Authors:
Jose Manuel Gómez-Pérez
1
;
Sandra Kohler
1
;
Ricardo Melero
1
;
Pablo Serrano
2
;
Leonardo Lezcano
3
;
Miguel Angel Sicilia
3
;
Ana Iglesias
4
;
Elena Castro
4
;
Margarita Rubio
5
and
Manuel De Buenaga
6
Affiliations:
1
iSOCO S.A, Spain
;
2
Hospital de Fuenlabrada, Spain
;
3
Universidad de Alcalá de Henares, Spain
;
4
Universidad Carlos III, Spain
;
5
Universidad Europea de Madrid, Spain
;
6
Universidad Europea De Madrid, Spain
Keyword(s):
Semantic interoperability in eHealth, CEN 13606, Archetypes, NLP, OWL, SNOMED.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Cloud Computing
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Data Engineering
;
e-Business
;
e-Health
;
Enterprise Information Systems
;
Health Information Systems
;
Healthcare Management Systems
;
Integration/Interoperability
;
Interoperability
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Platforms and Applications
;
Semantic Interoperability
;
Sensor Networks
;
Simulation and Modeling
;
Software Agents and Internet Computing
;
Software and Architectures
;
Support for Clinical Decision-Making
;
Symbolic Systems
Abstract:
The interoperability problem in eHealth can only be addressed by means of combining standards and technology. However, these alone do not suffice. An appropriate framework that articulates such combination is required. In this paper, we adopt a three-dimensional (information, concept, and inference) approach for such framework, based on OWL as formal language for terminological and ontological health resources, SNOMED CT as lexical backbone for all such resources, and the standard CEN 13606 for representing EHRs. Based on such framework, we propose a novel form for creating and supporting networks of clinical terminologies. Additionally, we propose a number of software modules to semantically process and exploit EHRs, including NLP-based search and inference, which can support medical applications in heterogeneous and distributed eHealth systems.