regarding patient background, laboratory data, prescriptions, and PCI/cardiac catheterization report were correctly acquired through the J-IMPACT system, and the accuracy of the multimodal data of the 4 categories was 100% in all 6 cases.The application of J-IMPACT system to clinical studies not only fills the gaps between randomized clinical trials and real-world medicine, but may also provide real-time big data that reinforces precision treatment for each patient.

Use of EHRs data for clinical research: Historical progress and current applications

The benefits of reusing EHR data for clinical research studies are numerous. They portend the opportunity to bring new therapies to patients sooner, potentially at a lower cost, and to accelerate learning health cycles-through faster data acquisition in clinical research studies. Metrics have proven that time can be saved, workflow and processes streamlined, and data quality increased significantly. Pilot projects and now actual investigational trials used for regulatory submissions have shown that these benefits support the transformation of clinical research by leveraging EHRs for research. Panelists at a recent collaborative focused on bridging clinical research and clinical care offered varying perspectives on how the latest standards and technologies could be leveraged to facilitate data transfer from EHR systems into clinical research databases, as well as the associated improvements in data quality. Panelists also discussed other avenues to leverage EHR in clinical research. Improvements and exciting possibilities notwithstanding, much work remains. Data ownership and access, attention to metadata and structured data for data sharing, and broader adoption of global standards are key areas for collaboration. With the steady increase in adoption of EHRs around the world, this is an excellent time for all stakeholders to work together and create an environment such that EHRs can be used more readily for research. The capacity for research can thus be increased to provide more high-quality information that will contribute to rapid continuous learning health systems from which all patients can benefit.

Development of a new seamless data stream from EMR to EDC system using SS-MIX2 standards applied for observational research in diabetes mellitus

Over the last decade, redundant entry of data in electronic medical records (EMR) for health care and electronic data capture (EDC) systems for research has been the typical medical research methodology. The corresponding data transcription this methodology requires not only increases the burden for clinician investigators and clinical research coordinators (CRCs), but it also decreases the quality of data. We designed and developed a new standards-based and platform-independent system to use data in the EMR to directly populate clinical data management systems in the EDC to eliminate the need for data transcription, streamline the clinical research process, and reduce clinician burden. Standardized structured medical information eXchange2 (SS-MIX2) was implemented along with the Integrating the Healthcare Enterprise (IHE) Retrieve Form for Data Capture (RFD) Integration Profile. Standards from Clinical Data Interchange Standards Consortium (CDISC) were used to define metadata for research data collection forms and as a means to standardize data exchange semantics. These standards and the associated methodology were applied to observational research in patients with diabetes mellitus. The system we developed complies with global requirements for regulated research. It provides a standard-based and platform-independent method that can serve to accelerate the cycle of a learning health system.

The cost-effectiveness of dulaglutide versus insulin glargine for the treatment of type 2 diabetes mellitus in Japan

AIMS

Dulaglutide is a new once weekly glucagon-like peptide-1 (GLP-1) receptor agonist administered via a disposable auto-injection pen for the management of type 2 diabetes mellitus (T2DM). The objective of this study was to estimate the cost-effectiveness of dulaglutide vs insulin glargine for the management of T2DM from a Japanese healthcare perspective, in accordance with recently approved Japanese Cost-Effectiveness Guidelines.

METHODS

The IQVIA CORE Diabetes Model (version 9) was used to estimate the long-term costs and effects of treatment with dulaglutide and insulin glargine. Direct comparative data from the Araki 2015 trial (NCT01584232) was used to inform the analysis. Costs associated with treatment and complications were derived from Japanese sources wherever possible and inflated to 2015 Japanese Yen (JPY). Utilities were based upon a European systematic review of diabetes utilities and adjusted for use in a Japanese population. One-way and probabilistic sensitivity analyses (OWSA and PSA) were conducted on all inputs and key modeling assumptions.

RESULTS

Dulaglutide 0.75 mg was associated with higher quality-adjusted life years (QALYs), life years (LYs), and total costs, compared to insulin glargine, resulting in an incremental cost-effectiveness ratio (ICER) of 416,280 JPY/QALY gained. Treatment with dulaglutide increased the time alive and free from diabetes-related complications by 4 months. OWSA and PSA indicated that results were robust to plausible variations in input parameters and modeling assumptions.

LIMITATIONS

Key limitations of this study are similar to other cost-utility analyses of diabetes, including the extrapolation of short-term clinical trial data into lifelong durations. In addition, due to the lack of robust published Japanese data, some values were derived from non-Japanese sources.

CONCLUSIONS

This analysis suggests that dulaglutide 0.75 mg may be a cost-effective treatment alternative to insulin glargine for patients with T2DM in Japan.

Design of and rationale for the Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System (J-DREAMS)

The "Japan Diabetes compREhensive database project based on an Advanced electronic Medical record System" is a registry of patients with diabetes in Japan. The characteristics of this registry include a clinical information input process using the template function of an electronic medical record (EMR) system [the standard diabetes management template (SDMT)], a standardized exchangeable information storage format [the Standardized Structured Medical Information eXchange 2 (SS-MIX2)], and a secure and efficient information extraction process [Multipurpose Clinical Data Repository System (MCDRS)]. Together, these characteristics enable efficient data input during routine patient consultations, efficient and exact data extraction from each facility, and the integration of data across different facilities even though these data were generated by EMR systems from different vendors. The SDMT collects clinical information including the type of diabetes, body height and weight, blood pressure, lifestyle, and comorbidities. Completing this template triggers the automatic collection of other information such as fundamental information (sex, year and month of birth, and facility), prescription information, and laboratory examination results. As the information from every routine consultation is saved with an anonymized patient ID, linked data can be used as panel data allowing longitudinal investigations. The data obtained from the registry will allow analyses, for exmaple, mortality and morbidity risk, by various characteristics or drug types and may reveal unmet needs that inform future diabetes care.

Validity of diagnoses, procedures, and laboratory data in Japanese administrative data

Background

Validation of recorded data is a prerequisite for studies that utilize administrative databases. The present study evaluated the validity of diagnoses and procedure records in the Japanese Diagnosis Procedure Combination (DPC) data, along with laboratory test results in the newly-introduced Standardized Structured Medical Record Information Exchange (SS-MIX) data.

Methods

Between November 2015 and February 2016, we conducted chart reviews of 315 patients hospitalized between April 2014 and March 2015 in four middle-sized acute-care hospitals in Shizuoka, Kochi, Fukuoka, and Saga Prefectures and used them as reference standards. The sensitivity and specificity of DPC data in identifying 16 diseases and 10 common procedures were identified. The accuracy of SS-MIX data for 13 laboratory test results was also examined.

Results

The specificity of diagnoses in the DPC data exceeded 96%, while the sensitivity was below 50% for seven diseases and variable across diseases. When limited to primary diagnoses, the sensitivity and specificity were 78.9% and 93.2%, respectively. The sensitivity of procedure records exceeded 90% for six procedures, and the specificity exceeded 90% for nine procedures. Agreement between the SS-MIX data and the chart reviews was above 95% for all 13 items.

Conclusion

The validity of diagnoses and procedure records in the DPC data and laboratory results in the SS-MIX data was high in general, supporting their use in future studies.

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Validity of DPC and SS-MIX data was tested using chart review results as references.

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Specificity of DPC diagnoses was high; sensitivity was low and varied by conditions.

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Procedure records in DPC data were highly sensitive and specific.

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Accuracy of SS-MIX laboratory data exceeded 95% in all 13 items examined.

Development of a novel algorithm for detecting glucocorticoid-induced diabetes mellitus using a medical information database

WHAT IS KNOWN AND OBJECTIVE

Glucocorticoid-induced diabetes mellitus (GIDM) increases the risk of diabetes mellitus (DM)-related complications but is generally difficult to detect in clinical settings. The criteria for diagnosing GIDM have not been established. Recently, medical information databases (MIDs) have been used in post-marketing surveillance (PMS) studies. We conducted a pharmacoepidemiological study to develop an algorithm for detecting GIDM using MID.

METHODS

We selected 1214 inpatients who were newly prescribed with a typical glucocorticoid, prednisolone, during hospitalization from 2008 to 2014 from an MID of Hamamatsu University Hospital in Japan. GIDM was screened based on fasting blood glucose (FBG) and haemoglobin A1c (HbA1c) levels according to the current Japan Diabetes Society (JDS) DM criteria, and its predictability was evaluated by an expert's review of medical records. We investigated further candidate screening factors using receiver operating characteristics analysis.

RESULTS

Sixty-three inpatients were identified by the JDS DM criteria. Of these, 33 patients were definitely diagnosed as having GIDM by expert's review (positive predictive value = 52·4%). To develop a highly predictive algorithm, we compared the characteristics of inpatients diagnosed with definite GIDM and those diagnosed as non-GIDM. The maximum levels of HbA1c in patients with GIDM were significantly higher than those of patients with non-GIDM (66·9 mmol/mol vs. 58·7 mmol/mol, P < 0·001). The patients with GIDM had significantly higher relative increase in maximum level of HbA1c (RIM-HbA1c) than those with non-GIDM (0·3 vs. 0·03, P < 0·001). However, we did not observe a significant difference in those of fasting blood glucose (FBG) levels. We applied the RIM-HbA1c as a second screening factor to improve the detection of GIDM. It showed that a 13% increase in RIM-HbA1c separated patients with from patients without GIDM.

WHAT IS NEW AND CONCLUSIONS

Patients with GIDM had significantly higher RIM-HbA1c than patients with non-GIDM. There was a 13% increase in RIM-HbA1c in patients with GIDM compared to the others. Our detection algorithm for GIDM using an MID achieved high sensitivity and specificity, and was superior to one based only on the current JDS DM criteria. Our results suggest that monitoring changes in HbA1c levels is important for detecting GIDM and adds to current diagnostic criteria for type 2 DM.

Comparison of Procedure-Based and Diagnosis-Based Identifications of Severe Sepsis and Disseminated Intravascular Coagulation in Administrative Data

BACKGROUND

Diagnoses recorded in administrative databases have limited utility for accurate identification of severe sepsis and disseminated intravascular coagulation (DIC). We evaluated the performance of alternative identification methods that use procedure records.

METHODS

We obtained data for adult patients admitted to intensive care units in three hospitals during a 1-year period. Severe sepsis and DIC were identified by three means: laboratory data, diagnoses, and procedures. Using laboratory data as a reference, the sensitivity and specificity of procedure-based methods and diagnosis-based methods were compared.

RESULTS

Of 595 intensive care unit admissions, 212 (35.6%) and 81 (13.6%) were identified as severe sepsis and DIC, respectively, using laboratory data. The sensitivity of procedure-based methods for identifying severe sepsis was 64.2%, and the specificity was 65.3%. Two diagnosis-based methods -the Angus and Martin algorithms- exhibited sensitivities of 21.7% and 14.6% and specificities of 98.7% and 99.5%, respectively, for severe sepsis. For DIC, the sensitivity of procedure-based methods was 55.6%, and the specificity was 67.1%, and the sensitivity and specificity of diagnosis-based methods were 35.8% and 98.2%, respectively.

CONCLUSIONS

Procedure-based methods were more sensitive and less specific than diagnosis-based methods in identifying severe sepsis and DIC. Procedure records could improve disease identification in administrative databases.

A Querying Method over RDF-ized Health Level Seven v2.5 Messages Using Life Science Knowledge Resources

Background

Health level seven version 2.5 (HL7 v2.5) is a widespread messaging standard for information exchange between clinical information systems. By applying Semantic Web technologies for handling HL7 v2.5 messages, it is possible to integrate large-scale clinical data with life science knowledge resources.

Objective

Showing feasibility of a querying method over large-scale resource description framework (RDF)-ized HL7 v2.5 messages using publicly available drug databases.

Methods

We developed a method to convert HL7 v2.5 messages into the RDF. We also converted five kinds of drug databases into RDF and provided explicit links between the corresponding items among them. With those linked drug data, we then developed a method for query expansion to search the clinical data using semantic information on drug classes along with four types of temporal patterns. For evaluation purpose, medication orders and laboratory test results for a 3-year period at the University of Tokyo Hospital were used, and the query execution times were measured.

Results

Approximately 650 million RDF triples for medication orders and 790 million RDF triples for laboratory test results were converted. Taking three types of query in use cases for detecting adverse events of drugs as an example, we confirmed these queries were represented in SPARQL Protocol and RDF Query Language (SPARQL) using our methods and comparison with conventional query expressions were performed. The measurement results confirm that the query time is feasible and increases logarithmically or linearly with the amount of data and without diverging.

Conclusions

The proposed methods enabled query expressions that separate knowledge resources and clinical data, thereby suggesting the feasibility for improving the usability of clinical data by enhancing the knowledge resources. We also demonstrate that when HL7 v2.5 messages are automatically converted into RDF, searches are still possible through SPARQL without modifying the structure. As such, the proposed method benefits not only our hospitals, but also numerous hospitals that handle HL7 v2.5 messages. Our approach highlights a potential of large-scale data federation techniques to retrieve clinical information, which could be applied as applications of clinical intelligence to improve clinical practices, such as adverse drug event monitoring and cohort selection for a clinical study as well as discovering new knowledge from clinical information.

Healthcare Databases in Thailand and Japan: Potential Sources for Health Technology Assessment Research

Background

Health technology assessment (HTA) has been continuously used for value-based healthcare decisions over the last decade. Healthcare databases represent an important source of information for HTA, which has seen a surge in use in Western countries. Although HTA agencies have been established in Asia-Pacific region, application and understanding of healthcare databases for HTA is rather limited. Thus, we reviewed existing databases to assess their potential for HTA in Thailand where HTA has been used officially and Japan where HTA is going to be officially introduced.

Method

Existing healthcare databases in Thailand and Japan were compiled and reviewed. Databases’ characteristics e.g. name of database, host, scope/objective, time/sample size, design, data collection method, population/sample, and variables were described. Databases were assessed for its potential HTA use in terms of safety/efficacy/effectiveness, social/ethical, organization/professional, economic, and epidemiological domains. Request route for each database was also provided.

Results

Forty databases– 20 from Thailand and 20 from Japan—were included. These comprised of national censuses, surveys, registries, administrative data, and claimed databases. All databases were potentially used for epidemiological studies. In addition, data on mortality, morbidity, disability, adverse events, quality of life, service/technology utilization, length of stay, and economics were also found in some databases. However, access to patient-level data was limited since information about the databases was not available on public sources.

Conclusion

Our findings have shown that existing databases provided valuable information for HTA research with limitation on accessibility. Mutual dialogue on healthcare database development and usage for HTA among Asia-Pacific region is needed.

Overview of recent trans-institutional health network projects in Japan and Germany

Worldwide populations are aging and countries have to prepare for the effects of demographic change in health care. Health information exchange (HIE), which is the process of moving patient information across health care providers electronically, can help overcome health data fragmentation and open opportunities to improve patient care in terms of quality, economy and efficiency. Since Japan and Germany are among the first countries strongly impacted by demographic changes of aging populations, we report on current developments about health information systems carrying out HIE based on case studies in both countries. Four projects that address the improvement of HIE within a defined region have been selected and investigated: the German project of the Lower Saxony Bank of Health and the Japanese projects Chiba ITnet, Nagasaki AjisaiNet and the National Disaster and Backup System of Japan. The project descriptions are based on relevant English publications, on-site visits and interviews with developers and users. The projects are introduced in terms of their basic architecture and implementation, their present status and future objectives. The projects' developments are still in progress and all have to cope with significant challenges before they will be able to provide a fully working trans-institutional health network solution.

Burden on university hospitals of handling portable data for imaging (PDI) media

BACKGROUND

Portable Data for Imaging (PDI) is regularly used as a guideline for sharing medical imaging data between hospitals and other medical institutions. When a patient is referred to another location, the patient almost always brings PDI media on a CD or DVD. However, problems often occur when trying to view images on PDI discs inserted into computer terminals, and it is more efficient to view images on the hospitals' own picture archiving and communication system (PACS). On the request of doctors, it has become a routine practice to import PDI data to the PACS of the referred hospital.

OBJECTIVE

The aim of this study was to analyze the increase in PDI image importing and investigate methods for reducing the burden caused by importing images.

METHODS

We compiled representative data on image importing over time and analyzed the test modalities, number of images, volume of data, and referring hospital or medical clinic from which the data originated.

RESULTS

The amount of PDI images imported to the PACS has risen despite no large increase in the number of patients. Currently, images imported from PDI media make up 22.8% of the total number of images stored in the PACS. The images come from a diverse array of hospitals (184 hospitals) and 82% are essential for medical care. The total annual expenditure associated with PDI data management is estimated to be 98,300 USD.

CONCLUSION

The spreading use of the PDI guideline has led to a dramatic increase in data image sharing in the field of healthcare. While this has great benefits for patients and doctors, it is also associated with a greater cost and an overall burden for hospitals. These results indicate the need for a system to enable many hospitals and clinics to participate in image sharing at a cheaper cost.

The trends in EMR and CPOE adoption in Japan under the national strategy

PURPOSE

We evaluate the status of health information system (HIS) adoption (In this paper, "HIS" means electronic medical record system (EMR) and computerized provider order entry system (CPOE)). We also evaluate the affect of the policies of Japanese government.

METHODS

The status of HIS adoption in Japan from 2002 to 2011 was investigated using reports from complete surveys of all medical institutions conducted by the Ministry of Health, Labour and Welfare (MHLW). HIS-related budgets invested by the Japanese government from 2000 to 2008 were surveyed mainly using literatures and administrative documents of the Japanese government (MHLW and Ministry of Economy, Trade and Industry).

RESULTS

The rates of HIS adoption in Japan in 2011 were: 20.9% for the rate of EMR adoption in clinics, 20.1% for the rate of EMR adoption and 36.6% for the rate of CPOE adoption in hospitals. In hospitals, the rate of EMR and CPOE adoption were 51.5% and 78.6% in 822 large hospitals (400 or more beds), 27.3% and 52.1% in 1832 medium hospitals (200-399 beds), and 13.5% and 26.0% in 5951 small hospitals (less than 200 beds), respectively. Japan has a large number of medical institutions (99,547 clinics and 8605 hospitals) with a low rate of EMR adoption in clinics and a high rate of HIS adoption in hospitals. The national budget to expand HIS use was implemented for medium and large hospitals mainly. The policy target of New IT Reform Strategy was not achieved.

CONCLUSION

The rate of HIS adoption in Japanese medium and large hospitals is high compared to small hospitals and clinics, and this is attributable to the fact that the Japanese government placed the target for HIS adoption on key hospitals with a large number of beds and concentrated budget investment in those hospitals. Besides, legal approval of EMR and the introduction of Diagnostic Procedure Combination system facilitated EMR adoption. There is less financial support for small hospitals than medium and large hospitals. The low rate of EMR adoption in clinics stems from the facts that there was little subsidies or incentives in the national remuneration for medical services, lack of cooperation from medical associations, and a failed attempt to mandate computerization of medical accounting (medical billing). Giving financial incentives is an effective means of raising EMR adoption rate. For wide usage of HIS, more financial support and incentive may be necessary for small hospitals and clinics.

Biomedical informatics--a confluence of disciplines?

BACKGROUND

Biomedical informatics is a broad discipline that borrows many methods and techniques from other disciplines.

OBJECTIVE

To reflect a) on the character of biomedical informatics and to determine whether it is multi-disciplinary or inter-disciplinary; b) on the question whether biomedical informatics is more than the sum of its supporting disciplines and c) on the position of biomedical informatics with respect to related disciplines.

METHOD

Inviting an international group of experts in biomedical informatics and related disciplines on the occasion of the 50th anniversary of Methods of Information in Medicine to present their viewpoints.

RESULTS AND CONCLUSIONS

This paper contains the reflections of a number of the invited experts on the character of biomedical informatics. Most of the authors agree that biomedical informatics is an interdisciplinary field of study where researchers with different scientific backgrounds alone or in combination carry out research. Biomedical informatics is a very broad scientific field and still expanding, yet comprised of a constructive aspect (designing and building systems). One author expressed that the essence of biomedical informatics, as opposed to related disciplines, lies in the modelling of the biomedical content. Interdisciplinarity also has consequences for education. Maintaining rigid disciplinary structures does not allow for sufficient adaptability to capitalize on important trends nor to leverage the influences these trends may have on biomedical informatics. It is therefore important for students to become aware of research findings in related disciplines. In this respect, it was also noted that the fact that many scientific fields use different languages and that the research findings are stored in separate bibliographic databases makes it possible that potentially connected findings will never be linked, despite the fact that these findings were published. Bridges between the sciences are needed for the success of biomedical informatics.