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

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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.

Original languageEnglish
Pages (from-to)223-240
Number of pages18
JournalHealth and Technology
Issue number2-3
Publication statusPublished - 1 Nov 2017
Externally publishedYes


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


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