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Anonymization of Electronic Medical Records to Support Clinical Analysis

Part of the SpringerBriefs in Electrical and Computer Engineering Book Series

DOI: 10.1007/978-1-4614-5668-1

ISBN: 978-1-4614-5667-4

Publisher: Springer New York - Springer Journals

Sep 13, 2012

Available

Introduction

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 1 –8

[This chapter provides an introduction to the problem of anonymizing patient data derived from Electronic Medical Record (EMR) systems. We first illustrate the need for sharing such data, in a privacy-preserving way, to support a growing number of medical applications. Subsequently, we consider...
Available

Overview of Patient Data Anonymization

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 9 –30

[This chapter presents an overview of anonymization techniques that can be used to protect different types of patient data. We first discuss anonymization principles that can prevent identity and sensitive information disclosure in demographic data publishing, as well as algorithms for enforcing...
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Re-identification of Clinical Data Through Diagnosis Information

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 31 –38

[In this chapter, we present an attack that can associate patients with their diagnosis and genomic information. The attack involves linking the published data with external, identified datasets, based on diagnosis codes. After motivating the need to prevent the attack, we discuss the type of...
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Preventing Re-identification While Supporting GWAS

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 39 –53

[This chapter discusses how clinical data can be published in a way that prevents re-identification attacks, while supporting the validation of Genome-Wide Association Studies (GWAS). After motivating the problem in Sect. 4.1, we provide an overview of an approach that deals with it [5, 9] in...
Available

Case Study on Electronic Medical Records Data

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 55 –64

[This chapter presents a case study, which demonstrates that attackers can link GWAS-related patient data with external, identified data sources, based on diagnosis codes, to re-identify patients and infer their DNA sequences. Section 5.1 discusses the characteristics of the electronic medical...
Available

Conclusions and Open Research Challenges

Gkoulalas-Divanis, Aris; Loukides, Grigorios

Pages: 65 –69

[In this book, we have explained why EMR data need to be disseminated in a way that prevents patient re-identification. We have provided an overview of data sharing policies and regulations, which serve as a first line of defence but are unable to provide computational privacy guarantees, and...

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