A framework for an intelligent decision support system: A case in pathology test ordering

Zoe Yan Zhuang, Carla Wilkin, Andrzej Stefan Ceglowski

    Research output: Contribution to journalArticleResearchpeer-review

    26 Citations (Scopus)


    Decision context, knowledge management, decision makers, and decision strategy are fundamental components for understanding decision support systems (DSSs). This paper describes the specific case of designing a framework for an intelligent DSS in the context of pathology test ordering by general practitioners (GPs). In doing so it illustrates the processes of discovering practical and relevant knowledge from pathology request data generated and stored in a professional pathology company, investigates and understands the decision makers (GPs) through a survey about their current practices in test ordering and their requirements for decision support, and finally proposes an intelligent decision support framework as the decision strategy to support GPs in ordering pathology tests more effectively and appropriately. The process and framework developed through this case contributes effective guidance for practitioners and theoretical understanding concerning intelligent decision support in a complex environment.
    Original languageEnglish
    Pages (from-to)476 - 487
    Number of pages12
    JournalDecision Support Systems
    Issue number2
    Publication statusPublished - 2013

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