About this Journal Submit a Manuscript Table of Contents
Journal of Biomedicine and Biotechnology
Volume 2012 (2012), Article ID 521267, 9 pages
http://dx.doi.org/10.1155/2012/521267
Research Article

A Privacy-Preserved Analytical Method for eHealth Database with Minimized Information Loss

1Service Systems Technology Center, Industrial Technology Research Institute (ITRI), Hsinchu 31040, Taiwan
2Department of Communications Engineering, National Chung Cheng University, Chiayi 62145, Taiwan

Received 17 May 2012; Revised 18 July 2012; Accepted 19 July 2012

Academic Editor: Tai Hoon Kim

Copyright © 2012 Ya-Ling Chen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Digitizing medical information is an emerging trend that employs information and communication technology (ICT) to manage health records, diagnostic reports, and other medical data more effectively, in order to improve the overall quality of medical services. However, medical information is highly confidential and involves private information, even legitimate access to data raises privacy concerns. Medical records provide health information on an as-needed basis for diagnosis and treatment, and the information is also important for medical research and other health management applications. Traditional privacy risk management systems have focused on reducing reidentification risk, and they do not consider information loss. In addition, such systems cannot identify and isolate data that carries high risk of privacy violations. This paper proposes the Hiatus Tailor (HT) system, which ensures low re-identification risk for medical records, while providing more authenticated information to database users and identifying high-risk data in the database for better system management. The experimental results demonstrate that the HT system achieves much lower information loss than traditional risk management methods, with the same risk of re-identification.