Designing the accident and emergency system: lessons from manufacturing.
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OBJECTIVES: To review the literature on manufacturing process design and demonstrate applicability in health care. METHODS: Literature review and application of theory using two years activity data from two healthcare communities and extensive observation of activities over a six week period by seven researchers. RESULTS: It was possible to identify patient flows that could be used to design treatment processes around the needs of the patient. Some queues are built into existing treatment processes and can be removed by better process design. Capacity imbalance, not capacity shortage, causes some unnecessary waiting in accident and emergency departments. CONCLUSIONS: Clinicians would find that modern manufacturing theories produce more acceptable designs of systems. In particular, good quality is seen as a necessary pre-requisite of fast, efficient services. (+info)
Would a prehospital practitioner model improve patient care in rural Australia?
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BACKGROUND: Existing rural prehospital models have been criticised for being isolated from the healthcare system, and for following inflexible clinical protocols. Greater reliance on clinical judgement and informed decision making in the prehospital setting offer the potential to improve patient care. METHODS: Soft systems methodology was used to develop and critically appraise the prehospital practitioner model as an alternative to existing models. This approach started from the philosophical viewpoint that prehospital services should be patient centred. Soft systems methodology was used to structure the elements of prehospital systems and the relations between them into metaphors and pictures that could be analysed. RESULTS: This analysis showed that the most powerful reason for advocating the prehospital practitioner model is that it places prehospital systems within a symbiotic relationship with the healthcare system. Unlike the existing emergency service models or the "chain of survival" model, it is an integrated system that provides a range of services at multiple points during the patient care cycle. Thus, the prehospital practitioner would have roles in the prevention of injury and illness, responding to emergencies, facilitating recovery, and planning future strategies for a healthy community. CONCLUSIONS: Implementing this new model would see the prehospital system using its available capacity more effectively to fulfill broader public health and primary care outreach roles than is currently the case. Patients would be referred or transported to the most appropriate and cost effective facility as part of a seamless system that provides patients with well organised and high quality care. (+info)
A natural class of robust networks.
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As biological studies shift from molecular description to system analysis we need to identify the design principles of large intracellular networks. In particular, without knowing the molecular details, we want to determine how cells reliably perform essential intracellular tasks. Recent analyses of signaling pathways and regulatory transcription networks have revealed a common network architecture, termed scale-free topology. Although the structural properties of such networks have been thoroughly studied, their dynamical properties remain largely unexplored. We present a prototype for the study of dynamical systems to predict the functional robustness of intracellular networks against variations of their internal parameters. We demonstrate that the dynamical robustness of these complex networks is a direct consequence of their scale-free topology. By contrast, networks with homogeneous random topologies require fine-tuning of their internal parameters to sustain stable dynamical activity. Considering the ubiquity of scale-free networks in nature, we hypothesize that this topology is not only the result of aggregation processes such as preferential attachment; it may also be the result of evolutionary selective processes. (+info)
The organization of the microbial biodegradation network from a systems-biology perspective.
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Microbial biodegradation of environmental pollutants is a field of growing importance because of its potential use in bioremediation and biocatalysis. We have studied the characteristics of the global biodegradation network that is brought about by all the known chemical reactions that are implicated in this process, regardless of their microbial hosts. This combination produces an efficient and integrated suprametabolism, with properties similar to those that define metabolic networks in single organisms. The characteristics of this network support an evolutionary scenario in which the reactions evolved outwards from the central metabolism. The properties of the global biodegradation network have implications for predicting the fate of current and future environmental pollutants. (+info)
Parallel analysis of transcript and metabolic profiles: a new approach in systems biology.
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The past few years in the medical and biological sciences have been characterized by the advent of systems biology. However, despite the well-known connectivity between the molecules described by transcriptomic, proteomic and metabolomic approaches, few studies have tried to correlate parameters across the various levels of systemic description. When comparing the discriminatory power of metabolic and RNA profiling to distinguish between different potato tuber systems, using the techniques described here suggests that metabolic profiling has a higher resolution than expression profiling. When applying pairwise transcript-metabolite correlation analyses, 571 of the 26,616 possible pairs showed significant correlation, most of which was novel and included several strong correlations to nutritionally important metabolites. We believe this approach to be of high potential value in the identification of candidate genes for modifying the metabolite content of biological systems. (+info)
Unraveling nature's networks.
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A report on the meeting 'Unravelling Nature's Networks: from Microarray and Proteomic Analysis to Systems Biology', Sheffield, UK, 21-22 July 2003. (+info)
Advancing a theoretical model for public health and health promotion indicator development: proposal from the EUHPID consortium.
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This paper discusses the work of the EUHPID Project to develop a European Health Promotion Monitoring System based on a common set of health promotion indicators. The Project has established three working groups to progress this task--health promotion policy and practice-driven, data-driven and theory-driven. The work of the latter group is reviewed in particular. EUHPID has taken a systems theory approach in order to develop a model as a common frame of reference and a rational basis for the selection, organization and interpretation of health promotion indicators. After reviewing the strengths and weaknesses of those health promotion models currently proposed for indicator development, the paper proposes a general systems model of health development, and specific analytical, socio-ecological models related to public health and health promotion. These are described and discussed in detail. Taking the Ottawa Charter as the preferred framework for health promotion, the socio-ecological model for health promotion adopts its five action areas to form five types of systems. The structure and processes for each of these five systems are proposed to form the basis of a classification system for health promotion indicators. The paper goes on to illustrate such a system with reference to indicators in the workplace setting. The EUHPID Consortium suggest that their socio-ecological model could become a common reference point for the public health field generally, and offer an invitation to interested readers to contribute to this development. (+info)
Nonlinear systems in medicine.
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Many achievements in medicine have come from applying linear theory to problems. Most current methods of data analysis use linear models, which are based on proportionality between two variables and/or relationships described by linear differential equations. However, nonlinear behavior commonly occurs within human systems due to their complex dynamic nature; this cannot be described adequately by linear models. Nonlinear thinking has grown among physiologists and physicians over the past century, and non-linear system theories are beginning to be applied to assist in interpreting, explaining, and predicting biological phenomena. Chaos theory describes elements manifesting behavior that is extremely sensitive to initial conditions, does not repeat itself and yet is deterministic. Complexity theory goes one step beyond chaos and is attempting to explain complex behavior that emerges within dynamic nonlinear systems. Nonlinear modeling still has not been able to explain all of the complexity present in human systems, and further models still need to be refined and developed. However, nonlinear modeling is helping to explain some system behaviors that linear systems cannot and thus will augment our understanding of the nature of complex dynamic systems within the human body in health and in disease states. (+info)