匿名化成本:使用临床数据的案例研究
Lisa Pilgram1,2, Thierry Meurers3, Bradley Malin4
1Junior Digital Clinician Scientist Program, Biomedical Innovation Academy, Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany.
Journal of medical Internet research
|April 24, 2024
概括
匿名临床数据平衡了隐私和实用性. 使用案例特定的匿名化提供了更好的实用性,保留了研究的统计属性,同时保护了患者信息.
科学领域:
- 医疗信息学 医疗信息学
- 数据科学数据科学数据科学
- 健康数据 隐私数据 隐私数据
背景情况:
- 临床数据共享加速了研究,但也面临着隐私障碍.
- 匿名算法减轻了重新识别的风险,但可以改变统计属性.
- 匿名化中的隐私-实用性权衡需要现实世界的证据,而这些证据很少.
研究的目的:
- 在现实临床环境中评估匿名数据的隐私-实用性权衡.
- 综合评估来自德国慢性病 (GCKD) 研究的不同匿名数据集.
主要方法:
- 使用了GCKD数据集 (5217条记录,70个变量).
- 应用了两步程序来识别重新识别风险并设置风险值 (0.02-1).
- 使用概括和抑制转换数据,通过通用和特定用例配置变化匿名化;使用一般 (细粒度,) 和特定 (可重复性) 度量评估实用性.
主要成果:
- 可重复性 (95%CI重叠>90%) 超过了一般效用指标 (细粒度68.2-87.6%,度25.5-46.2%).
- 观察到最少不重叠的95%CI (6/所有分析);大多数估计显示>50%的重叠.
- 使用案例特定的匿名化在同等的隐私级别下,比通用方法的可复制性更高.
结论:
- 匿名化在支持多种,潜在的竞争性数据用途方面面临挑战.
- 使用特定案例的匿名化可以提高数据实用性,同时保持隐私.
- 在评估各种应用程序的匿名数据时,请考虑成本和隐私水平.
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