Authors:
Johanne Bakalara
1
;
2
;
Thomas Guyet
3
;
2
;
Olivier Dameron
2
;
André Happe
4
and
Emmanuel Oger
1
Affiliations:
1
Univ. Rennes, EA-7449 REPERES, France
;
2
Univ. Rennes, Inria, IRISA-UMR6074, France
;
3
Institut Agro, Rennes, France
;
4
CHRU Brest, France
Keyword(s):
Temporal Query, Medico-administrative Databases, Sequences of Events, Chronicles, Semantic Web.
Abstract:
Medico-administrative databases contain information about patients’ medical events, i.e. their care trajectories. Semantic Web technologies are used by epidemiologists to query these databases in order to identify patients whose care trajectories conform to some criteria. In this article we are interested in care trajectories involving temporal constraints. In such cases, Semantic Web tools lack computational efficiency while temporal pattern matching algorithms are efficient but lack of expressiveness. We propose to use a temporal pattern called chronicles to represent temporal constraints on care trajectories. We also propose an hybrid approach, combining the expressiveness of SPARQL and the efficiency of chronicle recognition to query care trajectories. We evaluate our approach on synthetic data and real large data. The results show that the hybrid approach is more efficient than pure SPARQL, and validate the interest of our tool to detect patients having venous thromboembolism di
sease in the French medico-administrative database.
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