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A generic solution for web-based management of pseudonymized data

Overview of attention for article published in BMC Medical Informatics and Decision Making, November 2015
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Title
A generic solution for web-based management of pseudonymized data
Published in
BMC Medical Informatics and Decision Making, November 2015
DOI 10.1186/s12911-015-0222-y
Pubmed ID
Authors

Ronald Lautenschläger, Florian Kohlmayer, Fabian Prasser, Klaus A. Kuhn

Abstract

Collaborative collection and sharing of data have become a core element of biomedical research. Typical applications are multi-site registries which collect sensitive person-related data prospectively, often together with biospecimens. To secure these sensitive data, national and international data protection laws and regulations demand the separation of identifying data from biomedical data and to introduce pseudonyms. Neither the formulation in laws and regulations nor existing pseudonymization concepts, however, are precise enough to directly provide an implementation guideline. We therefore describe core requirements as well as implementation options for registries and study databases with sensitive biomedical data. We first analyze existing concepts and compile a set of fundamental requirements for pseudonymized data management. Then we derive a system architecture that fulfills these requirements. Next, we provide a comprehensive overview and a comparison of different technical options for an implementation. Finally, we develop a generic software solution for managing pseudonymized data and show its feasibility by describing how we have used it to realize two research networks. We have found that pseudonymization models are highly heterogeneous, already on a conceptual level. We have compiled a set of requirements from different pseudonymization schemes. We propose an architecture and present an overview of technical options. Based on a selection of technical elements, we suggest a generic solution. It supports the multi-site collection and management of biomedical data. Security measures are multi-tier pseudonymity and physical separation of data over independent backend servers. Integrated views are provided by a web-based user interface. Our approach has been successfully used to implement a national and an international rare disease network. We were able to identify a set of core requirements out of several pseudonymization models. Considering various implementation options, we realized a generic solution which was implemented and deployed in research networks. Still, further conceptual work on pseudonymity is needed. Specifically, it remains unclear how exactly data is to be separated into distributed subsets. Moreover, a thorough risk and threat analysis is needed.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 9%
Researcher 2 9%
Other 1 4%
Lecturer 1 4%
Professor 1 4%
Other 3 13%
Unknown 13 57%
Readers by discipline Count As %
Computer Science 6 26%
Nursing and Health Professions 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Medicine and Dentistry 1 4%
Engineering 1 4%
Other 0 0%
Unknown 13 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 04 December 2015.
All research outputs
#18,431,664
of 22,834,308 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,571
of 1,990 outputs
Outputs of similar age
#279,619
of 387,533 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#30
of 33 outputs
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