Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Privacy Technology to Support Data Sharing for Comparative Effectiveness Research

A Systematic Review

Bibliographic Data

ID9101541
AuthorsXiaoqian Jiang (0000-0001-9933-2205, University of California San Diego, corresponding author), Anand D Sarwate (0000-0001-6123-5282, Toyota Technological Institute at Chicago), Lucila Ohno-Machado, Lucila Ohno‐Machado (0000-0002-8005-7327, University of California San Diego, corresponding author)
Year2013
Volume51
IssueSupplement 8Suppl 3
PagesS58-S65
Publication date2013-08-01
Open AccessNo
TypeARTICLE
VenueMedical Care (JOURNAL)
Journal identifiersISSN: 0025-7079 • E-ISSN: 1537-1948
PublisherOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e31829b1d10
PMID23774511
PMCIDPMC3728160
OpenAlexW2137285932
LanguageEN
References cited29

OBJECTIVE: Effective data sharing is critical for comparative effectiveness research (CER), but there are significant concerns about inappropriate disclosure of patient data. These concerns have spurred the development of new technologies for privacy-preserving data sharing and data mining. Our goal is to review existing and emerging techniques that may be appropriate for data sharing related to CER. MATERIALS AND METHODS: We adapted a systematic review methodology to comprehensively search the research literature. We searched 7 databases and applied 3 stages of filtering based on titles, abstracts, and full text to identify those works most relevant to CER. RESULTS: On the basis of agreement and using the arbitrage of a third party expert, we selected 97 articles for meta-analysis. Our findings are organized along major types of data sharing in CER applications (ie, institution-to-institution, institution hosted, and public release). We made recommendations based on specific scenarios. LIMITATION: We limited the scope of our study to methods that demonstrated practical impact, eliminating many theoretical studies of privacy that have been surveyed elsewhere. We further limited our study to data sharing for data tables, rather than complex genomic, set valued, time series, text, image, or network data. CONCLUSION: State-of-the-art privacy-preserving technologies can guide the development of practical tools that will scale up the CER studies of the future. However, many challenges remain in this fast moving field in terms of practical evaluations and applications to a wider range of data types

Comparative effectiveness research · Data science · Data sharing · Field (mathematics) · Health care · Information privacy · Internet privacy · Scope (computer science) · Set (abstract data type) · Computer Science · Ethics in Clinical Research · Medicine · Privacy-Preserving Technologies in Data · Privacy, Security, and Data Protection

  • K-Anonymity

    Latanya Sweeney•International Journal of…•2002

  • Privacy of medical records

    Open Access•David Baumer, David L Baumer et al.•ACM SIGCAS Computers and Society•2000

Highly citedNo

Tools

Open DOISci-HubOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae