Cross Fact Health Insurance Claims Database (Japan)

Field Names
Records
Coordinating Country
Japan
Region

Japan

Brief Database Description

The Cross Fact Health Insurance Claims Database of Japan is a longitudinal database containing employer-sponsored insurance claims. Specifically, Cross Fact has drug and diagnosis data with medical and pharmacy insurance claims for both outpatients and inpatients.

This database has data since the year 2010 on >7 million patients. It has excellent coverage including local (regional) areas of Japan (i.e., prefectures), with the additional ability to track treatment and medication(s) on a per-patient basis.

NOTE: Dental insurance claims are also included, but not organ transplant-related claims or patient comment fields.

Database Type
Longitudinal Population Database
- Drug and Diagnosis Data
- - Medical and Pharmacy Insurance Claims
- - - Outpatient and inpatient

(The Cross Fact Health Insurance Claims Database of Japan is a longitudinal database containing employer-sponsored insurance claims. Specifically, Cross Fact has drug and diagnosis data with medical and pharmacy insurance claims for both outpatients and inpatients.)

Database Source
Medical Insurance Claims
Frequency of Data Collection
Monthly
Frequency of Data Update
Monthly
Years Covered
2010 - Present

Most data are available since 2012, though some data are available starting 2010

Population Type
Insured

Health insurance societies for salaried workers

Patient Type
Inpatient and Outpatient
Date of Last Update
Ongoing

(The Cross Fact Health Insurance Claims Database is updated on an ongoing basis;
This profile was developed for the B.R.I.D.G.E. TO DATA site on October 14, 2022.)

Field Names
Records
Database Population Size
5 - 20 Million

(>7 Million)

Active Population Size
5 - 20 Million

(>7 Million)

Annual Change in Population
N/A

(Not applicable)

Sample Weights - Extrapolation Factors
No
Final Population Size
N/A

(Not applicable as data are still being collected)

Field Names
Records
Age of Patients at Data Collection
Yes

(Month of Birth is recorded)

Approximate Percentage of Participants <18 years and those >65 years

< 18 years = 22%
> 65 years = 4%

Gender Data
Yes
Percentage of Males/Females

Males = 48%
Females = 52%

Ethnicity / Race Data
No
Geographic Location

Prefectures of Japan

Date of Birth Recorded
Yes

Month of Birth is recorded as Year/Month, in the format of yyyymm

Death Recorded
Yes

Patient outcomes are recorded

Availability of death certificate / autopsy information
No
Other Demographic Data
Yes

Information is available on insured persons or their dependents

Field Names
Records
Physician ID
Yes

However, the data are limited

Physician Specialty
No
Pharmacy ID
Yes
Field Names
Records
Diagnosis Data
Yes
Diagnoses Coded
ICD-10
Diagnoses: Date Parameters
2010 - Present
Diagnoses: Maximum Number of Codes Allowed
Unlimited
Physical Examination Findings
Yes

Some physical examination data are available from some insurance companies

Birth Defect Data
Yes

Information is available in case there is a congenital abnormality / birth defects

Cancer Data
Yes
Infectious Disease Data
Yes
Environmental Exposures
Yes
Behavioral Data Elements
Yes

Frequency of alcohol consumption, smoking, etc. are all included in the physical examination data.

Field Names
Records
Procedure Data
Yes
Procedures Coded
Receipt code for computerized processing system (MHLW)
Number of Procedures Coded
Unlimited
Procedure Date Parameters
2010 - Present
Laboratory Information
No
Field Names
Records
Drug Data
Yes: Prescription only
Drug Date Parameters
2010 - Present

Most data are available since 2012; however, some data are available since 2010.

Drug Regimen & Route
Yes

Route of administration is recorded

Drug Manufacturer
Yes
Drug Dosage
Yes
Drug Days Supply
Yes
Drug Coding System: Maximum Number
Unlimited
Drug Coding System: Primary
Other

[YJ code - YJ codes are part of a drug identification coding system that was developed by the Medical Information System Development Center (MEDIS-DC). It consists of 12 alphanumeric characters: the first four digits represent a drug class effect, the next three digits represent a route of administration, an alphabet represents a dosage form, followed by one digit representing a dosage, two digits representing a brand, and the last digit is a check digit to avoid misreads. The dosage form characters are as follows: A-E: powders, F-L: tablets, M-P: capsules, Q-S: liquids, and T or X: other dosage forms.]

Drug Coding System: Other
ATC-EPhMRA/IPMRG
Drug Generic Name
Yes
Drug Additional Information
Yes

Information on drug prices is available

Field Names
Records
Biobank Type
N/A
Human Specimen
N/A
Blood Type
N/A
Biomarkers
N/A
Patient ID
N/A
Number of Samples
N/A
Frequency of Sample Collection
N/A
Pre-diagnostic Sample Collection
N/A
Post-treatment Sample Collection
N/A
Method of Sample Collection
N/A
Age at Sample Collection
N/A
Date of Sample Collection
N/A
Reason for Sample Collection
N/A
Method of Sample Storage
N/A
Length of Sample Storage
N/A
Pathology
N/A
DNA Isolation
N/A
RNA Isolation
N/A
Cell Culture
N/A
Genetic Testing
N/A
Access for Research: Specimens
N/A
Access for Research: Genetic Data
N/A
Access for Research: Epidemiologic Data
N/A
Quality Assurance Procedures
N/A
Family History
N/A
Medical History
N/A
Biobank Linkage
N/A
Field Names
Records
Type of Genetic Database
N/A
Source of Genetic Data
N/A
Specimen Genotyped
N/A
Tissue Form
N/A
Genetic Template
N/A
Gene-Drug Response
N/A
Gene-Disease Relationship
N/A
Gene-Health Outcome Relationship
N/A
Gene-Environment Response
N/A
Method of Imputing Genetic Data
N/A
Genetic Variant Identification
N/A
Genetic Data Level
N/A
Genotyping Method
N/A
Method of Genetic Variant Filtering
N/A
Haplotypes
N/A
Haplogroups
N/A
Variable Number of Tandem Repeats (VNTR)
N/A
Single Nucleotide Polymorphisms (SNPs)
N/A
Variant Type
N/A
Variant Class
N/A
Mutation Indicated
N/A
Position
N/A
Amino Acid Change
N/A
Genotype / Polymorphism
N/A
Allele Frequency
N/A
Linkage Disequilibrium (r²)
N/A
Noncarriers Indicated
N/A
Association Statistics
N/A
Genetic Relatedness Pairing
N/A
Data Sharing: Genetic Data
N/A
Access for Research
N/A
Genetic Data Linkage
N/A
Description of Genetic Data Linkage
N/A
Field Names
Records
Cost Data
Yes

Billing information is available

Cost Denomination
Japanese Yen (JPY)
Type of Cost Data
Yes

Cost of therapy, cost of prescription, cost for medical consultation or doctor visit, etc.

Description of Surrogate Link
No
Field Names
Records
Data Validation Against Original Source
No
Access to Medical Records
No
Linkage to Other Databases
No
Brief Description of Linkage Capabilities

N/A

(Not applicable)

Field Names
Records
Database Contact Data

Email: irw-info@intage.com

Alternate Contact

N/A

(Not applicable)

Source of Database Funding
Private

(Intage Real World, Inc.)
NOTE: The company changed its name from Japan Medical Information Research Institute Inc. (JMIRI) to INTAGE Real World, Inc. in July 2021.
JMIRI, the retail pharmacy claims database, and Medi-Scope, the health insurance claims database, managed by JMIRI have since been managed and operated under the name, Cross Fact, an integrated healthcare database.

Sponsoring Government Agency
N/A

(Not applicable)

Sponsoring Pharmaceutical Manufacturer

N/A

(Not applicable)

Database Usage Restrictions
Private Access

Data are accessible by companies that have a Japanese branch. These include pharmaceutical companies, academia, and research institutions. For more information re: datasets, please email irw-info@intage.com, and a sales representative will contact you.

Charge for Database Usage
Yes

For cost information, please contact Intage via email at irw-info@intage.com

Data Media Format
Excel / CSV

Aggregated reports (excel, ppt, etc.)
BI (Business Intelligence) software/tool - MotionBoard]

Number of Publications Using Database
5
References of Studies Using/Describing Database

1. Machida T, Obara T, Miyazaki M, Inoue J, Mano N. Trends in drug prescriptions for type 2 diabetes, hypertension, and dyslipidemia among adults with non-alcoholic fatty liver disease. Ann Hepatol. 2022;27(4):100699.

2. Hozawa S, Maeda S, Kikuchi A, Koinuma M. Exploratory research on asthma exacerbation risk factors using the Japanese claims database and machine learning: a retrospective cohort study. J Asthma. 2022;59(7):1328-1337.

3. Maeda S, Kobayashi S, Takahashi K, Miyata S. Association of comorbidities and medications with risk of asthma exacerbation in pediatric patients: a retrospective study using Japanese claims data. Sci Rep. 2022;12(1):5509.

4. Yokoyama A, Okazaki H, Makita N, Fukui A, Piao Y, Arita Y, Itoh Y, Tashiro N. Regional differences in the incidence of asthma exacerbations in Japan: A heat map analysis of healthcare insurance claims data. Allergol Int. 2022;71(1):47-54.

5. Kubota K, Kelly T, Sato T, Pratt N, Roughead E, Yamaguchi T. A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies. BMC Med Res Methodol. 2021;21(1):214.

    Database Contact
    Database Contact Data

    Email: irw-info@intage.com

    Alternate Contact

    N/A

    References of Studies Using/Describing Database

    1. Machida T, Obara T, Miyazaki M, Inoue J, Mano N. Trends in drug prescriptions for type 2 diabetes, hypertension, and dyslipidemia among adults with non-alcoholic fatty liver disease. Ann Hepatol. 2022;27(4):100699.

    2. Hozawa S, Maeda S, Kikuchi A, Koinuma M. Exploratory research on asthma exacerbation risk factors using the Japanese claims database and machine learning: a retrospective cohort study. J Asthma. 2022;59(7):1328-1337.

    3. Maeda S, Kobayashi S, Takahashi K, Miyata S. Association of comorbidities and medications with risk of asthma exacerbation in pediatric patients: a retrospective study using Japanese claims data. Sci Rep. 2022;12(1):5509.

    4. Yokoyama A, Okazaki H, Makita N, Fukui A, Piao Y, Arita Y, Itoh Y, Tashiro N. Regional differences in the incidence of asthma exacerbations in Japan: A heat map analysis of healthcare insurance claims data. Allergol Int. 2022;71(1):47-54.

    5. Kubota K, Kelly T, Sato T, Pratt N, Roughead E, Yamaguchi T. A novel weighting method to remove bias from within-subject exposure dependency in case-crossover studies. BMC Med Res Methodol. 2021;21(1):214.