Epidemiologic Research on Real-World Medical Data in Japan

Volume 1
1. Auflage 2022
ISBN: 978-981-16-6375-8
Verlag: Springer

Buch, Englisch, 93 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 207 g

Reihe: SpringerBriefs for Data Scientists and Innovators

This book analyzes the development of medical big data projects in Japan.Japan is experiencing unprecedented population aging, and labor productivity has decreased accordingly. Big data analysis of the Japanese medical real-world database (RWD) has the potential to tackle this issue.To allow readers to gain an understanding of Japanese medical big data analysis, the book discusses the original Japanese system that generates medical RWDs in the hospital medical records system, the nationwide standardized health checkup system, and the public medical insurance system in Japan.After introducing four major big data projects in the healthcare–medical field in Japan, the book explains the importance of creating information standards to maintain data quality and to analyze medical big data. It enables readers to analyze which standards are installed in which RWDs, how the standards are maintained, and which issues are prevalent in Japan.This book also describes the ethical processes involved in big data projects involving medical RWDs in Japan.

Zielgruppe

Research

Autoren/Hrsg.

Nakashima, Naoki

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Betriebliches Gesundheitsmanagement
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Geriatrie, Gerontologie
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Sozialwissenschaften Soziologie | Soziale Arbeit Altersgruppen Alterssoziologie
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data

Inhaltsverzeichnis

• Overview
• NDB (National Database)
• MID-NET (Medical Information Database Network)
  
• DPC (Diagnosis Procedure Combination)
  
• Disease Registration Cohort Study with EMR(SS-MIX2)
  
• Standard Code Mapping and Data Quality
  
• Phenotyping
  
• Data Analysis on Real World Data
  
• Ethical Issues of Data Secondary Use in Japan