Changes in Demand Volume and Patient/Health Care Provider Characteristics of First-Time Telehealth Users: A Comparative Analysis Before and After the COVID-19 Policy Response Using the Administrative Claims Database.

Introduction: The COVID-19 pandemic has led to a decrease in demand for medical services in Japan, but the utilization of telehealth, which the Japanese government has recently promoted, has seen a temporary increase. This study aims to analyze the trend of telehealth utilization and changes in patient characteristics following the policy response to COVID-19. Methods: This retrospective study analyzed data from 26,152 adult patients who used telehealth for the first time between April 2019 and April 2021 in Mie Prefecture, Japan. An interrupted time series analysis was conducted to evaluate changes in the number of first-time patients before and after April 2020. Results: The number of telehealth users increased by 111.87% after April 2020, but the trend showed a declining slope thereafter. Patient characteristics and disease types showed different trends. The percentage of patients choosing a hospital over a clinic increased for the first time. Conclusions: After the policy response to COVID-19, the number of first-time telehealth users overall increased immediately, but gradually showed a declining trend. However, some diseases have shown both an immediate increase and a continued upward trend in telehealth utilization. Patients with these diseases may be candidates for adopting telehealth services in clinical settings.

Monthly trends and seasonality of hemodialysis treatment and outcomes of newly initiated patients from the national database (NDB) of Japan.

BACKGROUND: The numbers of patients treated with hemodialysis (HD) in Japan are currently quantified by manual survey. As this method requires much effort from medical institutions and cannot achieve 100% response, a more practical method is required. We aimed to establish a novel method for determining the static and dynamic numbers of patients treated with HD. METHODS: This observational study used the national medical billing database (termed NDB) of Japan, based on the records of the universal healthcare insurance system. Medical billing data registered in the NDB between April 2011 and March 2015 were analyzed. From 130 billion records, we extracted and analyzed records of patients who had undergone HD at least once per month. Patients' monthly condition was classified as newly initiated HD, chronic HD, or presumed death, using conditional expressions. We also investigated renal outcome and presumed survival in newly initiated HD patients. RESULTS: In the last month of the study period, 274,100 patients were identified as receiving chronic HD, which is estimated as > 95% of the number of these patients identified in the manual survey so far. The monthly data showed clear seasonality in the incidence of transient HD, which increased in winter and decreased in summer. CONCLUSION: Analysis of a large national database revealed a significant increase in transient HD in winter and decrease in summer. Applied to additional epidemiological exploratory studies or clinical research, this analytical technique would enable collection of the dynamics of almost all HD patients nationwide.

Predicting demand for long-term care using Japanese healthcare insurance claims data.

BACKGROUND: Driven by the rapid aging of the population, Japan introduced public long-term care insurance to reinforce healthcare services for the elderly in 2000. Precisely predicting future demand for long-term care services helps authorities to plan and manage their healthcare resources and citizens to prevent their health status deterioration. METHODS: This paper presents our novel study for developing an effective model to predict individual-level future long-term care demand using previous healthcare insurance claims data. We designed two discriminative models and subsequently trained and validated the models using three learning algorithms with medical and long-term care insurance claims and enrollment records, which were provided by 170 regional public insurers in Gifu, Japan. RESULTS: The prediction model based on multiclass classification and gradient-boosting decision tree achieved practically high accuracy (weighted average of Precision, 0.872; Recall, 0.878; and F-measure, 0.873) for up to 12 months after the previous claims. The top important feature variables were indicators of current health status (e.g., current eligibility levels and age), risk factors to worsen future healthcare status (e.g., dementia), and preventive care services for improving future healthcare status (e.g., training and rehabilitation). CONCLUSIONS: The intensive validation tests have indicated that the developed prediction method holds high robustness, even though it yields relatively lower accuracy for specific patient groups with health conditions that are hard to distinguish.

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data.

BACKGROUND: Heart failure is one of the leading causes of hospitalization in the United States. Advances in big data solutions allow for storage, management, and mining of large volumes of structured and semi-structured data, such as complex healthcare data. Applying these advances to complex healthcare data has led to the development of risk prediction models to help identify patients who would benefit most from disease management programs in an effort to reduce readmissions and healthcare cost, but the results of these efforts have been varied. The primary aim of this study was to develop a 30-day readmission risk prediction model for heart failure patients discharged from a hospital admission. METHODS: We used longitudinal electronic medical record data of heart failure patients admitted within a large healthcare system. Feature vectors included structured demographic, utilization, and clinical data, as well as selected extracts of un-structured data from clinician-authored notes. The risk prediction model was developed using deep unified networks (DUNs), a new mesh-like network structure of deep learning designed to avoid over-fitting. The model was validated with 10-fold cross-validation and results compared to models based on logistic regression, gradient boosting, and maxout networks. Overall model performance was assessed using concordance statistic. We also selected a discrimination threshold based on maximum projected cost saving to the Partners Healthcare system. RESULTS: Data from 11,510 patients with 27,334 admissions and 6369 30-day readmissions were used to train the model. After data processing, the final model included 3512 variables. The DUNs model had the best performance after 10-fold cross-validation. AUCs for prediction models were 0.664 ± 0.015, 0.650 ± 0.011, 0.695 ± 0.016 and 0.705 ± 0.015 for logistic regression, gradient boosting, maxout networks, and DUNs respectively. The DUNs model had an accuracy of 76.4% at the classification threshold that corresponded with maximum cost saving to the hospital. CONCLUSIONS: Deep learning techniques performed better than other traditional techniques in developing this EMR-based prediction model for 30-day readmissions in heart failure patients. Such models can be used to identify heart failure patients with impending hospitalization, enabling care teams to target interventions at their most high-risk patients and improving overall clinical outcomes.

Characterization of a Very Short Meq Protein Isoform in a Marek's Disease Virus Strain in Japan.

Marek's disease virus (MDV) causes malignant lymphoma (Marek's disease; MD) in chickens. The Meq protein is essential for tumorigenesis since it regulates the expression of host and viral genes. Previously, we reported that the deletion of the short isoform of Meq (S-Meq) decreases the pathogenicity of MDV. Recently, we identified a further short isoform of Meq (very short isoform of Meq, VS-Meq) in chickens with MD in Japan. A 64-amino-acid deletion was confirmed at the C-terminus of VS-Meq. We measured the transcriptional regulation by VS-Meq in three gene promoters to investigate the effect of VS-Meq on protein function. Wild-type VS-Meq decreased the transrepression of the pp38 promoter but did not alter the transactivation activity of the Meq and Bcl-2 promoters. The deletion in VS-Meq did not affect the activity of the pp38 promoter but enhanced the transactivation activities of the Meq and Bcl-2 promoters. Collectively, the deletion of VS-Meq potentially enhanced the activity of the Meq promoter, while other amino acid sequences in wild-type VS-Meq seemed to affect the weak transrepression of the pp38 promoter. Further investigation is required to clarify the effects of these changes on pathogenicity.

In Vivo Characterization of the Anti-Glutathione S-Transferase Antibody Using an In Vitro Mite Feeding Model.

Poultry red mites (Dermanyssus gallinae, PRMs), tropical fowl mites (Ornithonyssus bursa, TFMs), and northern fowl mites (O. sylviarum, NFMs) are blood-feeding pests that debilitate poultry worldwide. Glutathione S-transferase (GST) plays an important role in the detoxification and drug metabolism of mites. However, research on avian mite GSTs as vaccine antigens is still lacking. Therefore, we aimed to evaluate the potential of avian mite GSTs for vaccine development. We identified GST genes from TFMs and NFMs. We prepared recombinant GST (rGST) from TFMs, NFMs, and PRMs, and assessed their protein functions. Moreover, we evaluated the cross-reactivity and acaricidal effect of immune plasma against each rGST on TFMs, NFMs, and PRMs. The deduced amino acid sequences of GSTs from TFMs and NFMs were 80% similar to those of the PRMs. The rGSTs exhibited catalytic activity in conjugating glutathione to the 1-chloro-2,4-dinitrobenzene substrate. Immune plasma against each rGST showed cross-reactivity with rGST from different mite species. Moreover, the survival rate of PRMs fed with immune plasma against the rGST of TFMs and NFMs was significantly lower than that of the control plasma. These results demonstrate the potential application of GST as an antigen for the development of a broad-spectrum vaccine against avian mites.

Virtual patient identifier (vPID): Improving patient traceability using anonymized identifiers in Japanese healthcare insurance claims database.

Objective: Japan's national-level healthcare insurance claims database (NDB) is a collective database that contains the entire information on healthcare services being provided to all citizens. However, existing anonymized identifiers (ID1 and ID2) have a poor capability of tracing patients' claims in the database, hindering longitudinal analyses. This study presents a virtual patient identifier (vPID), which we have developed on top of these existing identifiers, to improve the patient traceability. Methods: vPID is a new composite identifier that intensively consolidates ID1 and ID2 co-occurring in an identical claim to allow to collect claims of each patient even though its ID1 or ID2 may change due to life events or clerical errors. We conducted a verification test with prefecture-level datasets of healthcare insurance claims and enrollee history records, which allowed us to compare vPID with the ground truth, in terms of an identifiability score (indicating a capability of distinguishing a patient's claims from another patient's claims) and a traceability score (indicating a capability of collecting claims of an identical patient). Results: The verification test has clarified that vPID offers significantly higher traceability scores (0.994, Mie; 0.997, Gifu) than ID1 (0.863, Mie; 0.884, Gifu) and ID2 (0.602, Mie; 0.839, Gifu), and comparable (0.996, Mie) and lower (0.979, Gifu) identifiability scores. Discussion: vPID is seemingly useful for a wide spectrum of analytic studies unless they focus on sensitive cases to the design limitation of vPID, such as patients experiencing marriage and job change, simultaneously, and same-sex twin children. Conclusion: vPID successfully improves patient traceability, providing an opportunity for longitudinal analyses that used to be practically impossible for NDB. Further exploration is also necessary, in particular, for mitigating identification errors.

Characterization of cysteine proteases from poultry red mite, tropical fowl mite, and northern fowl mite to assess the feasibility of developing a broadly efficacious vaccine against multiple mite species.

Infestation with poultry red mites (PRM, Dermanyssus gallinae) causes anemia, reduced egg production, and death in serious cases, resulting in significant economic losses to the poultry industry. As a novel strategy for controlling PRMs, vaccine approaches have been focused upon and several candidate vaccine antigens against PRMs have been reported. Tropical (TFM, Ornithonyssus bursa) and northern (NFM, Ornithonyssus sylviarum) fowl mites are also hematophagous and cause poultry industry problems similar to those caused by PRM. Therefore, ideal antigens for anti-PRM vaccines are molecules that cross-react with TFMs and NFMs, producing pesticidal effects similar to those against PRMs. In this study, to investigate the potential feasibility of developing vaccines with broad efficacy across mite species, we identified and characterized cysteine proteases (CPs) of TFMs and NFMs, which were previously reported to be effective vaccine antigens of PRMs. The open reading frames of CPs from TFMs and NFMs had the same sequences, which was 73.0% similar to that of PRMs. Phylogenetic analysis revealed that the CPs of TFMs and NFMs clustered in the same clade as CPs of PRMs. To assess protein functionality, we generated recombinant peptidase domains of CPs (rCP-PDs), revealing all rCP-PDs showed CP-like activities. Importantly, the plasma obtained from chickens immunized with each rCP-PD cross-reacted with rCP-PDs of different mites. Finally, all immune plasma of rCP-PDs reduced the survival rate of PRMs, even when the plasma was collected from chickens immunized with rCP-PDs derived from TFM and NFM. Therefore, CP antigen is a promising, broadly efficacious vaccine candidate against different avian mites.

Potential of ferritin 2 as an antigen for the development of a universal vaccine for avian mites, poultry red mites, tropical fowl mites, and northern fowl mites.

Introduction: Poultry red mites (PRMs, Dermanyssus gallinae), blood-sucking ectoparasites, are a threat to the poultry industry because of reduced production caused by infestation. In addition, tropical fowl mites (TFMs, Ornithonyssus bursa) and northern fowl mites (NFMs, Ornithonyssus sylviarum) are hematophagous, distributed in various regions, genetically and morphologically close to PRMs, and cause similar problems to the poultry industry. Vaccine approaches have been studied for PRM control, and several molecules have been identified in PRMs as candidates for effective vaccine antigens. The development of an anti-PRM vaccine as a universal vaccine with broad efficacy against avian mites could improve the productivity of poultry farms worldwide. Molecules that are highly conserved among avian mites and have critical functions in the physiology and growth of mites could be ideal antigen candidates for the development of universal vaccines. Ferritin 2 (FER2), an iron-binding protein, is critical for the reproduction and survival of PRMs and has been reported as a useful vaccine antigen for the control of PRMs and a candidate for the universal vaccine antigen in some tick species. Method and results: Herein, we identified and characterized FER2 in TFMs and NFM. Compared with the sequence of PRM, the ferroxidase centers of the heavy chain subunits were conserved in FER2 of TFMs and NFMs. Phylogenetic analysis revealed that FER2 belongs to clusters of secretory ferritins of mites and other arthropods. Recombinant FER2 (rFER2) proteins from PRMs, TFMs, and NFMs exhibited iron-binding abilities. Immunization with each rFER2 induced strong antibody responses in chickens, and each immune plasma cross-reacted with rFER2 from different mites. Moreover, mortality rates of PRMs fed with immune plasma against rFER2 from TFMs or NFMs, in addition to PRMs, were higher than those of control plasma. Discussion: rFER2 from each avian mite exhibited anti-PRM effects. This data suggests that it has the potential to be used as an antigen candidate for a universal vaccine against avian mites. Further studies are needed to access the usefulness of FER2 as a universal vaccine for the control of avian mites.

The Association Between Telehealth Utilization and Policy Responses on COVID-19 in Japan: Interrupted Time-Series Analysis.

BACKGROUND: Telehealth using telephones or online communication is being promoted as a policy initiative in several countries. However, there is a lack of research on telehealth utilization in a country such as Japan that offers free access to medical care and regulates telehealth provision-particularly with respect to COVID-19. OBJECTIVE: The present study aimed to clarify telehealth utilization, the characteristics of patients and medical institutions using telehealth, and the changes to telehealth in Japan in order to support the formulation of policy strategies for telehealth provision. METHODS: Using a medical administrative claim database of the National Health Insurance and Advanced Elderly Medical Service System in Mie Prefecture, we investigated patients who used telehealth from January 2017 to September 2021. We examined telehealth utilization with respect to both patients and medical institutions, and we determined their characteristics. Using April 2020 as the reference time point for COVID-19, we conducted an interrupted time-series analysis (ITSA) to assess changes in the monthly proportion of telehealth users to beneficiaries. RESULTS: The number of telehealth users before the reference time point was 13,618, and after the reference time point, it was 28,853. Several diseases and conditions were associated with an increase in telehealth utilization. Telehealth consultations were mostly conducted by telephone and for prescriptions. The ITSA results showed a sharp increase in the proportion of telehealth use to beneficiaries after the reference time point (rate ratio 2.97; 95% CI 2.14-2.31). However, no apparent change in the trend of increasing or decreasing telehealth use was evident after the reference time point (rate ratio 1.00; 95% CI 1.00-1.01). CONCLUSIONS: We observed a sharp increase in telehealth utilization after April 2020, but no change in the trend of telehealth use was evident. We identified changes in the characteristics of patients and providers using telehealth.

Prevalence of hypertensive diseases and treated hypertensive patients in Japan: A nationwide administrative claims database study.

We investigated the prevalence of hypertensive patients and treated hypertensive patients using a Japanese nationwide administrative claims database. We analyzed national database data from 2014, including all claims data, provided by the Ministry of Health, Labour and Welfare of Japan. Hypertensive diseases were identified using Japanese standardized disease codes. Among hypertensive patients, treated hypertensive patients were defined by the prescription of any antihypertensive medication, identified using national health insurance price listing codes. We calculated and compared the number and age-adjusted prevalence of hypertensive patients and treated hypertensive patients by prefecture and the proportion of these patients by the size of medical facilities. In 2014, approximately 27 million Japanese people were identified as hypertensive, among which 89.6% were treated. The age-adjusted prevalence of hypertensive patients (per 100,000 persons) among women and men was 21,414 and 21,084, respectively. The age-adjusted prevalence of treated hypertensive patients (per 100,000 persons) among women and men was 19,118 and 18,974, respectively. While the prevalence of hypertensive and treated hypertensive patients varied geographically, the prevalence remained similar between the sexes. Approximately 59% of hypertensive patients visited clinics (0 to 19 beds) in Japan. In Japan, 27 million people were diagnosed with hypertensive diseases, and approximately 90% of these patients were treated with any antihypertensive medication in 2014. The distribution of hypertensive patients varied geographically throughout Japan.

Effect of Insertion and Deletion in the Meq Protein Encoded by Highly Oncogenic Marek's Disease Virus on Transactivation Activity and Virulence.

Marek's disease virus (MDV) causes malignant lymphoma in chickens (Marek's disease, MD). Although MD is currently controlled by vaccination, MDV strains have continuously increased in virulence over the recent decades. Polymorphisms in Meq, an MDV-encoded oncoprotein that serves as a transcription factor, have been associated with the enhanced virulence of the virus. In addition, insertions and deletions in Meq have been observed in MDV strains of higher virulence, but their contribution to said virulence remains elusive. In this study, we investigated the contribution of an insertion (L-Meq) and a deletion in the Meq gene (S-Meq) to its functions and MDV pathogenicity. Reporter assays revealed that both insertion and deletion enhanced the transactivation potential of Meq. Additionally, we generated RB-1B-based recombinant MDVs (rMDVs) encoding each Meq isoform and analyzed their pathogenic potential. rMDV encoding L-Meq indueced the highest mortality and tumor incidence in infected animals, whereas the rMDV encoding S-Meq exhibited the lowest pathogenicity. Thus, insertion enhanced the transactivation activity of Meq and MDV pathogenicity, whereas deletion reduced pathogenicity despite having increased transactivation activity. These data suggest that other functions of Meq affect MDV virulence. These data improve our understanding of the mechanisms underlying the evolution of MDV virulence.

Retrieving and Analyzing Hospital Service Suspensions from Regional Healthcare Insurance Claims Data.

The geographical imbalance of the healthcare workforce is a social problem in Japan. Except for big cities, hospitals have difficulties in securing a sufficient workforce to offer healthcare services stably. For local government, hospital service suspensions are potentially an essential indicator to figure out the capacity of the regional healthcare supply. This paper proposes an algorithm that automatically identifies and classifies hospital service suspensions from insurance claims data, based on periodicity and similarity. To verify the effectiveness, we have applied the algorithm to the insurance claim dataset, which has been provided 91 regional public insurers in Japan. The case studies have confirmed that the proposed algorithm has presented an evidential picture of hospital service suspensions, which is potentially useful to understand the actual capacity of healthcare service supply in regions.

Indications and classes of outpatient antibiotic prescriptions in Japan: A descriptive study using the national database of electronic health insurance claims, 2012-2015.

OBJECTIVES: To evaluate condition-specific antibiotic prescription rates and the appropriateness of antibiotic use in outpatient settings in Japan. METHODS: Using Japan's national administrative claims database, all outpatient visits with infectious disease diagnoses were linked to reimbursed oral antibiotic prescriptions. Prescription rates stratified by age, sex, prefecture, and antibiotic category were determined for each infectious disease diagnosis. The proportions of any antibiotic prescription to all infectious disease visits and the proportions of first-line antibiotic prescriptions to all antibiotic prescriptions were calculated for each infectious disease diagnosis. RESULTS: Of the 659 million infectious disease visits between April 2012 and March 2015, antibiotics were prescribed in 266 million visits (704 prescriptions per 1000 population per year). Third-generation cephalosporins, macrolides, and quinolones accounted for 85.9% of all antibiotic prescriptions. Fifty-six percent of antibiotic prescriptions were directed toward infections for which antibiotics are generally not indicated. The diagnoses with frequent antibiotic prescription were bronchitis (184 prescriptions per 1000 population per year), viral upper respiratory infections (166), pharyngitis (104), sinusitis (52), and gastrointestinal infection (41), for which 58.3%, 40.6%, 58.9%, 53.9%, and 26.1% of visits antibiotics were prescribed, respectively. First-line antibiotics were rarely prescribed for pharyngitis (8.8%) and sinusitis (9.8%). More antibiotics were prescribed for children aged 0-9 years, adult women, and patients living in western Japan. CONCLUSIONS: Antibiotic prescription rates are high in Japan. Acute respiratory or gastrointestinal infections, which received the majority of the antibiotics generally not indicated, should be the main targets of antimicrobial stewardship intervention.

Novel Analytics Framework for Universal Healthcare Insurance Claims Database.

Medical insurance claims are useful data to offer a big-picture view and insight of a nation-wide healthcare system. Yet, formal description of the logic to analyze the claims has not been established. So far, we proposed a description scheme of analytics logic over claims database. In this paper, we propose a novel analytics framework based on the description scheme. By showing a case study, we demonstrate the effectiveness of the framework.

Enabling Patient Traceability Using Anonymized Personal Identifiers in Japanese Universal Health Insurance Claims Database.

Anonymization of medical data helps protect patient identities. However, with conventional anonymized personal identifiers it is difficult to trace patients, which hinders longitudinal analyses in insurance claim database. Herein, we describe the development of a method to identify unique patients by using partial equivalence relationships of multiple anonymized personal identifiers. By using two conventional anonymized personal identifiers, we have developed virtual patient identifiers (vPIDs) to indicate unique patients. To verify the effectiveness of the developed identifiers, we have applied vPIDs to a six-year dataset of national-level Japanese insurance claims dataset and a prefectural-level insurance claims dataset with enrollee master data. In addition, we have applied vPIDs to practical analyses of medical expenditures and doctor consultations. vPID has enabled the continued tracing of patients throughout the six-year study period, and demonstrated the validity of our method. Therefore, the proposed method can be used to improve patient traceability in insurance claims database.

Novel Analytics Framework for Universal Healthcare Insurance Database.

Medical insurance claims data is one of the most useful data sources that can offer a big-picture view of a nation-wide healthcare system. Form the viewpoint of medical policy planning, Japan's Ministry of Health, Labour and Welfare has been continuously collecting claims data. However, claims data in Japan has an ordered nested tuple format, and a method for describing the logic to analyze this form in a simple and clear manner has not been established yet. In the present work, we construct a novel analytics framework based on previous analyses that we conducted with medical researchers and design a UI that facilitates the construction of the processing logic in a simple and clear manner. By showing the execution result of typical analyses of claim data, we demonstrate the effectiveness of the developed tool.

Significant Improvement of Copper Dry Etching Property of a High-Pressure Hydrogen-Based Plasma by Nitrogen Gas Addition.

The characteristics of copper (Cu) isotropic dry etching using a hydrogen-based plasma generated at 13.3 kPa (100 Torr) were improved dramatically by simply introducing a moderate amount of N2 gas into the process atmosphere. A maximum Cu etch rate of 2.4 µm/min was obtained by nitrogen addition at a H2 mixture ratio (C H2 ) of 0.9 and an input power of 70 W. The etch rate for the optimally N2-added plasma was 8 times higher than that for the pure H2 plasma. The Cu etch rate increased with increasing input power. The maximum etch rate reached 3.1 µm/min at an input power of 100 W and a C H2 of 0.9. The surface roughness of the etched copper decreased as a result of optimum N2 addition. Furthermore, N2 addition also improved the etch selectivity between Cu and SiO2 such that the selectivity ratio reached 190. Finally, selective etching of a trench-patterned Si wafer with an electroplated Cu layer was demonstrated.