Temporal constraints play a fundamental role in clinical guidelines. For example, temporal indeterminacy, constraints about duration, delays between actions and periodic repetitions of actions are essential in order to cope with clinical therapies. This paper proposes a computer- based approach in order to deal with temporal constraints in clinical guidelines. Specifically, it provides the possibility to represent such constraints and reason with them (i.e., perform inferences in the form of constraint propagation). We first propose a temporal representation formalism and two constraint propagation algorithms operating on it, and then we show how they can be exploited in order to provide clinical guideline systems with different temporal facilities. Our approach offers several advantages: for example, during the guideline acquisition phase, it enables to represent temporal constraints and to check their consistency; during the execution phase, it allows the physician to check the consistency between action execution-times and the constraints in the guidelines, and to provide queryanswering and temporal simulation facilities (e.g., when choosing among alternative paths in a guideline).

Automatic Treatment of Temporal Issues in Clinical Guidelines in the GLARE System

ANSELMA, LUCA;
2007

Abstract

Temporal constraints play a fundamental role in clinical guidelines. For example, temporal indeterminacy, constraints about duration, delays between actions and periodic repetitions of actions are essential in order to cope with clinical therapies. This paper proposes a computer- based approach in order to deal with temporal constraints in clinical guidelines. Specifically, it provides the possibility to represent such constraints and reason with them (i.e., perform inferences in the form of constraint propagation). We first propose a temporal representation formalism and two constraint propagation algorithms operating on it, and then we show how they can be exploited in order to provide clinical guideline systems with different temporal facilities. Our approach offers several advantages: for example, during the guideline acquisition phase, it enables to represent temporal constraints and to check their consistency; during the execution phase, it allows the physician to check the consistency between action execution-times and the constraints in the guidelines, and to provide queryanswering and temporal simulation facilities (e.g., when choosing among alternative paths in a guideline).
12th World Congress on Health (Medical) Informatics - Building Sustainable Health Systems
Brisbane, Australia
20 - 24 August 2007
Proceedings of the 12th World Congress on Health (Medical) Informatics - Building Sustainable Health Systems
IOS Press
Vol. 129
935
940
9781586037741
http://www.iospress.nl/loadtop/load.php?isbn=9781586037741
Artificial Intelligence; Clinical guidelines; Temporal reasoning
L. ANSELMA; P. TERENZIANI; S. MONTANI; A. BOTTRIGHI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/28940
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