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Privacy Protection and Aggregate Health Data: A Review of Tabular Cell Suppression Methods (Not) Employed in Public Health Data Systems

机译：隐私保护和总体健康数据：公共健康数据系统中采用的表格式细胞抑制方法（非）综述

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Public health research often relies on individuals’ confidential medical data. Therefore, data collecting entities, such as states, seek to disseminate this medical data as widely as possible while still maintaining the privacy of the individual for legal and ethical reasons. One common way in which this medical data is released is through the use of Web-based Data Query Systems (WDQS). In this article, we examined WDQS listed in the National Association for Public Health Statistics and Information Systems (NAPHSIS) specifically reviewing them for how they prevent statistical disclosure in queries that produce a tabular response. One of the most common methods to combat this type of disclosure is through the use of suppression, that is, if a cell count in a table is below a certain threshhold, the true value is suppressed. This technique does work to prevent the direct disclosure of small cell counts, however, primary suppression by itself is not always enough to preserve privacy in tabular data. Here, we present several real examples of tabular response queries that employ suppression, but we are able to infer the values of the suppressed cells, including cells with 1 counts, which could be linked to auxiliary data sources and thus has the possibility to create an identity disclosure. We seek to stimulate awareness of the potential for disclosure of information that individuals may wish to keep private through an online query system. This research is undertaken in the hope that privacy concerns can be dealt with preemptively rather than only after a major disclosure has taken place. In the wake of a such an event, a major concern is that state and local officials would react to this by permanently shutting down these sites and cutting off a valuable source of research data.
机译：公共卫生研究通常依赖于个人的机密医疗数据。因此，数据收集实体（例如州）寻求尽可能广泛地传播此医疗数据，同时出于法律和道德原因仍保持个人的隐私。发布此医疗数据的一种常见方式是使用基于Web的数据查询系统（WDQS）。在本文中，我们检查了美国国家公共卫生统计和信息系统协会（NAPHSIS）列出的WDQS，专门审查了它们如何防止在产生表格响应的查询中进行统计披露。对抗这种类型的公开的最常见方法之一是通过使用抑制，即，如果表中的单元格计数低于某个阈值，则将抑制真实值。这项技术确实可以防止小单元格数目的直接泄露，但是，其主要抑制本身并不总是足以保留表格数据中的隐私。在这里，我们提供了采用抑制的表格响应查询的几个实际示例，但是我们能够推断出被抑制的单元格的值，包括计数为1的单元格，这些值可以链接到辅助数据源，因此有可能创建一个身份披露。我们寻求激发人们对可能希望通过在线查询系统保密的信息泄露的意识。进行这项研究的目的是希望可以先行解决隐私问题，而不是仅在进行重大披露后才能解决。在发生此类事件之后，主要的担忧是，州和地方官员将通过永久关闭这些站点并切断宝贵的研究数据源来对此做出反应。

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