Validity of Claims Diagnosis Codes for Cardiovascular Diseases in Diabetes Patients in Japanese Administrative Database.

Background: Observational studies using large claims databases for diabetes patients have been increasingly conducted. While validation of outcomes is important in such studies, validation studies from Japan are still scarce and small in scale with questions remaining on the representativeness of their findings. We examined the positive predictive value (PPV) of outcomes that often develop in type 2 diabetes patients: cardiovascular outcomes including congestive heart failure (CHF), myocardial infarction (MI), stroke-related diseases, and renal outcomes including end stage renal disease (ESRD), and death using a large Japanese database containing administrative claims and electronic medical record (EMR) data. Patients and Methods: We used patient-level administrative claims data from 2003 and EMR data from 1985 to the most recent data up to December 2018 provided by Real World Data Co., Ltd. The database consisted of data from over 200 hospitals including >= 12 million uniquely identifiable patients. Among patients who had >= 1 type 2 diabetes diagnosis in the EMR, those who had administrative claims for each outcome were identified, and then the PPV was calculated for each outcome using the EMR as the gold standard. Results: The numbers of patients identified for each outcome were 1,700 for MI, 2,027 for hemorrhagic stroke, 3,722 for ESRD, 4,723 for ischemic stroke, 5,404 for CHF, 6,678 for any type of stroke, and 10,815 for death. PPVs ranged from 67.4% for ESRD, 78.7% for MI, 80.3% for death, 85.7% for ischemic stroke, 88.9% for any type of stroke, 89.9% for hemorrhagic stroke, and 95.7% for CHF. A post hoc analysis showed PPV for ESRD as 83.8%. Conclusion: This large-scale validation study on diagnosis in administrative claims showed reasonable PPVs for the outcomes. We believe that the definitions of outcomes can be considered to be appropriate for future studies using Japanese administrative claims data.