Tomohide Iwao

Institute for Advancement of Clinical and Translational Science (iACT) Kyoto University Hospital, Kyoto, Japan

Publications

• Research Article   
  Analysis Unit Data Model for Statistical and Machine Learning Analysis using the Health Insurance Claims Database
  Author(s): Tomohide Iwao*
  
  Background: Administrative databases of health insurance claims are becoming increasingly popular. However, since they generally contain only the data necessary to assess claims, they are insufficient for research purposes, and the data are normalized in such a manner that patient-care data are dispersed across multiple tables. Thus, creating a dataset that is appropriate for analysis requires a great deal of effort and involves techniques that would be difficult for clinicians. Objectives: The aim of the present study was to create a data warehouse (DW) that could provide easy access to the data required for epidemiological research Methods: First, epidemiological studies that used data from the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) as a source were surveyed to identify the attributes (variables) most commonly analyzed. Subsequently,.. Read More»
  10.24105/ejbi.2022.18.8.80-87