Advancing clinical research by semantically interconnecting aggregated medical data information in a secure context

  • Athos Antoniades
  • Aristos Aristodimou
  • Christos Georgousopoulos
  • Nikolaus Forgó
  • Ann Gledson
  • Panagiotis Hasapis
  • Caroline Vandeleur
  • Konstantinos Perakis
  • Ratnesh Sahay
  • Muntazir Mehdi
  • Christiana A. Demetriou
  • Marie-Pierre F. Strippoli
  • Vasiliki Giotaki
  • Myrto Ioannidi
  • David Tian
  • Federica Tozzi
  • John Keane
  • Constantinos Pattichis
Original Paper

DOI: 10.1007/s12553-017-0188-0

Cite this article as:
Antoniades, A., Aristodimou, A., Georgousopoulos, C. et al. Health Technol. (2017). doi:10.1007/s12553-017-0188-0
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Part of the following topical collections:
  1. Systems Medicine

Abstract

Electronic Health Records (EHRs) contain an increasing wealth of medical information. When combined with molecular level data, they enhance the understanding of the underlying biological mechanisms of diseases, enabling the identification of key prognostic biomarkers to disease and treatment outcomes. However, the European healthcare information space is fragmented due to the lack of legal and technical standards, cost effective platforms, and sustainable business models. There is a clear need for a framework facilitating the efficient and homogenized access to anonymized distributed EHRs, merged from multiple data sources into a single data analysis space. In this paper we present the outcomes of Linked2Safety, a project that proposes a solution to these problems by providing a semantically interconnected approach to sharing aggregate data in the form of data cubes. This approach eliminates the risks associated with sharing pseudoanonymized (and therefore still personal) data while enabling the multi-source, multi-type analysis of health data through a single web based secure access platform. The Linked2Safety system is evaluated by external to the project Medical science analysts, Analytic methodology engineers and Data providers with respect to five specific dimensions of the system (analysis space, linked data space, usability of the system, legal and ethical issues, and value of the system) in this paper. For all five dimensions that were examined, the participants’ perceptions were overwhelmingly positive.

Keywords

Semantic Interoperability Linked2Safety Electronic health records Personal data protection Anonymity Adverse Event prediction Genetic analysis 

Funding information

Funder NameGrant NumberFunding Note
Seventh Framework Programme
  • 288328

Copyright information

© IUPESM and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  • Athos Antoniades
    • 1
    • 2
  • Aristos Aristodimou
    • 1
    • 2
  • Christos Georgousopoulos
    • 3
  • Nikolaus Forgó
    • 4
  • Ann Gledson
    • 5
  • Panagiotis Hasapis
    • 3
  • Caroline Vandeleur
    • 6
  • Konstantinos Perakis
    • 7
  • Ratnesh Sahay
    • 8
  • Muntazir Mehdi
    • 8
  • Christiana A. Demetriou
    • 9
  • Marie-Pierre F. Strippoli
    • 6
  • Vasiliki Giotaki
    • 10
  • Myrto Ioannidi
    • 10
  • David Tian
    • 11
  • Federica Tozzi
    • 1
    • 2
  • John Keane
    • 5
  • Constantinos Pattichis
    • 1
  1. 1.University of CyprusNicosiaCyprus
  2. 2.Stremble Ventures LTDLimassolCyprus
  3. 3.INTRASOFT InternationalLuxembourg CityLuxembourg
  4. 4.Gottfried Wilhelm Leibniz Universität HannoverHannoverGermany
  5. 5.University of ManchesterManchesterUK
  6. 6.Centre Hospitalier Universitaire VaudoisLausanneSwitzerland
  7. 7.Ubitech Ltd.AthensGreece
  8. 8.Insight Centre for Data AnalyticsNUI GalwayGalwayIreland
  9. 9.Cyprus Institute of Neurology & GeneticsNicosiaCyprus
  10. 10.Zeincro Hellas S.A.VrillisiaGreece
  11. 11.Leeds Beckett UniversityLeedsUK

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