@article{ref1,
title="Individual privacy versus public good: protecting confidentiality in health research",
journal="Statistics in Medicine",
year="2015",
author="O'Keefe, Christine M. and Rubin, Donald B.",
volume="34",
number="23",
pages="3081-3103",
abstract="Health and medical data are increasingly being generated, collected, and stored in electronic form in healthcare facilities and administrative agencies. Such data hold a wealth of information vital to effective health policy development and evaluation, as well as to enhanced clinical care through evidence-based practice and safety and quality monitoring. These initiatives are aimed at improving individuals' health and well-being. Nevertheless, analyses of health data archives must be conducted in such a way that individuals' privacy is not compromised. One important aspect of protecting individuals' privacy is protecting the confidentiality of their data. It is the purpose of this paper to provide a review of a number of approaches to reducing disclosure risk when making data available for research, and to present a taxonomy for such approaches. Some of these methods are widely used, whereas others are still in development. It is important to have a range of methods available because there is also a range of data-use scenarios, and it is important to be able to choose between methods suited to differing scenarios. In practice, it is necessary to find a balance between allowing the use of health and medical data for research and protecting confidentiality. This balance is often presented as a trade-off between disclosure risk and data utility, because methods that reduce disclosure risk, in general, also reduce data utility. Copyright © 2015 John Wiley & Sons, Ltd.<p /> <p>Language: en</p>",
language="en",
issn="0277-6715",
doi="10.1002/sim.6543",
url="http://dx.doi.org/10.1002/sim.6543"
}