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  • META-GLARE’s Supports to Agent Coordination

    Author(s)
    Anselma, L
    Bottrighi, A
    Piovesan, L
    Terenziani, P
    Griffith University Author(s)
    Terenziani, Paolo
    Year published
    2019
    Metadata
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    Abstract
    Clinical Guidelines (GLs) provide evidence-based recommendations to suggest to physicians the “best” medical treatments, and are widely used to enhance the quality of patient care, and to optimize it. In many cases, the treatment of patients cannot be provided by a unique healthcare agent, operating in a unique context. For instance, the treatment of chronic patients is usually performed not only in the hospital, but also at home and\or in the general practitioner’s ambulatory, and many healthcare agents (e.g., different specialist, nurses, family doctor) may be involved. To grant the quality of the treatments, all such ...
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    Clinical Guidelines (GLs) provide evidence-based recommendations to suggest to physicians the “best” medical treatments, and are widely used to enhance the quality of patient care, and to optimize it. In many cases, the treatment of patients cannot be provided by a unique healthcare agent, operating in a unique context. For instance, the treatment of chronic patients is usually performed not only in the hospital, but also at home and\or in the general practitioner’s ambulatory, and many healthcare agents (e.g., different specialist, nurses, family doctor) may be involved. To grant the quality of the treatments, all such agents must cooperate and interact. A computer-based support to GL execution is important to provide facilities for coordinating such different agents, and for granting that, at any time, the actions to be executed have a “proper” person in charge and executor, and are executed in the correct context. Additionally, also facilities to support the delegation of responsibility should also be considered. In this paper we extend META-GLARE, a computerized GL management system, to support such needs providing facilities for (1) treatment continuity (2) action contextualization, (3) responsibility assignment and delegation (4) check of agent “appropriateness”. Specific attention is also devoted to the temporal dimension, to grant that each action is executed according to the temporal constraints possibly present in the GL. We illustrate our approach by means of a practical case study.
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    Conference Title
    Biomedical Engineering Systems and Technologies
    Volume
    1024
    DOI
    https://doi.org/10.1007/978-3-030-29196-9_24
    Subject
    Software engineering
    Science & Technology
    Life Sciences & Biomedicine
    Engineering, Biomedical
    Medical Informatics
    Publication URI
    http://hdl.handle.net/10072/392772
    Collection
    • Conference outputs

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