TY - GEN
T1 - Novel analytics framework for universal healthcare insurance claims database
AU - Sato, Jumpei
AU - Goda, Kazuo
AU - Kitsuregawa, Masaru
AU - Nakashima, Naoki
AU - Mitsutake, Naohiro
N1 - Funding Information:
This work has been in part supported by Health Labour Sciences Research Grant (Ministry of Health Labour and Welfare, Japan), Funding Program for World-Leading Innovative R&D on Science and Technology (Cabinet Office, Japan), Impulsing Paradigm Change through Disruptive Technologies Program (Cabinet Office, Japan) and ICT infrastructure establishment and implementation of artificial intelligence for clinical and medical research (Japan Agency for Medical Research and Development).
Publisher Copyright:
© 2019 International Medical Informatics Association (IMIA) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/8/21
Y1 - 2019/8/21
N2 - Medical insurance claims are useful data to offer a big-picture view and insight of a nation-wide healthcare system. Yet, formal description of the logic to analyze the claims has not been established. So far, we proposed a description scheme of analytics logic over claims database. In this paper, we propose a novel analytics framework based on the description scheme. By showing a case study, we demonstrate the effectiveness of the framework.
AB - Medical insurance claims are useful data to offer a big-picture view and insight of a nation-wide healthcare system. Yet, formal description of the logic to analyze the claims has not been established. So far, we proposed a description scheme of analytics logic over claims database. In this paper, we propose a novel analytics framework based on the description scheme. By showing a case study, we demonstrate the effectiveness of the framework.
UR - http://www.scopus.com/inward/record.url?scp=85071472705&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85071472705&partnerID=8YFLogxK
U2 - 10.3233/SHTI190543
DO - 10.3233/SHTI190543
M3 - Conference contribution
C2 - 31438240
AN - SCOPUS:85071472705
T3 - Studies in Health Technology and Informatics
SP - 1578
EP - 1579
BT - MEDINFO 2019
A2 - Seroussi, Brigitte
A2 - Ohno-Machado, Lucila
A2 - Ohno-Machado, Lucila
A2 - Seroussi, Brigitte
PB - IOS Press
T2 - 17th World Congress on Medical and Health Informatics, MEDINFO 2019
Y2 - 25 August 2019 through 30 August 2019
ER -