Although 70-80% of problems have some component of human error, its overall contribution to many problems may be small; studies of complex systems have revealed that up to 85 % are primarily due to deficiencies in the layout and processes of the system. The anaesthetist has to operate in a complex system; many problems originate from deficiencies in this system. Information of relevance to system failure was extracted from the first 2000 incidents reported to the Australian Incident Monitoring Study (AIMS). A system-based deficiency directly contributed to one-quarter of problems (four-fifths if human factors are included), some aspect of the system minimized the adverse outcome in over half of all cases (four-fifths if human factors are included), and in two-thirds (three-quarters if human factors are included) a system-based strategy would have been helpful; the system was implicated in 90% of all incidents (97% if human factors are included). Regardless of whether or not all human error should be regarded as part of the "system'; attempts to modify its incidence and nature have to emanate from the system. AIMS reporting pathways and the organizations involved in developing and implementing strategies to improve the system operate at four levels. Level I involves the use of AIMS reports by hospitals and group practices for audit at a local level. Level Il involves AIMS participants sending forms to the AIMS central office; collated information is then sent back to contributors by newsletter. Level III involves interaction between AIMS and the major professional bodies and level IV interaction between AIMS, these bodies and a variety of national and international agencies. Over 100 topics were identified from the AIMS data for consideration at one or more of these levels. AIMS has the potential not only to play a vital practical role in the continued enhancement of the quality of anaesthetic practice, but also to provide a valuable resource for research at the increasingly important interface between human behaviour and complex systems.
This paper discusses the problem of optimizing the utilization of communication satellite capacity. The modern fixed satellite service provider seeks improved methods to optimize the amount of service demand that is accommodated by capacity available on its satellite network. A mixed-integer programming (MIP) model is proposed for the solution of the problem, as part of a decision support tool. Such a tool integrates three system components, which are: a mathematical optimization model, an optimization algorithm, and a graphical user interface. This paper will discuss the design process associated with each component of the system and will conclude with preliminary results obtained from sample optimization runs.
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