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タイトル: Data Processing Model for Compliance with International Medical Research Data Processing Rules
著者: Kuroda, Yuki
Yamamoto, Goshiro  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0002-2014-7195 (unconfirmed)
Kuroda, Tomohiro  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0003-1472-7203 (unconfirmed)
著者名の別形: 黒田, 佑輝
山本, 豪志朗
黒田, 知宏
キーワード: data protection
privacy
data processing model
GDPR
regulatory science
発行日: 2022
出版者: Japanese Society for Medical and Biological Engineering
誌名: Advanced Biomedical Engineering
巻: 11
開始ページ: 48
終了ページ: 57
抄録: In addition to traditional clinical research, advances in information communication technologies facilitates new medical research using internet of things devices and other cutting-edge technologies. Such medical research also simplifies the collection of data on research subjects in their daily lives internationally. In this context, medical research is increasingly required to comply with rules protecting patients’ personal data. This study proposes a model to enable researchers and other stakeholders including ethics committees in such international medical research to easily verify whether the planned processing of patient data complies with relevant legal and ethical rules. The model proposed in this study consists of (1) how patient information is pro-cessed, (2) the rules that are relevant to the processing, and (3) the analysis of whether the processing complies with the rules. This study suggests that the model should describe the aspects of data processing that are sub-ject to many rules, such as the location of the processing, categories of data, purposes of the processing, and the storage period. Thus, using the information described in the model as a guide, stakeholders can determine which national and international legal/ethical rules apply to the planned processing. Then, they can use the model to verify and document whether the processing complies with the specific regulatory rules. The use of the model in this study enables stakeholders in medical research to comply with the rules related to patient data more effectively than without using the model.
著作権等: © 2022 Japanese Society for Medical and Biological Engineering
Copyright: ©2022 The Author(s). This is an open access article distributed under the terms of the Creative Commons BY 4.0 International (Attribution) License, which permits the unrestricted distribution, reproduction and use of the article provided the original source and authors are credited.
URI: http://hdl.handle.net/2433/287054
DOI(出版社版): 10.14326/abe.11.48
出現コレクション:学術雑誌掲載論文等

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