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Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital
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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Korean Society of Medical Informatics
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3717433/ https://www.ncbi.nlm.nih.gov/pubmed/23882415 http://dx.doi.org/10.4258/hir.2013.19.2.102 |
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author | Shin, Soo-Yong Lyu, Yongman Shin, Yongdon Choi, Hyo Joung Park, Jihyun Kim, Woo-Sung Lee, Jae Ho |
author_facet | Shin, Soo-Yong Lyu, Yongman Shin, Yongdon Choi, Hyo Joung Park, Jihyun Kim, Woo-Sung Lee, Jae Ho |
author_sort | Shin, Soo-Yong |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3717433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Korean Society of Medical Informatics |
record_format | MEDLINE/PubMed |
spelling | pubmed-37174332013-07-23 Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital Shin, Soo-Yong Lyu, Yongman Shin, Yongdon Choi, Hyo Joung Park, Jihyun Kim, Woo-Sung Lee, Jae Ho Healthc Inform Res Original Article 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. Korean Society of Medical Informatics 2013-06 2013-06-30 /pmc/articles/PMC3717433/ /pubmed/23882415 http://dx.doi.org/10.4258/hir.2013.19.2.102 Text en © 2013 The Korean Society of Medical Informatics http://creativecommons.org/licenses/by-nc/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Shin, Soo-Yong Lyu, Yongman Shin, Yongdon Choi, Hyo Joung Park, Jihyun Kim, Woo-Sung Lee, Jae Ho Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title | Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title_full | Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title_fullStr | Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title_full_unstemmed | Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title_short | Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital |
title_sort | lessons learned from development of de-identification system for biomedical research in a korean tertiary hospital |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3717433/ https://www.ncbi.nlm.nih.gov/pubmed/23882415 http://dx.doi.org/10.4258/hir.2013.19.2.102 |
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