Deputy Coodination Director Pharmaceuticals and Medical Devices Agency, Japan
Background: MID-NET® (Medical Information Database Network) is one of Japanese medical information databases launched in April 2018 for drug safety assessment based on real world data. It stores electronic medical records (EMRs), claims data, and diagnosis procedure combination (DPC) data in collaboration with 10 healthcare organizations including 23 hospitals and has been utilized in pharmacoepidemiological studies conducted by PMDA (Pharmaceuticals and Medical Devices Agency), pharmaceutical industries and academia.
Objectives: For promoting appropriate utilization of real world data from MID-NET®, characteristics of the accumulated MID-NET® data since 2018 were examined, including impacts of the changing social circumstances such as COVID-19.
Methods: Trends of the number of records and patients per year from 2018 to 2022 were examined utilizing data from the MID-NET®. Factors associated with changes on these numbers were also considered by subanalysis stratified by disease categories (ICD10: International Statistical Classification of Diseases and Related Health Problems).
Results: By the end of 2022, approximately 6.05 million patient’s data were stored in the MID-NET® with increase of approximately 0.35 million patients from 2021. Although the average of annual number of patients was around 1.34 million, its number was relatively lower in 2020, suggesting that spread of the COVID-19 in Japan may affect the hospital visit of patients. In terms of disease category, higher proportion of patients was observed in the circulatory system (I00-I99) followed by endocrine, nutritional and metabolic diseases (E00-E90), diseases of the digestive system (K00-K93) and neoplasms (C00-D48). Distinctive changes on these proportions were also observed in the last five years.
Conclusions: Data stored in the MID-NET® steadily increased in the last five years. Number of records and patients per year could be affected by the social circumstances like COVID-19. Understanding data characteristics stored in the database will be important for proper planning of a pharmacoepidemiological study based on real world data.
