Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.
10.4258/hir.2013.19.2.102
- Author:
Soo Yong SHIN
1
;
Yongman LYU
;
Yongdon SHIN
;
Hyo Joung CHOI
;
Jihyun PARK
;
Woo Sung KIM
;
Jae Ho LEE
Author Information
1. Department of Biomedical Informatics, Asan Medical Center, Seoul, Korea.
- Publication Type:Original Article
- Keywords:
Access to Information;
Information Systems;
Research Design;
Research Ethics;
Biomedical Research
- MeSH:
Access to Information;
Bioethics;
Computer Security;
Electronics;
Electrons;
Ethics Committees, Research;
Ethics, Research;
Humans;
Information Systems;
Jurisprudence;
Masks;
Privacy;
Research Design;
Social Control, Formal;
Tertiary Care Centers
- From:Healthcare Informatics Research
2013;19(2):102-109
- CountryRepublic of Korea
- Language:English
-
Abstract:
OBJECTIVES: The Korean government has enacted two laws, namely, the Personal Information Protection Act and the Bioethics and Safety Act to prevent the unauthorized use of medical information. To protect patients' privacy by complying with governmental regulations and improve the convenience of research, Asan Medical Center has been developing a de-identification system for biomedical research. METHODS: We reviewed Korean regulations to define the scope of the de-identification methods and well-known previous biomedical research platforms to extract the functionalities of the systems. Based on these review results, we implemented necessary programs based on the Asan Medical Center Information System framework which was built using the Microsoft. NET Framework and C#. RESULTS: The developed de-identification system comprises three main components: a de-identification tool, a search tool, and a chart review tool. The de-identification tool can substitute a randomly assigned research ID for a hospital patient ID, remove the identifiers in the structured format, and mask them in the unstructured format, i.e., texts. This tool achieved 98.14% precision and 97.39% recall for 6,520 clinical notes. The search tool can find the number of patients which satisfies given search criteria. The chart review tool can provide de-identified patient's clinical data for review purposes. CONCLUSIONS: We found that a clinical data warehouse was essential for successful implementation of the de-identification system, and this system should be tightly linked to an electronic Institutional Review Board system for easy operation of honest brokers. Additionally, we found that a secure cloud environment could be adopted to protect patients' privacy more thoroughly.
