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本文引用的文献

1
Ethical and coordinative challenges in setting up a national cohort study during the COVID-19 pandemic in Germany.在德国 COVID-19 大流行期间建立国家队列研究面临的伦理和协调挑战。
BMC Med Ethics. 2023 Oct 17;24(1):84. doi: 10.1186/s12910-023-00959-0.
2
[The German Network of University Medicine: technical and organizational approaches for research data platforms].[德国大学医学网络:研究数据平台的技术与组织方法]
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2023 Feb;66(2):114-125. doi: 10.1007/s00103-022-03649-1. Epub 2023 Jan 23.
3
The German National Pandemic Cohort Network (NAPKON): rationale, study design and baseline characteristics.德国国家大流行队列网络(NAPKON):原理、研究设计和基线特征。
Eur J Epidemiol. 2022 Aug;37(8):849-870. doi: 10.1007/s10654-022-00896-z. Epub 2022 Jul 29.
4
Long-term health sequelae and quality of life at least 6 months after infection with SARS-CoV-2: design and rationale of the COVIDOM-study as part of the NAPKON population-based cohort platform (POP).新冠病毒感染后至少 6 个月的长期健康后遗症和生活质量:COVIDOM 研究的设计和原理,该研究作为 NAPKON 基于人群队列平台(POP)的一部分。
Infection. 2021 Dec;49(6):1277-1287. doi: 10.1007/s15010-021-01707-5. Epub 2021 Oct 12.
5
[Seroprevalence of COVID-19 and Psychosocial Effects in the General Population: Results of the STAAB-COVID-One Program].[普通人群中新冠病毒病血清流行率及心理社会影响:STAAB-COVID-One项目结果]
Gesundheitswesen. 2021 Dec;83(12):965-975. doi: 10.1055/a-1630-7601. Epub 2021 Oct 12.
6
[Making COVID-19 research data more accessible-building a nationwide information infrastructure].让新冠病毒研究数据更易获取——构建全国性信息基础设施
Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz. 2021 Sep;64(9):1084-1092. doi: 10.1007/s00103-021-03386-x. Epub 2021 Jul 23.
7
COVID-19 in Patients Receiving CD20-depleting Immunochemotherapy for B-cell Lymphoma.接受CD20靶向免疫化疗的B细胞淋巴瘤患者中的新型冠状病毒肺炎
Hemasphere. 2021 Jun 28;5(7):e603. doi: 10.1097/HS9.0000000000000603. eCollection 2021 Jul.
8
Left and right ventricular dysfunction in patients with COVID-19-associated myocardial injury.COVID-19 相关心肌损伤患者的左右心室功能障碍。
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9
Management and Data Sharing of COVID-19 Pandemic Information.新型冠状病毒肺炎大流行信息的管理与数据共享
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Studying the pathophysiology of coronavirus disease 2019: a protocol for the Berlin prospective COVID-19 patient cohort (Pa-COVID-19).研究 2019 年冠状病毒病的病理生理学:柏林前瞻性 COVID-19 患者队列研究方案(Pa-COVID-19)。
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[将队列研究和注册研究的库存数据整合到现有的研究网络中:国家大流行队列网络(NAPKON)]

[Integration of Inventory Data from Cohort and Registry Studies into an Existing Research Network: National Pandemic Cohort Network (NAPKON)].

作者信息

Hofmann Anna-Lena, Vehreschild Jörg Janne, Witzenrath Martin, Hoffmann Wolfgang, Illig Thomas, Schreiber Stefan, Anton Gabriele, Hellmuth Johannes Christian, Muenchhoff Maximilian, Scherer Clemens, Pley Christina, Thibeault Charlotte, Kurth Florian, Berger Sarah, Hummel Michael, Hopff Sina Marie, Stecher Melanie, Appel Katharina, Stahl Dana, Kraus Monika, Lorenz-Depiereux Bettina, Hanß Sabine, von Kielmansegg Sebastian, Schlünder Irene, Niemeyer Anna, Heuschmann Peter, Krawczak Michael, Reese Jens-Peter

机构信息

Universität Würzburg, Institut für klinische Epidemiologie und Biometrie, Würzburg, Germany.

Goethe-Universität Frankfurt am Main, Abteilung für Innere Medizin 2, Hämatologie/Onkologie, Frankfurt am Main, Germany.

出版信息

Gesundheitswesen. 2024 Oct;86(10):647-654. doi: 10.1055/a-2346-9680. Epub 2024 Aug 22.

DOI:10.1055/a-2346-9680
PMID:39173676
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11469301/
Abstract

In the early phase of the COVID-19 pandemic, many local collections of clinical data on patients infected with SARS-CoV-2 were initiated in Germany. As part of the National Pandemic Cohort Network (NAPKON) of the University Medicine Network, the "Integration Core" was established to design the legal, technical and organisational requirements for the integration of inventory data into ongoing prospective data collections and to test the feasibility of the newly developed solutions using use cases (UCs). Detailed study documents of the data collections were obtained. After structured document analysis, a review board evaluated the integrability of the data in NAPKON according to defined criteria. Of 30 university hospitals contacted, 20 responded to the request. Patient information and consent showed a heterogeneous picture with regard to the pseudonymised transfer of data to third parties and re-contact. The majority of the data collections (n=13) met the criteria for integration into NAPKON; four studies would require adjustments to the regulatory documents. Three cohorts were not suitable for inclusion in NAPKON. The legal framework for retrospective data integration and consent-free data use via research clauses (§27 BDSG) was elaborated by a legal opinion by TMF - Technology, Methods and Infrastructure for Networked Medical Research, Berlin. Two UCs selected by the NAPKON steering committee (CORKUM, LMU Munich; Pa-COVID-19, Charité- Universitätsmedizin Berlin) were used to demonstrate the feasibility of data integration in NAPKON by the end of 2021. Quality assurance and performance-based reimbursement of the cases were carried out according to the specifications. Based on the results, recommendations can be formulated for various contexts in order to create technical-operational prerequisites such as interoperability, interfaces and data models for data integration and to fulfil regulatory requirements on ethics, data protection, medical confidentiality and data access when integrating existing cohort data. The possible integration of data into research networks and their secondary use should be taken into account as early as the planning phase of a study - particularly with regard to informed consent - in order to maximise the benefits of the data collected.

摘要

在新冠疫情早期,德国启动了许多关于感染SARS-CoV-2患者的临床数据本地收集工作。作为大学医学网络国家大流行队列网络(NAPKON)的一部分,设立了“整合核心”部门,以设计将存量数据整合到正在进行的前瞻性数据收集中的法律、技术和组织要求,并通过用例(UC)测试新开发解决方案的可行性。获取了数据收集的详细研究文档。经过结构化文档分析后,一个审查委员会根据既定标准评估了NAPKON中数据的可整合性。在联系的30家大学医院中,有20家回复了请求。患者信息和同意书在数据假名化传输给第三方及再次联系方面呈现出不同的情况。大多数数据收集(n = 13)符合整合到NAPKON的标准;四项研究需要对监管文件进行调整。三个队列不适合纳入NAPKON。柏林的TMF - 网络医学研究的技术、方法和基础设施通过一份法律意见阐述了通过研究条款(《德国数据保护法》第27条)进行回顾性数据整合和无同意数据使用的法律框架。NAPKON指导委员会选择的两个用例(慕尼黑大学的CORKUM;柏林夏里特大学医学中心的Pa-COVID-19)被用于在2021年底前展示NAPKON中数据整合的可行性。根据规范对病例进行了质量保证和基于绩效的报销。基于这些结果,可以针对各种情况制定建议,以便创建诸如数据整合的互操作性、接口和数据模型等技术操作前提条件,并在整合现有队列数据时满足关于伦理、数据保护、医疗保密和数据访问的监管要求。早在研究规划阶段就应考虑将数据整合到研究网络及其二次使用的可能性——特别是在知情同意方面——以便最大限度地提高所收集数据的效益。