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

16 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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