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Authors: Roberto Gatta 1 ; Mauro Vallati 2 ; Carlo Cappelli 3 ; Berardino De Bari 4 ; Massimo Salvetti 3 ; Silvio Finardi 5 ; Maria Lorenza Muiesan 3 ; Vincenzo Valentini 1 and Maurizio Castellano 3

Affiliations: 1 Università Cattolica del Sacro Cuore, Italy ; 2 University of Huddersfield, United Kingdom ; 3 University of Brescia, Italy ; 4 Centre Hospitalier Universitaire Vaudois, Switzerland ; 5 A.O. Spedali Civili di Brescia, Italy

Keyword(s): Decision Support System, Computer Interpretable Guidelines, Electronic Health Record.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Cardiovascular Technologies ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Electronic Health Records and Standards ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Health Information Systems ; Healthcare Management Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Knowledge-Based Systems ; Ontologies and the Semantic Web ; Society, e-Business and e-Government ; Symbolic Systems ; Web Information Systems and Technologies

Abstract: Decision Support Systems (DSSs) are systems that supports decision-making activities. Their application in medical domain needs to face the critical issue of retrieving information from heterogeneous existing data sources, such as Electronic Health Records (EHRs). It is well-known that there exists a huge problem of standardisation. In fact, EHRs can represent the same knowledge in many different ways. It is evident that the applicability of DSSs strongly relies on the availability of homogeneous collections of data. On the other hand, the gap between DSSs and different EHRs can be bridged by exploiting middleware technologies. In this paper, we tested CSL, a technology designed for working as a middleware between DSS and EHRs, which is able to combine data taken from different EHR sources and to provide abstract and homogeneous data to DSSs. Moreover, CSL has been used for implementing three Clinical Guidelines, in order to test its capability in representing complex work-flows. The performed analysis highlight strengths and limitations of the proposed approach. (More)

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Paper citation in several formats:
Gatta, R.; Vallati, M.; Cappelli, C.; De Bari, B.; Salvetti, M.; Finardi, S.; Muiesan, M.; Valentini, V. and Castellano, M. (2016). Bridging the Gap between Knowledge Representation and Electronic Health Records. In Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - HEALTHINF; ISBN 978-989-758-170-0; ISSN 2184-4305, SciTePress, pages 159-165. DOI: 10.5220/0005648801590165

@conference{healthinf16,
author={Roberto Gatta. and Mauro Vallati. and Carlo Cappelli. and Berardino {De Bari}. and Massimo Salvetti. and Silvio Finardi. and Maria Lorenza Muiesan. and Vincenzo Valentini. and Maurizio Castellano.},
title={Bridging the Gap between Knowledge Representation and Electronic Health Records},
booktitle={Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - HEALTHINF},
year={2016},
pages={159-165},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005648801590165},
isbn={978-989-758-170-0},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2016) - HEALTHINF
TI - Bridging the Gap between Knowledge Representation and Electronic Health Records
SN - 978-989-758-170-0
IS - 2184-4305
AU - Gatta, R.
AU - Vallati, M.
AU - Cappelli, C.
AU - De Bari, B.
AU - Salvetti, M.
AU - Finardi, S.
AU - Muiesan, M.
AU - Valentini, V.
AU - Castellano, M.
PY - 2016
SP - 159
EP - 165
DO - 10.5220/0005648801590165
PB - SciTePress