4 resultados para Strategic decision model

em Université de Lausanne, Switzerland


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INTRODUCTION: Hip fractures are responsible for excessive mortality, decreasing the 5-year survival rate by about 20%. From an economic perspective, they represent a major source of expense, with direct costs in hospitalization, rehabilitation, and institutionalization. The incidence rate sharply increases after the age of 70, but it can be reduced in women aged 70-80 years by therapeutic interventions. Recent analyses suggest that the most efficient strategy is to implement such interventions in women at the age of 70 years. As several guidelines recommend bone mineral density (BMD) screening of postmenopausal women with clinical risk factors, our objective was to assess the cost-effectiveness of two screening strategies applied to elderly women aged 70 years and older. METHODS: A cost-effectiveness analysis was performed using decision-tree analysis and a Markov model. Two alternative strategies, one measuring BMD of all women, and one measuring BMD only of those having at least one risk factor, were compared with the reference strategy "no screening". Cost-effectiveness ratios were measured as cost per year gained without hip fracture. Most probabilities were based on data observed in EPIDOS, SEMOF and OFELY cohorts. RESULTS: In this model, which is mostly based on observed data, the strategy "screen all" was more cost effective than "screen women at risk." For one woman screened at the age of 70 and followed for 10 years, the incremental (additional) cost-effectiveness ratio of these two strategies compared with the reference was 4,235 euros and 8,290 euros, respectively. CONCLUSION: The results of this model, under the assumptions described in the paper, suggest that in women aged 70-80 years, screening all women with dual-energy X-ray absorptiometry (DXA) would be more effective than no screening or screening only women with at least one risk factor. Cost-effectiveness studies based on decision-analysis trees maybe useful tools for helping decision makers, and further models based on different assumptions should be performed to improve the level of evidence on cost-effectiveness ratios of the usual screening strategies for osteoporosis.

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INTRODUCTION: This study sought to increase understanding of women's thoughts and feelings about decision making and the experience of subsequent pregnancy following stillbirth (intrauterine death after 24 weeks' gestation). METHODS: Eleven women were interviewed, 8 of whom were pregnant at the time of the interview. Modified grounded theory was used to guide the research methodology and to analyze the data. RESULTS: A model was developed to illustrate women's experiences of decision making in relation to subsequent pregnancy and of subsequent pregnancy itself. DISCUSSION: The results of the current study have significant implications for women who have experienced stillbirth and the health professionals who work with them. Based on the model, women may find it helpful to discuss their beliefs in relation to healing and health professionals to provide support with this in mind. Women and their partners may also benefit from explanations and support about the potentially conflicting emotions they may experience during this time.

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This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

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Background: The public health burden of coronary artery disease (CAD) is important. Perfusion cardiac magnetic resonance (CMR) is generally accepted to detect and monitor CAD. Few studies have so far addressed its costs and costeffectiveness. Objectives: To compare in a large CMR registry the costs of a CMR-guided strategy vs two hypothetical invasive strategies for the diagnosis and the treatment of patients with suspected CAD. Methods: In 3'647 patients with suspected CAD included prospectively in the EuroCMR Registry (59 centers; 18 countries) costs were calculated for diagnostic examinations, revascularizations as well as for complication management over a 1-year follow-up. Patients with ischemia-positive CMR underwent an invasive X-ray coronary angiography (CXA) and revascularization at the discretion of the treating physician (=CMR+CXA strategy). Ischemia was found in 20.9% of patients and 17.4% of them were revascularized. In ischemia-negative patients by CMR, cardiac death and non-fatal myocardial infarctions occurred in 0.38%/y. In a hypothetical invasive arm the costs were calculated for an initial CXA followed by FFR testing in vessels with ≥50% diameter stenoses (=CXA+FFR strategy). To model this hypothetical arm, the same proportion of ischemic patients and outcome was assumed as for the CMR+CXA strategy. The coronary stenosis - FFR relationship reported in the literature was used to derive the proportion of patients with ≥50% diameter stenoses (Psten) in the study cohort. The costs of a CXA-only strategy were also calculated. Calculations were performed from a third payer perspective for the German, UK, Swiss, and US healthcare systems.