Pseudonymization tools for medical research: a systematic review.

IF 3.3 3区 医学 Q2 MEDICAL INFORMATICS
Hammam Abu Attieh, Armin Müller, Felix Nikolaus Wirth, Fabian Prasser
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引用次数: 0

Abstract

Background: Pseudonymization is an important technique for the secure and compliant use of medical data in research. At its core, pseudonymization is a process in which directly identifying information is separated from medical research data. Due to its importance, a wide range of pseudonymization tools and services have been developed, and researchers face the challenge of selecting an appropriate tool for their research projects. This review aims to address this challenge by systematically comparing existing tools.

Methods: A systematic review was performed and is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines where applicable. The search covered PubMed and Web of Science to identify pseudonymization tools documented in the scientific literature. The tools were assessed based on predefined criteria across four key dimensions that describe researchers' requirements: (1) single-center vs. multi-center use, (2) short-term vs. long-term projects, (3) small data vs. big data processing, and (4) integration vs. standalone functionality.

Results: From an initial pool of 1,052 papers, 92 were selected for detailed full-text review after the title and abstract screening. This led to the identification of 20 pseudonymization tools, of which 10 met our inclusion criteria and were assessed. The results show that there are differences between the tools that make them more or less suited for research projects differing in regards to the dimensions described above, enabling us to provide targeted recommendations.

Conclusions: The landscape of existing pseudonymization tools is heterogeneous, and researchers need to carefully select the appropriate solutions for their research projects. Our findings highlight two Software-as-a-Service-based solutions that enable centralized use without local infrastructure, one tool for retrospective pseudonymization of existing databases, two tools suitable for local deployment in smaller, short-term projects, and two tools well-suited for local deployment in large, multi-center studies.

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来源期刊
CiteScore
7.20
自引率
5.70%
发文量
297
审稿时长
1 months
期刊介绍: BMC Medical Informatics and Decision Making is an open access journal publishing original peer-reviewed research articles in relation to the design, development, implementation, use, and evaluation of health information technologies and decision-making for human health.
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