March Stefanie, Andrich Silke, Drepper Johannes, Horenkamp-Sonntag Dirk, Icks Andrea, Ihle Peter, Kieschke Joachim, Kollhorst Bianca, Maier Birga, Meyer Ingo, Müller Gabriele, Ohlmeier Christoph, Peschke Dirk, Richter Adrian, Rosenbusch Marie-Luise, Scholten Nadine, Schulz Mandy, Stallmann Christoph, Swart Enno, Wobbe-Ribinski Stefanie, Wolter Antke, Zeidler Jan, Hoffmann Falk
Institut für Sozialmedizin und Gesundheitsökonomie (ISMG), Medizinische Fakultät, Otto-von-Guericke-Universität Magdeburg, Magdeburg.
Institut für Versorgungsforschung und Gesundheitsökonomie, Centre for Health and Society, Medizinische Fakultät, Heinrich-Heine-Universität Düsseldorf, Düsseldorf.
Gesundheitswesen. 2019 Aug;81(8-09):636-650. doi: 10.1055/a-0962-9933. Epub 2019 Aug 8.
Individual data linkage of different data sources for research purposes is being increasingly used in Germany in recent years. However, generally accepted methodological guidance is missing. The aim of this article is to define such methodological standards for research projects. Another aim is to provide readers with a checklist for critical appraisal of research proposals and articles. Since 2016, an expert panel of members of different German scientific societies have worked together and developed 7 guidelines with a total of 27 practical recommendations. These recommendations include (1) research aims, questions, data sources and resources, (2) infrastructure and data flow, (3) data privacy, (4) ethics, (5) key variables and type of linkage, (6) data validation/quality assurance and (7) long-term use for future research questions. The authors provide a rationale for each recommendation. Future revisions will include any new developments in science and data privacy.
近年来,出于研究目的对不同数据源进行个体数据关联在德国越来越多地被使用。然而,目前缺少普遍认可的方法学指导。本文的目的是为研究项目定义此类方法学标准。另一个目的是为读者提供一份用于批判性评估研究提案和文章的清单。自2016年以来,来自不同德国科学协会的成员组成的专家小组共同努力,制定了7项指南,共提出27条实用建议。这些建议包括:(1)研究目的、问题、数据源和资源;(2)基础设施和数据流;(3)数据隐私;(4)伦理;(5)关键变量和关联类型;(6)数据验证/质量保证;(7)为未来研究问题的长期使用。作者为每条建议提供了理论依据。未来的修订将纳入科学和数据隐私方面的任何新进展。