Details
| Original language | English |
|---|---|
| Pages (from-to) | 223-240 |
| Number of pages | 18 |
| Journal | Health and Technology |
| Volume | 7 |
| Issue number | 2-3 |
| Early online date | 22 Mar 2017 |
| Publication status | Published - 1 Nov 2017 |
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
- Adverse Event prediction, Anonymity, Electronic health records, Genetic analysis, Linked2Safety, Personal data protection, Semantic Interoperability
ASJC Scopus subject areas
- Biochemistry, Genetics and Molecular Biology(all)
- Biotechnology
- Chemical Engineering(all)
- Bioengineering
- Immunology and Microbiology(all)
- Applied Microbiology and Biotechnology
- Engineering(all)
- Biomedical Engineering
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In: Health and Technology, Vol. 7, No. 2-3, 01.11.2017, p. 223-240.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Advancing clinical research by semantically interconnecting aggregated medical data information in a secure context
AU - Antoniades, Athos
AU - Aristodimou, Aristos
AU - Georgousopoulos, Christos
AU - Forgó, Nikolaus
AU - Gledson, Ann
AU - Hasapis, Panagiotis
AU - Vandeleur, Caroline
AU - Perakis, Konstantinos
AU - Sahay, Ratnesh
AU - Mehdi, Muntazir
AU - Demetriou, Christiana A.
AU - Strippoli, Marie Pierre F.
AU - Giotaki, Vasiliki
AU - Ioannidi, Myrto
AU - Tian, David
AU - Tozzi, Federica
AU - Keane, John
AU - Pattichis, Constantinos
N1 - Funding Information: MASTOS received approval from the Cyprus National Bioethics Committee and was funded by the Research Promotion Foundation of Cyprus and the Cyprus Institute of Neurology and Genetics.
PY - 2017/11/1
Y1 - 2017/11/1
N2 - 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.
AB - 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.
KW - Adverse Event prediction
KW - Anonymity
KW - Electronic health records
KW - Genetic analysis
KW - Linked2Safety
KW - Personal data protection
KW - Semantic Interoperability
UR - http://www.scopus.com/inward/record.url?scp=85034765376&partnerID=8YFLogxK
U2 - 10.1007/s12553-017-0188-0
DO - 10.1007/s12553-017-0188-0
M3 - Article
AN - SCOPUS:85034765376
VL - 7
SP - 223
EP - 240
JO - Health and Technology
JF - Health and Technology
SN - 2190-7188
IS - 2-3
ER -