{"title":"医疗一体化生物银行中的数据保护","authors":"P. Duhm-Harbeck, J. Habermann","doi":"10.36401/iddb-22-7","DOIUrl":null,"url":null,"abstract":"\n \n \n Development of personalized medicine depends on research using clinical biospecimens and data. This interface between clinical care and translational research is increasingly served by hospital-integrated biobanks; yet their implementation is hampered by complex data regulations.\n \n \n \n A generic data protection concept with a decision and application matrix was developed addressing five criteria: (1) organizational integration into university medicine, (2) biobank governance, (3) ethical and legal aspects, (4) specifications of the BSI (Bundesamt für Sicherheit in der Informationstechnik [Federal Office for Information Security]), and (5) FAIR (findable, accessible, interoperable, and reusable) principles for research data. Applicability was tested for the highest complexity level at Campus Lübeck.\n \n \n \n The data protection concept was approved by the local ethics committee as well as local and national data protection authorities. The concept allows an automated research-guided patient recruitment and data protection-compliant information technology (IT) in connection to national and international research networks. It ensures university and hospital conformity with the EU Data Protection Regulation. Consent behavior of 277,766 patients over five years proved routine practicability (error rate 0.0013%; withdrawals 0.09%). Clinical staff obtained higher consent rates (85.6%) compared with consent rates for use of data only at central patient admission (56.1%); even though consents in central patient admission increased constantly during observation time.\n \n \n \n The generic data protection concept can legitimately enable personalized medicine through biobanking in the clinical context.\n","PeriodicalId":331225,"journal":{"name":"Innovations in Digital Health, Diagnostics, and Biomarkers","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Data Protection in Healthcare-Integrated Biobanking\",\"authors\":\"P. Duhm-Harbeck, J. Habermann\",\"doi\":\"10.36401/iddb-22-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n \\n \\n Development of personalized medicine depends on research using clinical biospecimens and data. This interface between clinical care and translational research is increasingly served by hospital-integrated biobanks; yet their implementation is hampered by complex data regulations.\\n \\n \\n \\n A generic data protection concept with a decision and application matrix was developed addressing five criteria: (1) organizational integration into university medicine, (2) biobank governance, (3) ethical and legal aspects, (4) specifications of the BSI (Bundesamt für Sicherheit in der Informationstechnik [Federal Office for Information Security]), and (5) FAIR (findable, accessible, interoperable, and reusable) principles for research data. Applicability was tested for the highest complexity level at Campus Lübeck.\\n \\n \\n \\n The data protection concept was approved by the local ethics committee as well as local and national data protection authorities. The concept allows an automated research-guided patient recruitment and data protection-compliant information technology (IT) in connection to national and international research networks. It ensures university and hospital conformity with the EU Data Protection Regulation. Consent behavior of 277,766 patients over five years proved routine practicability (error rate 0.0013%; withdrawals 0.09%). Clinical staff obtained higher consent rates (85.6%) compared with consent rates for use of data only at central patient admission (56.1%); even though consents in central patient admission increased constantly during observation time.\\n \\n \\n \\n The generic data protection concept can legitimately enable personalized medicine through biobanking in the clinical context.\\n\",\"PeriodicalId\":331225,\"journal\":{\"name\":\"Innovations in Digital Health, Diagnostics, and Biomarkers\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Innovations in Digital Health, Diagnostics, and Biomarkers\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.36401/iddb-22-7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Innovations in Digital Health, Diagnostics, and Biomarkers","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36401/iddb-22-7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
个性化医疗的发展依赖于使用临床生物标本和数据的研究。这种临床护理和转化研究之间的接口越来越多地由医院整合的生物银行提供服务;然而,它们的实施受到复杂的数据法规的阻碍。一个带有决策和应用矩阵的通用数据保护概念被开发出来,解决了五个标准:(1)与大学医学的组织整合,(2)生物库治理,(3)伦理和法律方面,(4)BSI(联邦信息安全办公室)规范,以及(5)研究数据的公平(可查找、可访问、可互操作和可重用)原则。在Campus l beck进行了最高复杂性水平的适用性测试。数据保护概念得到了当地伦理委员会以及地方和国家数据保护部门的批准。该概念允许自动研究指导患者招募和符合数据保护的信息技术(IT)连接到国家和国际研究网络。它确保大学和医院符合欧盟数据保护条例。277,766例患者5年的同意行为证明了常规实用性(错误率0.0013%;取款0.09%)。临床工作人员获得了更高的同意率(85.6%),而仅在中心患者入院时使用数据的同意率(56.1%);即使在观察期间,中心患者入院的同意率不断增加。仿制数据保护概念可以通过临床环境中的生物银行合法地实现个性化医疗。
Data Protection in Healthcare-Integrated Biobanking
Development of personalized medicine depends on research using clinical biospecimens and data. This interface between clinical care and translational research is increasingly served by hospital-integrated biobanks; yet their implementation is hampered by complex data regulations.
A generic data protection concept with a decision and application matrix was developed addressing five criteria: (1) organizational integration into university medicine, (2) biobank governance, (3) ethical and legal aspects, (4) specifications of the BSI (Bundesamt für Sicherheit in der Informationstechnik [Federal Office for Information Security]), and (5) FAIR (findable, accessible, interoperable, and reusable) principles for research data. Applicability was tested for the highest complexity level at Campus Lübeck.
The data protection concept was approved by the local ethics committee as well as local and national data protection authorities. The concept allows an automated research-guided patient recruitment and data protection-compliant information technology (IT) in connection to national and international research networks. It ensures university and hospital conformity with the EU Data Protection Regulation. Consent behavior of 277,766 patients over five years proved routine practicability (error rate 0.0013%; withdrawals 0.09%). Clinical staff obtained higher consent rates (85.6%) compared with consent rates for use of data only at central patient admission (56.1%); even though consents in central patient admission increased constantly during observation time.
The generic data protection concept can legitimately enable personalized medicine through biobanking in the clinical context.