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  • Supporting the distributed execution of clinical guidelines by multiple agents

    Author(s)
    Bottrighi, Alessio
    Piovesan, Luca
    Terenziani, Paolo
    Griffith University Author(s)
    Terenziani, Paolo
    Year published
    2019
    Metadata
    Show full item record
    Abstract
    Clinical guidelines (GLs) are widely adopted in order to improve the quality of patient care, and to optimize it. To achieve such goals, their application on a specific patient usually requires the interventions of different agents, with different roles (e.g., physician, nurse), abilities (e.g., specialist in the treatment of alcohol-related problems) and contexts (e.g., many chronic patients may be treated at home). Additionally, the responsibility of the application of a guideline to a patient is usually retained by a physician, but delegation of responsibility (of the whole guideline, or of a part of it) is often used\required ...
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    Clinical guidelines (GLs) are widely adopted in order to improve the quality of patient care, and to optimize it. To achieve such goals, their application on a specific patient usually requires the interventions of different agents, with different roles (e.g., physician, nurse), abilities (e.g., specialist in the treatment of alcohol-related problems) and contexts (e.g., many chronic patients may be treated at home). Additionally, the responsibility of the application of a guideline to a patient is usually retained by a physician, but delegation of responsibility (of the whole guideline, or of a part of it) is often used\required (e.g., delegation to a specialist), as well as the possibility, for a responsible, to select the executor of an action (e.g., a physician may retain the responsibility of an action, but delegate to a nurse its execution). To manage such phenomena, proper support to agent interaction and communication must be provided, providing agents with facilities for (1) treatment continuity (2) contextualization, (3) responsibility assignment and delegation (4) check of agent “appropriateness”. In this paper we extend GLARE, a computerized GL management system, to support such needs. We illustrate our approach by means of a practical case study.
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    Journal Title
    Artificial Intelligence in Medicine
    Volume
    98
    DOI
    https://doi.org/10.1016/j.artmed.2019.05.001
    Subject
    Engineering
    Delegation and execution
    Distributed execution of clinical guideline
    Knowledge representation
    Management of agents' qualification and capabilities
    Management of responsibility
    Publication URI
    http://hdl.handle.net/10072/387232
    Collection
    • Journal articles

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