The University of Tokyo · Medicine
Professor Hayato Yamana's research lab specializes in health informatics and pharmacoepidemiology, focusing on the validation and utilization of large-scale healthcare databases for clinical research. The lab investigates disease identification and risk prediction using administrative and claims data, with particular emphasis on improving the accuracy of diagnoses and procedures in population-based studies. Key research directions include the application of procedure-based methods for identifying severe conditions such as sepsis and DIC, exploring immune-mediated associations in gynecological and autoimmune diseases, and analyzing real-world patterns of traditional Japanese Kampo medicine use within national health insurance systems. The lab also contributes to the development of robust, data-driven approaches for risk adjustment and health outcomes research in Japan and beyond.
Figures are computed from collected data and may differ slightly.
The validity of diagnoses and procedure records in the DPC data and laboratory results in the SS-MIX data was high in general, supporting their use in future studies.
Validation studies are being conducted at an increasing rate in Japan, although most of them are small scale. Further large-scale comprehensive validation studies are necessary to effectively utilize the databases for research.
Procedure-based methods were more sensitive and less specific than diagnosis-based methods in identifying severe sepsis and DIC. Procedure records could improve disease identification in administrative databases.
Several allergic diseases were associated with an increased incidence of endometriosis. A higher incidence was also observed in patients with rheumatoid arthritis. Further studies are warranted to elucidate the influence of immune responses on the development of endometriosis.
Objective Kampo is a traditional Japanese medicine using formulae of natural agents. Although Kampo is widely practiced, information regarding the current prescriptions of Kampo formulations is lacking. The aim of the study was to describe the outpatient use of Kampo formulations in the current Japanese health insurance system. Methods From the JMDC Claims Database, we identified subscribers with outpatient prescriptions of Kampo extract formulations between April 2017 and March 2018. Prescripti
Procedure-based severity index predicted mortality well, suggesting that procedure records in administrative database are useful for risk adjustment.
In this era of large-scale, multi-institutional studies, the importance of analyzing hierarchical (clustered) data is increasing. However, conventional regression analysis may be inadequate for this purpose because it assumes that records for individual patients are independent of records for other patients. Multilevel analysis is a statistical method that allows one to analyze data with a hierarchical structure. Mixed-effect models expand the conventional regression models by incorporating rand
Little improvement was observed in the prognosis of cirrhosis compared with previous reports, and the prognosis of Child-Pugh class C cirrhosis remained poor. Untreated esophageal varices were identified as a risk factor for death.
Our model using routinely collected administrative data accurately identified postoperative infections. Further external validation would lead to the application of the model for research using administrative databases.
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