Towards the development of a decision support system for multi-agency decision-making during cross-border emergencies

Karen Neville*, Sheila O'Riordan, Andrew Pope, Marion Rauner, Maria Rochford, Martina Madden, James Sweeney, Alexander Nussbaumer, Nora McCarthy, Cian O'Brian

*Korrespondierende/r Autor/-in für diese Arbeit

    Publikation: Beitrag in einer FachzeitschriftArtikelBegutachtung

    Abstract

    Developing decision support systems for emergency situations is a complex and challenging task. These difficulties are compounded further in the case of cross-border emergencies, which often require the coordination and collaboration of independent agencies. These agencies have different structures and resources in place, and follow their own internal policies and procedures. If a number of countries have been affected, agencies may not even share the same language. Large-scale disasters, whether natural, deliberate, or accidental do not respect borders and come with a high risk to human life and a variety of economic and health impacts. Thus, it is the aim of the S-HELP (Securing-Health Emergency Learning Planning) project to develop a decision support tool-set that supports multi-agency decision-making during cross-border emergencies. S-HELP seeks to provide a tool-set that supports rapid and effective decision-making across all stages of the emergency management lifecycle (i.e. mitigation, preparedness, response, and recovery). To address the challenges associated with multi-agency emergency management, a holistic framed approach to healthcare preparedness, response, and recovery is proposed. This holistic framework has been created to guide the development of the S-HELP solution. The framework integrates a number of components important in the phased iterative development of an emergency management decision support system, such as, interoperability standards, risk communication, spatial data management, agile development, healthcare responder training, and scenario development for system evaluation.
    Originalspracheenglisch
    Seiten (von - bis)381-396
    Seitenumfang16
    FachzeitschriftJournal of Decision Systems
    Jahrgang25
    AusgabenummerSupplement 1
    DOIs
    PublikationsstatusVeröffentlicht - 2016

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