Kimura Eizen, Chida Koji, Ikarashi Dai, Hamada Koki, Ishihara Ken
Department of Medical Informatics, Ehime University Hospital, Ehime, Japan.
Stud Health Technol Inform. 2012;180:1117-9.
The Act for the Protection of Personal Information in Japan considers as personal information any quasi-identifier that may be used to obtain information that identifies individuals through comparisons with datasets. Studies using health records are not widely conducted because of the concern regarding the safety of anonymized health records. To increase the safety of such records, we used the Pk-anonymity method. In this method, attributes are probabilistically randomized and then reconstructions are performed on the basis of statistical information from perturbed data. Hence, it is expected to provide more precise statistics and more reliably preserve privacy than the traditional "k-anonymity" method. We anonymized health records, performed cross tabulation, and assessed the error rate using original data. This study shows that the Pk-anonymity method can be used to perform safety statistical disclosures with low error rates, even in small cases.
日本的《个人信息保护法》将任何可能通过与数据集进行比较来获取识别个人信息的准标识符都视为个人信息。由于担心匿名化健康记录的安全性，使用健康记录的研究并未广泛开展。为提高此类记录的安全性，我们采用了Pk匿名方法。在这种方法中，属性以概率方式随机化，然后根据扰动数据的统计信息进行重构。因此，与传统的“k匿名”方法相比，预计它能提供更精确的统计数据，并更可靠地保护隐私。我们对健康记录进行匿名化处理，进行交叉制表，并使用原始数据评估错误率。本研究表明，即使在小样本情况下，Pk匿名方法也可用于进行低错误率的安全统计披露。
