940 resultados para risk assessment


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PURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce "overuse" and "underuse" of increased-risk services.Genet Med 18 10, 1020-1028.

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This paper describes a framework that is being developed for the prediction and analysis of electronics power module reliability both for qualification testing and in-service lifetime prediction. Physics of failure (PoF) reliability methodology using multi-physics high-fidelity and reduced order computer modelling, as well as numerical optimization techniques, are integrated in a dedicated computer modelling environment to meet the needs of the power module designers and manufacturers as well as end-users for both design and maintenance purposes. An example of lifetime prediction for a power module solder interconnect structure is described. Another example is the lifetime prediction of a power module for a railway traction control application. Also in the paper a combined physics of failure and data trending prognostic methodology for the health monitoring of power modules is discussed.

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Hurricanes are destructive storms with strong winds, intense storm surges, and heavy rainfall. The resulting impact from a hurricane can include structural damage to buildings and infrastructure, flooding, and ultimately loss of human life. This paper seeks to identify the impact of Hurricane Ivan on the aected population of Grenada, one of the Caribbean islands. Hurricane Ivan made landfall on 7th September 2004 and resulted in 80% of the population being adversely aected. The methods that were used to model these impacts involved performing hazard and risk assessments using GIS and remote sensing techniques. Spatial analyses were used to create a hazard and a risk map. Hazards were identied initially as those caused by storm surges, severe winds speeds, and flooding events related to Hurricane Ivan. These estimated hazards were then used to create a risk map. An innovative approach was adopted, including the use of hillshading to assess the damage caused by high wind speeds. This paper explains in detail the methodology used and the results produced.

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At the start of the industrial revolution (circa 1750) the atmospheric concentration of carbon dioxide (CO2) was around 280 ppm. Since that time the burning of fossil fuel, together with other industrial processes such as cement manufacture and changing land use, has increased this value to 400 ppm, for the first time in over 3 million years. With CO2 being a potent greenhouse gas, the consequence of this rise for global temperatures has been dramatic, and not only for air temperatures. Global Sea Surface Temperature (SST) has warmed by 0.4–0.8 °C during the last century, although regional differences are evident (IPCC, 2007). This rise in atmospheric CO2 levels and the resulting global warming to some extent has been ameliorated by the oceanic uptake of around one quarter of the anthropogenic CO2 emissions (Sabine et al., 2004). Initially this was thought to be having little or no impact on ocean chemistry due to the capacity of the ocean’s carbonate buffering system to neutralise the acidity caused when CO2 dissolves in seawater. However, this assumption was challenged by Caldeira and Wickett (2005) who used model predictions to show that the rate at which carbonate buffering can act was far too slow to moderate significant changes to oceanic chemistry over the next few centuries. Their model predicted that since pre-industrial times, ocean surface water pH had fallen by 0.1 pH unit, indicating a 30% increase in the concentration of H+ ions. Their model also showed that the pH of surface waters could fall by up to 0.4 units before 2100, driven by continued and unabated utilisation of fossil fuels. Alongside increasing levels of dissolved CO2 and H+ (reduced pH) an increase in bicarbonate ions together with a decrease in carbonate ions occurs. These chemical changes are now collectively recognised as “ocean acidification”. Concern now stems from the knowledge that concentrations of H+, CO2, bicarbonate and carbonate ions impact upon many important physiological processes vital to maintaining health and function in marine organisms. Additionally, species have evolved under conditions where the carbonate system has remained relatively stable for millions of years, rendering them with potentially reduced capacity to adapt to this rapid change. Evidence suggests that, whilst the impact of ocean acidification is complex, when considered alongside ocean warming the net effect on the health and productivity of the oceans will be detrimental.

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In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.

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The purpose of this study is to develop a decision making system to evaluate the risks in E-Commerce (EC) projects. Competitive software businesses have the critical task of assessing the risk in the software system development life cycle. This can be conducted on the basis of conventional probabilities, but limited appropriate information is available and so a complete set of probabilities is not available. In such problems, where the analysis is highly subjective and related to vague, incomplete, uncertain or inexact information, the Dempster-Shafer (DS) theory of evidence offers a potential advantage. We use a direct way of reasoning in a single step (i.e., extended DS theory) to develop a decision making system to evaluate the risk in EC projects. This consists of five stages 1) establishing knowledge base and setting rule strengths, 2) collecting evidence and data, 3) determining evidence and rule strength to a mass distribution for each rule; i.e., the first half of a single step reasoning process, 4) combining prior mass and different rules; i.e., the second half of the single step reasoning process, 5) finally, evaluating the belief interval for the best support decision of EC project. We test the system by using potential risk factors associated with EC development and the results indicate that the system is promising way of assisting an EC project manager in identifying potential risk factors and the corresponding project risks.

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The bovine spongiform encephalopathy (BSE) outbreak in the United Kingdom is regarded as one of the worst public policy crises the British government has experienced during the postwar era. In material terms, it has led to the slaughter of 3.3 million cattle and estimated economic losses of £3.7 billion. In administrative terms, the crisis brought about the dissolution of the Ministry of Agriculture, Fisheries and Food. This article examines the istitutional context in which decisions about the scientific evidence on BSE were made. The authors argue that a centralized system in which government agencies control science for government is inherently vulnerable to alliances of experts and interest groups that undermine the credible assessment of public health and safety risks. Specific societal conditions may encourage risk-opportunistic behavior among policy makers that is conducive to delays and inaction until such time as the evidence of a health risk becomes overwhelming.

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The issue of inherited disorders in pedigree dogs is not a recent phenomenon and reports of suspected genetic defects associated with breeding practices date back to Charles Darwin's time. In recent years, much information on the array of inherited defects has been assimilated and the true extent of the problem has come to light. Historically, the direction of research funding in the field of canine genetic disease has been largely influenced by the potential transferability of findings to human medicine, economic benefit and importance of dogs for working purposes. More recently, the argument for a more canine welfare-orientated approach has been made, targeting research efforts at the alleviation of the most suffering in the greatest number of animals.

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