Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité Junior Digital Clinician Scientist Program, Berlin, Germany.
Stud Health Technol Inform. 2023 May 18;302:28-32. doi: 10.3233/SHTI230058.
Data sharing provides benefits in terms of transparency and innovation. Privacy concerns in this context can be addressed by anonymization techniques. In our study, we evaluated anonymization approaches which transform structured data in a real-world scenario of a chronic kidney disease cohort study and checked for replicability of research results via 95% CI overlap in two differently anonymized datasets with different protection degrees. Calculated 95% CI overlapped in both applied anonymization approaches and visual comparison presented similar results. Thus, in our use case scenario, research results were not relevantly impacted by anonymization, which adds to the growing evidence of utility-preserving anonymization techniques.
数据共享在透明性和创新性方面具有优势。在此背景下，隐私问题可以通过匿名化技术来解决。在我们的研究中，我们评估了在慢性肾脏病队列研究的真实场景中对结构化数据进行匿名化的方法，并通过在两个具有不同保护级别且不同程度匿名化的数据集之间进行 95%置信区间（CI）重叠检查，以检查研究结果的可重复性。在两种应用的匿名化方法中，计算出的 95%CI 均有重叠，并且直观对比也给出了相似的结果。因此，在我们的用例场景中，匿名化并未对研究结果产生显著影响，这进一步证明了保留效用的匿名化技术的实用性。
