%0期刊文章%@ 1438- 8871% I Gunther Eysenbach %V 14% N 1% P e33% T开放健康数据去识别方法:遗产健康奖申请数据集%A El Emam,Khaled %A Arbuckle,Luk %A Koru,Gunes %A Eze,Benjamin %A Gaudette,Lisa %A Neri,Emilio %A Rose,Sean %A Howard,Jeremy %A Gluck,Jonathan %+电子健康信息实验室，CHEO研究所，Inc, 401 Smyth Road, Ottawa, ON, K1H 8L1, Canada, 1 738 4181, kelemam@uottawa.ca %K开放数据%K去识别%K隐私%D 2012 %7 27.02.2012 %9原始论文%J J Med Internet Res %G英文%X背景:开放数据集有很多好处。然而，对隐私的担忧阻碍了开放健康数据的广泛创建。在创建公共卫生数据方面，缺乏记录在案的方法和案例研究。我们描述了一种在传统健康奖(HHP)的背景下创建纵向公共卫生数据集的新方法。HHP是一项全球数据挖掘竞赛，通过使用索赔数据来预测患者在随后一年的住院天数。获胜者将是模型精度超过阈值的团队或个人，并将获得300万美元的现金奖励。HHP开始于2011年4月4日，结束于2013年4月3日。目的:对HHP竞赛中使用的索赔数据进行去识别，并确保其符合美国健康保险可携带性和责任法案(HIPAA)隐私规则的要求。 Methods: We defined a threshold risk consistent with the HIPAA Privacy Rule Safe Harbor standard for disclosing the competition dataset. Three plausible re-identification attacks that can be executed on these data were identified. For each attack the re-identification probability was evaluated. If it was deemed too high then a new de-identification algorithm was applied to reduce the risk to an acceptable level. We performed an actual evaluation of re-identification risk using simulated attacks and matching experiments to confirm the results of the de-identification and to test sensitivity to assumptions. The main metric used to evaluate re-identification risk was the probability that a record in the HHP data can be re-identified given an attempted attack. Results: An evaluation of the de-identified dataset estimated that the probability of re-identifying an individual was .0084, below the .05 probability threshold specified for the competition. The risk was robust to violations of our initial assumptions. Conclusions: It was possible to ensure that the probability of re-identification for a large longitudinal dataset was acceptably low when it was released for a global user community in support of an analytics competition. This is an example of, and methodology for, achieving open data principles for longitudinal health data. %M 22370452 %R 10.2196/jmir.2001 %U //www.mybigtv.com/2012/1/e33/ %U https://doi.org/10.2196/jmir.2001 %U http://www.ncbi.nlm.nih.gov/pubmed/22370452