Authors:
Ricardo Ferreira
1
;
Manuel Eduardo Correia
1
;
Francisco Rocha-Gonçalves
2
and
Ricardo Cruz-Correia
3
Affiliations:
1
INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Portugal
;
2
Instituto Português de Oncologia do Porto, Portugal
;
3
University of Porto, Portugal
Keyword(s):
Health Level Seven, Healthcare Integration, Production Measurement.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Cloud Computing
;
Collaboration and e-Services
;
Complex Systems Modeling and Simulation
;
Data Engineering
;
Data Management and Quality
;
Data Manipulation
;
Data Visualization
;
Decision Support Systems
;
e-Business
;
e-Health
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Integration/Interoperability
;
Interoperability
;
Knowledge Management
;
Knowledge Management and Information Sharing
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Platforms and Applications
;
Sensor Networks
;
Simulation and Modeling
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Software and Architectures
;
Symbolic Systems
;
Web Information Systems and Technologies
Abstract:
The improvements made to healthcare IT systems made over the past years led to the creation of a multitude of different applications essential to the institutions daily operations. Aim: We aim to create and install a system capable of displaying production metrics for healthcare management with little requirements, efforts and software providers involved.
Methods: We propose a system capable of displaying production metrics for healthcare facilities, by extracting HL7 messages and other eHealth relevant protocols directly from the institution´s network infrastructure. Our system is then able to populate a knowledge database with meaningful information derived from the gathered data. Results: Our system is currently being
tested on a large healthcare facility where it extracts and analyses a daily average of 44,000 HL7 messages. The system is currently capable of inferring and displaying the daily distribution of healthcare related activities such as laboratory orders or even rele
vant billing information. Conclusion: HL7 messages moving over the network contain valuable information that can then
be used to assess many relevant production metrics for the entire facility and from otherwise non-interoperable production systems that, in most cases, can only be seen as black boxes by other system integrators.
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