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Protecting patient privacy by quantifiable control of disclosures in disseminated databases.

Abstract：

:One of the fundamental rights of patients is to have their privacy protected by health care organizations, so that information that can be used to identify a particular individual is not used to reveal sensitive patient data such as diagnoses, reasons for ordering tests, test results, etc. A common practice is to remove sensitive data from databases that are disseminated to the public, but this can make the disseminated database useless for important public health purposes. If the degree of anonymity of a disseminated data set could be measured, it would be possible to design algorithms that can assure that the desired level of confidentiality is achieved. Privacy protection in disseminated databases can be facilitated by the use of special ambiguation algorithms. Most of these algorithms are aimed at making one individual indistinguishable from one or more of his peers. However, even in databases considered "anonymous", it may still be possible to obtain sensitive information about some individuals or groups of individuals with the use of pattern recognition algorithms. In this article, we study the problem of determining the degree of ambiguation in disseminated databases and discuss its implications in the development and testing of "anonymization" algorithms.

journal_name

Int J Med Inform

journal_title

International journal of medical informatics

authors

Ohno-Machado L,Silveira PS,Vinterbo S

doi

10.1016/j.ijmedinf.2004.05.002

subject

Has Abstract

pub_date

2004-08-01 00:00:00

pages

599-606

issue

7-8

eissn

1386-5056

issn

1872-8243

pii

S1386505604000942

journal_volume

73

pub_type

杂志文章

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