Data regarding fracture incidence according to fracture site, month, and age group obtained from the large public health insurance claim database in Japan

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.

Seasonal exacerbation of rheumatoid arthritis detected by big claims data analysis: A retrospective population study

OBJECTIVES

The objective of the study was to determine the seasonal changes in the initiation of biological disease-modifying antirheumatic drugs (bDMARDs) and methotrexate (MTX) using big claims data.

METHODS

We counted the monthly number of initial administrations of each bDMARD and MTX in patients with rheumatoid arthritis (RA) between April 2010 and March 2017. Data were collected from the National Database of Health Insurance Claims and Specific Health Checkups of Japan. This database covers more than 95% of Japanese citizens. Seasonal changes in the number of initiations were determined. Patient claims were also classified according to drugs, districts, gender, and ages.

RESULTS

The initiation of bDMARDs and MTX administration varied according to the season in a sine curve shape, with the highest numbers in May to July and the lowest numbers in November to January. The same changing pattern was observed among each bDMARD, district, gender, and age groups particularly when the number was on the higher side.

CONCLUSION

We noted an apparent seasonal change in the number of bDMARDs initiated, with a peak during spring, suggesting an exacerbation of RA in the spring in Japan. These changes are overlooked in daily practice and are only visible using big data.

The Age of Death in Japanese patients with type 2 and type 1 diabetes: A descriptive epidemiological study

This study clarified the age of death in patients with or without diabetes using the largest health insurance database in Japan. This population‐based retrospective cohort study was performed using the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) data. The ages of death between people with and without diabetes were compared. A total of 142,277,986 patients (74,488,962 women and 67,789,024 men) over 6 years, including 4,647,016 females, and 6,507,817 males with diabetes, were included. 2,786,071 females and 2,975,876 males died over 6 years, including 652,699 females and 954,655 males with diabetes. The average age of death in patients with diabetes was 2.6 years less than that of patients without diabetes. This descriptive epidemiological study illustrated the difference in age at death of patients with and without diabetes.

Evaluation of adrenaline auto-injector prescription profiles: A population-based, retrospective cohort study within the National Insurance Claims Database of Japan

BACKGROUND

Adrenaline is the first-line medication for managing anaphylaxis. A better understanding of prescription trends for adrenaline auto-injectors (AAIs) is important to improving patient care as well as information on health education interventions and medical guidelines. However, it has been difficult to gather comprehensive data in a sustainable manner. Thus, we aimed to investigate trends in AAI prescriptions in Japan.

METHODS

We searched the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), a unique and comprehensive database of health insurance claims, and investigated prescriptions for AAIs for all ages (April 2017 to March 2018). We assessed the annual number of prescriptions per person as well as prescription rates per 100,000 population per year by age, sex, and geographic region.

RESULTS

A total of 88,039 subjects (56,109 males, 31,930 female) and 116,758 devices (1.33 AAIs per patient per year) were prescribed AAIs at least once a year for all ages. The prescription rate for AAIs was 69.5 per 100,000 population-years. Patients aged 0-9 years were prescribed AAIs at the rate of 278.9 per 100,000 population-years. Patients aged 0-19 years were 6.4 times more likely to be prescribed AAIs than those over 20 years of age. Males were more frequently prescribed AAIs than females in all age groups, except for those aged 20-24 years. We also evaluated differences in prescription rates by geographic region.

CONCLUSIONS

This comprehensive evaluation revealed trends in AAI prescriptions, thus helping develop preventive strategies with respect to anaphylaxis in Japan.

Association between influenza and the incidence rate of new-onset type 1 diabetes in Japan

AIM

This study aimed to determine whether there is an association between influenza and new-onset type 1 diabetes.

MATERIALS AND METHODS

This population-based retrospective cohort study used data from the National Database of Health Insurance Claims and Specific Health Check-ups of Japan. Influenza was defined based on drug prescriptions and the onset of type 1 diabetes was defined using specific medical codes indicating a diagnosis of type 1 diabetes. The incidence rate ratio of new-onset type 1 diabetes within 180 days after an influenza diagnosis was calculated and it was compared with that at other times using Poisson regression and generalized estimating equations. Sensitivity analyses were performed to confirm the robustness of this finding.

RESULTS

The data of 10,400 patients with new-onset type 1 diabetes were analyzed, including 2,196 (952 male 1,244 female) patients diagnosed with influenza between 1 September 2014 and 31 August 2017. Although only patients with type 1 diabetes were included, adjusted analysis showed that individuals had a 1.3-fold (95% confidence interval: 1.15-1.46) higher risk of developing type 1 diabetes in the first 180 days after influenza diagnosis than that at other times.

CONCLUSIONS

In this Japanese population-based cohort, the risk of new-onset type 1 diabetes may increase after the diagnosis of influenza. These results, which must be confirmed in other populations, suggest that influenza may be a causal factor for new-onset type 1 diabetes. The molecular mechanisms underlying the potential etiological relationship between influenza and type 1 diabetes should be elucidated.

Incidence and seasonality of type 1 diabetes: a population-based 3-year cohort study using the National Database in Japan

INTRODUCTION

To investigate the incidence of type 1 diabetes by age group (0-19, 20-39, 40-59, ≥60 years) in Japan and whether there is seasonality in this incidence.

RESEARCH DESIGN AND METHODS

The incidence of type 1 diabetes from September 2014 to August 2017 was estimated using 2013-2018 data from the National Database of Health Insurance Claims and Specific Health Check-ups of Japan. The incidence rate was analyzed using Tango's Index and the self-controlled case series method.

RESULTS

Overall, 10 400 of the 79 175 553 included individuals were diagnosed with type 1 diabetes. The incidence of type 1 diabetes from September 2014 to August 2017 was 4.42/100 000 person-years. The incidence rates for men aged 0-19, 20-39, 40-59, and ≥60 years were 3.94, 5.57, 5.70, and 3.48, respectively. Among women, the incidence rates for the same age ranges were 5.22, 4.83, 4.99, and 3.31, respectively. Tango's index showed that the incidence rate of type 1 diabetes was significantly associated with seasons among those aged 0-19 years. Further, the self-controlled case series method showed a significant interaction between age and season, with the incidence of type 1 diabetes being higher in spring for patients younger than 20 years of age.

CONCLUSIONS

In Japan, men aged 40-59 years and women aged 0-19 years are the groups with the highest incidence of type 1 diabetes. Further, the incidence of younger-onset diabetes in Japan was higher in spring (from March to May).