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.
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