Meurers Thierry, Otte Karen, Abu Attieh Hammam, Briki Farah, Despraz Jérémie, Halilovic Mehmed, Kaabachi Bayrem, Milicevic Vladimir, Müller Armin, Papapostolou Grigorios, Wirth Felix Nikolaus, Raisaro Jean Louis, Prasser Fabian
Health Data Science Center, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
Biomedical Data Science Center, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland.
NPJ Digit Med. 2025 May 14;8(1):279. doi: 10.1038/s41746-025-01644-9.
Anonymized biomedical data sharing faces several challenges. This systematic review analyzes 1084 PubMed-indexed studies (2018-2022) using anonymized biomedical data to quantify usage trends across geographic, regulatory, and cultural regions to identify effective approaches and inform implementation agendas. We identified a significant yearly increase in such studies with a slope of 2.16 articles per 100,000 when normalized against the total number of PubMed-indexed articles (p = 0.021). Most studies used data from the US, UK, and Australia (78.2%). This trend remained when normalized by country-specific research output. Cross-border sharing was rare (10.5% of studies). We identified twelve common data sources, primarily in the US (seven) and UK (three), including commercial (seven) and public entities (five). The prevalence of anonymization in the US, UK, and Australia suggests their practices could guide broader adoption. Rare cross-border anonymized data sharing and differences between countries with comparable regulations underscore the need for global standards.
匿名生物医学数据共享面临若干挑战。本系统综述分析了1084篇发表于《医学索引》(2018 - 2022年)且使用匿名生物医学数据的研究,以量化地理、监管和文化区域的使用趋势,从而确定有效的方法并为实施议程提供参考。我们发现,相对于《医学索引》收录文章总数进行标准化处理后,此类研究每年显著增加,斜率为每10万篇文章中有2.16篇(p = 0.021)。大多数研究使用来自美国、英国和澳大利亚的数据(78.2%)。按各国特定研究产出进行标准化处理后,这一趋势依然存在。跨境共享很少见(占研究的10.5%)。我们确定了十二个常见数据源,主要在美国(七个)和英国(三个),包括商业机构(七个)和公共实体(五个)。美国、英国和澳大利亚的匿名化普及情况表明,它们的做法可指导更广泛的采用。跨境匿名数据共享罕见以及法规类似国家之间存在差异,凸显了制定全球标准的必要性。