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The problems associated with planning and managing patient treatment through complex care settings are significant. It has long been realised that support tools are invaluable in ensuring quality and consistency of care in a domain characterised by complex information spread over widely differing contexts. This paper focuses on the temporal nature of medical support tools and describes structures designed to accommodate their representation and reasoning requirements. The paper discusses the temporal facilities of the CIG-Plan medical care planning system and critically compares our work with contemporary research in the medical guideline and AI Planning communities. [ABSTRACT FROM AUTHOR]

Information System and Information Technology (IS/IT) development and implementation have become more difficult with the rapid introduction of new technology and the increasing complexity of the marketplace. IS/IT projects often encounter a range of problems that can be described as failure. Thus, learning from an analysis of past projects and from the issues contributing to failure is becoming a major stage in the risk management process. In IS/IT projects, it is common for groups of stakeholders to participate in planning and management. One important element in these activities is risk assessment, that is, the identification of potential risks and their interrelationships throughout the project lifecycle. The ability to visualise cause and effect risk networks and the capability for interactive network building and modification have the potential for individual and group risk identification, justification and prediction. In this paper we introduce Causal Mapping as a method of accomplishing this, and describe two experiments: one carried out with a group of masters-level students and a second with practitioners from a government organization who had experienced an IS/IT project failure. These two exploratory experiments have demonstrated the potential (and also some of the problems) of the approach in identifying problem areas in past projects, through the collaborative construction of cause and effect maps that allow project participants to visualise their perceptions. [ABSTRACT FROM AUTHOR]

The UK National Health Service (NHS) is currently undergoing an intensive review into the way patient care is designed, delivered and recorded. One important element of this is the development of care pathways (clinical guidelines) that provide a reasoned plan of care for each patient journey, based on locally-agreed, evidence-based best practice. The ability to generate, critique, and continually evaluate and modify plans of patient care is considered important and challenging, but in the case of computerised systems, the possibilities are exciting. In this paper we outline the case for incorporating AI Planning technology in the generation, evaluation and manipulation of care plans. We demonstrate that an integrative approach to its adoption in the clinical guideline domain is called for. The PROforma Clinical Guideline Modelling Language is used to demonstrate the issues involved. [ABSTRACT FROM AUTHOR]