%0 Journal Article
%T Ensuring Confidentiality of Geocoded Health Data: Assessing Geographic Masking Strategies for Individual-Level Data
%A Paul A. Zandbergen
%J Advances in Medicine
%D 2014
%R 10.1155/2014/567049
%X Public health datasets increasingly use geographic identifiers such as an individualĄ¯s address. Geocoding these addresses often provides new insights since it becomes possible to examine spatial patterns and associations. Address information is typically considered confidential and is therefore not released or shared with others. Publishing maps with the locations of individuals, however, may also breach confidentiality since addresses and associated identities can be discovered through reverse geocoding. One commonly used technique to protect confidentiality when releasing individual-level geocoded data is geographic masking. This typically consists of applying a certain amount of random perturbation in a systematic manner to reduce the risk of reidentification. A number of geographic masking techniques have been developed as well as methods to quantity the risk of reidentification associated with a particular masking method. This paper presents a review of the current state-of-the-art in geographic masking, summarizing the various methods and their strengths and weaknesses. Despite recent progress, no universally accepted or endorsed geographic masking technique has emerged. Researchers on the other hand are publishing maps using geographic masking of confidential locations. Any researcher publishing such maps is advised to become familiar with the different masking techniques available and their associated reidentification risks. 1. Introduction The widespread availability of powerful geocoding tools in commercial Geographic Information System (GIS) software and the interest in spatial analysis at the individual level have made mapping residential addresses of individuals a widely employed technique in public health research [1¨C6]. Spatial analysis and mapping of georeferenced, individual-level health data can help identify important geographical patterns [1, 2, 7, 8]. However, given the need and/or legal requirement to preserve the confidentiality of microdata, the possibilities of undertaking geographical analysis on certain types of individual-level data are often limited [9, 10]. As a result of restrictions on access to confidential data, important information may remain inaccessible. Releasing locations of individuals in digital or paper format presents reidentifications risk since these locations can be reverse geocoded to find the addresses and identities associated with those locations. Geographic masking techniques have been developed to reduce the risk of reidentification. The present review describes the background for sharing and
%U http://www.hindawi.com/journals/amed/2014/567049/