Estimating diabetes mellitus incidence using health insurance claims data: A database-driven cohort study.

Abstract

Type II diabetes mellitus is a global public health challenge, necessitating robust epidemiological investigations. The majority of evidence reports prevalence as estimations of incidence requiring longitudinal cohort studies that are challenging to conduct. However, this has been addressed by the secondary use of existing health insurance claims data. The current study aimed to examine the incidence of type II diabetes mellitus using existing claims and ledger data. The National Health Insurance and medical care system databases were used to extract type II diabetes mellitus (defined as ICD10 codes E11$-14$) claims data over a period of 5 years for individuals over 40 years old living in one city in Japan. Prevalence was calculated, and insured individuals whose data could be tracked over the entire study period were included in the subsequent analyses. Therefore, annual incidence was calculated by estimating differences in prevalence by year. Data analyses were stratified by sex and age group, and a model analysis was conducted to account for these variables. Overall, the prevalence, diabetes medication usage, and insulin usage were 26.3%, 12.1%, and 2.0%, respectively. Annual incidence of type II diabetes mellitus ranged between 1.2% and 4.6%. Both prevalence and incidence tended to be higher in males and peaked around 60-80 years old. The overall annual incidence was estimated at 3.03% (95% CI: 2.21%-3.85%). The annual incidence was not always associated with a low risk, indicating a consistent risk from middle age onward, although the level of risk varied with age. The current study successfully integrated existing claims and ledger data to explore incidence, and this methodology could be applied to a range of injuries and illnesses in the future.