Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital
2
조회
0
다운로드
5
인용
0
참고문헌
키워드
초록
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.
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.
참고문헌 (18)
- "Guidance regarding methods for de-identification of protected health information in accordance with the Health Insurance Portability and Accountability Act (HIPAA) privacy rule" (2013)[URL]
- "The Personal Information Protection Act" (2013)[URL]
- "The Bioethics and Safety Act" (2013)[URL]
- 류현정, "Asan Medical Information System for Healthcare Quality Improvement", Healthcare Informatics Research, 16(3), pp.191~197 (2010), 대한의료정보학회
- Lowe HJ, "STRIDE: an integrated standards-based translational research informatics platform", AMIA Annu Symp Proc, 2009, pp.391~395 (2009)
- Murphy SN, "Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2)", J Am Med Inform Assoc, 17(2), pp.124~130 (2010)
- Nalichowski R, "Calculating the benefits of a Research Patient Data Repository", AMIA Annu Symp Proc, 2006, pp.1044~ (2006)
- "Stanford Translational Research Integrated Database Environment" (2013)[URL]
- "Informatics for Integrating Biology & the Bedside" (2013)[URL]
- "Research Patient Data Registry" (2013)[URL]
- El Emam K, "Methods for the de-identification of electronic health records for genomic research", Genome Med, 3(4), pp.25~ (2011)
- "Tools for de-identification of personal health information" (2009)[URL]
- Meystre SM, "Automatic de-identification of textual documents in the electronic health record: a review of recent research", BMC Med Res Methodol, 10, pp.70~ (2010)
- Deleger L, "Large-scale evaluation of automated clinical note de-identification and its impact on information extraction", J Am Med Inform Assoc, 20(1), pp.84~94 (2013)
- Shin SY, "Deidentification method for bilingual EMR free texts", Proceedings of the 14th World Congress on Medical and Health Informatics (2013)
- El Emam K, "Heuristics for de-identifying health data", IEEE Secur Priv, 6(4), pp.58~61 (2008)
- El Emam K, "A globally optimal k-anonymity method for the de-identification of health data", J Am Med Inform Assoc, 16(5), pp.670~682 (2009)
- Liu J, "Toward a fully de-identified biomedical information warehouse", AMIA Annu Symp Proc, 2009, pp.370~374 (2009)