Japanese Society of Nephrology, in collaboration with the Japan Association for Medical Informaton, has established a new nationwide comprehensive CKD clinical database (J-CKD-DB) as a project of the Ministry of Health, Labour and Welfare. The purpose of the database is to contribute to the investigation of CKD, analysis of prognostic factors, evaluation of the equalization rate of standard treatment, planning of effective prevention and control of severe disease, and improvement of the quality of kidney disease treatment by utilizing real world data (RWD). The system automatically extracts CKD case data (basic information, prescriptions, test values, etc.) from electronic health records (EHRs) using SS-MIX2 and converts them into a database. With the participation of 15 university hospitals nationwide, 148,000 CKD cases were registered. In addition, five university hospitals constructed J-CKD-DB-Ex (152,000 patients), a DB that enables longitudinal analysis for five years. These DBs will make it possible to survey the actual status of kidney disease treatment.
Clinical guidelines are required to be evidence-based. RCTs require a large investment of resources and it is not easy to answer the many clinical questions submitted from clinical practice. Real world data (RWD) and propensity score matching methods can be used to generate findings with a high level of evidence. The obtained real world evidence (RWE) will be reflected in the guidelines, and the compliance and dissemination rates will be analyzed in the DB. By circulating the above process in a circular manner, it is possible to build an independent evidence generation platform. In this symposium, we would like to report a case study of the use of big data generated from RWD for kidney disease.