996 resultados para Price grant, Venezuela.
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Estimating the financial value of pain informs issues as diverse as the market price of analgesics, the cost-effectiveness of clinical treatments, compensation for injury, and the response to public hazards. Such valuations are assumed to reflect a stable trade-off between relief of discomfort and money. Here, using an auction-based health-market experiment, we show that the price people pay for relief of pain is strongly determined by the local context of the market, that is, by recent intensities of pain or immediately disposable income (but not overall wealth). The absence of a stable valuation metric suggests that the dynamic behavior of health markets is not predictable from the static behavior of individuals. We conclude that the results follow the dynamics of habit-formation models of economic theory, and thus, this study provides the first scientific basis for this type of preference modeling.
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First, recent studies on the information preservation (IP) method, a particle approach for low-speed micro-scale gas flows, are reviewed. The IP method was validated for benchmark issues such as Couette, Poiseuille and Rayleigh flows, compared well with measured data for typical internal flows through micro-channels and external flows past micro flat plates, and combined with the Navier-Stokes equations to be a hybrid scheme for subsonic, rarefied gas flows. Second, the focus is moved to the microscopic characteristic of China stock market, particularly the price correlation between stock deals. A very interesting phenomenon was found that showed a reverse transition behaviour between two neighbouring price changes. This behaviour significantly differs from the transition rules for atomic and molecular energy levels, and it is very helpful to understand the essential difference between stock markets and nature.
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Background: Despite being the third largest tobacco producer in the world, Brazil has developed a comprehensive tobacco control policy that includes a broad restriction on both advertising and smoking in indoor public places, compulsory pictorial warning labels, and a menthol cigarette ban. However, tax and pricing policies have been developed slowly and only very recently were stronger measures implemented. This study investigated the expected responses of smokers to hypothetical price increases in Brazil.Methods: We analyzed smokers' responses to hypothetical future price increases according to sociodemographic characteristics and smoking conditions in a multistage sample of Brazilian current cigarette smokers aged >= 14 years (n = 500). Logistic regression analysis was used to examine the relationship between possible responses and different predictors.Results: in most subgroups investigated, smokers most frequently said they would react to a hypothetical price increase by taking up alternatives that might have a positive impact on health, i.e., they would try to stop smoking (52.3%) or smoke fewer cigarettes (46.8%). However, a considerable percentage responded that they would use alternatives that would reduce the effect of price increases, such as the same brand with lower cost (48.1%). After controlling for sex age group (14-19, 20-39, 40-59, and >= 60 years), schooling level (>= 9 versus <= 9 years), number of cigarettes per day (>20 versus <= 20), and stage of change for smoking cessation (precontemplation, contemplation, and preparation), lower levels of dependence were positively associated with the response I would try to stop smoking (odds ratio [OR], 2.19). Young age was associated with I would decrease the number of cigarettes (OR, 3.44). A low schooling level was strongly associated with all responses.Conclusions: Taxes and prices increases have great potential to stimulate cessation or reduction of cigarette consumption further among two important vulnerable populations of smokers in Brazil: young smokers and those of low educational level. the results from the present study also suggest that seeking illegal products may reduce the impact of increased taxes, but does not eliminate it.
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http://www.archive.org/details/catholicindianmi013196mbp
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Background: Elective repeat caesarean delivery (ERCD) rates have been increasing worldwide, thus prompting obstetric discourse on the risks and benefits for the mother and infant. Yet, these increasing rates also have major economic implications for the health care system. Given the dearth of information on the cost-effectiveness related to mode of delivery, the aim of this paper was to perform an economic evaluation on the costs and short-term maternal health consequences associated with a trial of labour after one previous caesarean delivery compared with ERCD for low risk women in Ireland.Methods: Using a decision analytic model, a cost-effectiveness analysis (CEA) was performed where the measure of health gain was quality-adjusted life years (QALYs) over a six-week time horizon. A review of international literature was conducted to derive representative estimates of adverse maternal health outcomes following a trial of labour after caesarean (TOLAC) and ERCD. Delivery/procedure costs derived from primary data collection and combined both "bottom-up" and "top-down" costing estimations.Results: Maternal morbidities emerged in twice as many cases in the TOLAC group than the ERCD group. However, a TOLAC was found to be the most-effective method of delivery because it was substantially less expensive than ERCD ((sic)1,835.06 versus (sic)4,039.87 per women, respectively), and QALYs were modestly higher (0.84 versus 0.70). Our findings were supported by probabilistic sensitivity analysis.Conclusions: Clinicians need to be well informed of the benefits and risks of TOLAC among low risk women. Ideally, clinician-patient discourse would address differences in length of hospital stay and postpartum recovery time. While it is premature advocate a policy of TOLAC across maternity units, the results of the study prompt further analysis and repeat iterations, encouraging future studies to synthesis previous research and new and relevant evidence under a single comprehensive decision model.
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Introduction: Copayments for prescriptions are associated with decreased adherence to medicines resulting in increased health service utilisation, morbidity and mortality. In October 2010 a 50c copayment per prescription item was introduced on the General Medical Services (GMS) scheme in Ireland, the national public health insurance programme for low-income and older people. The copayment was increased to €1.50 per prescription item in January 2013. To date, the impact of these copayments on adherence to prescription medicines on the GMS scheme has not been assessed. Given that the GMS population comprises more than 40% of the Irish population, this presents an important public health problem. The aim of this thesis was to assess the impact of two prescription copayments, 50c and €1.50, on adherence to medicines.Methods: In Chapter 2 the published literature was systematically reviewed with meta-analysis to a) develop evidence on cost-sharing for prescriptions and adherence to medicines and b) develop evidence for an alternative policy option; removal of copayments. The core research question of this thesis was addressed by a large before and after longitudinal study, with comparator group, using the national pharmacy claims database. New users of essential and less-essential medicines were included in the study with sample sizes ranging from 7,007 to 136,111 individuals in different medication groups. Segmented regression was used with generalised estimating equations to allow for correlations between repeated monthly measurements of adherence. A qualitative study involving 24 individuals was conducted to assess patient attitudes towards the 50c copayment policy. The qualitative and quantitative findings were integrated in the discussion chapter of the thesis. The vast majority of the literature on this topic area is generated in North America, therefore a test of generalisability was carried out in Chapter 5 by comparing the impact of two similar copayment interventions on adherence, one in the U.S. and one in Ireland. The method used to measure adherence in Chapters 3 and 5 was validated in Chapter 6. Results: The systematic review with meta-analysis demonstrated an 11% (95% CI 1.09 to 1.14) increased odds of non-adherence when publicly insured populations were exposed to copayments. The second systematic review found moderate but variable improvements in adherence after removal/reduction of copayments in a general population. The core paper of this thesis found that both the 50c and €1.50 copayments on the GMS scheme were associated with larger reductions in adherence to less-essential medicines than essential medicines directly after the implementation of policies. An important exception to this pattern was observed; adherence to anti-depressant medications declined by a larger extent than adherence to other essential medicines after both copayments. The cross country comparison indicated that North American evidence on cost-sharing for prescriptions is not automatically generalisable to the Irish setting. Irish patients had greater immediate decreases of -5.3% (95% CI -6.9 to -3.7) and -2.8% (95% CI -4.9 to -0.7) in adherence to anti-hypertensives and anti-hyperlipidaemic medicines, respectively, directly after the policy changes, relative to their U.S. counterparts. In the long term, however, the U.S. and Irish populations had similar behaviours. The concordance study highlighted the possibility of a measurement bias occurring for the measurement of adherence to non-steroidal anti-inflammatory drugs in Chapter 3. Conclusions: This thesis has presented two reviews of international cost-sharing policies, an assessment of the generalisability of international evidence and both qualitative and quantitative examinations of cost-sharing policies for prescription medicines on the GMS scheme in Ireland. It was found that the introduction of a 50c copayment and its subsequent increase to €1.50 on the GMS scheme had a larger impact on adherence to less-essential medicines relative to essential medicines, with the exception of anti-depressant medications. This is in line with policy objectives to reduce moral hazard and is therefore demonstrative of the value of such policies. There are however some caveats. The copayment now stands at €2.50 per prescription item. The impact of this increase in copayment has yet to be assessed which is an obvious point for future research. Careful monitoring for adverse effects in socio-economically disadvantaged groups within the GMS population is also warranted. International evidence can be applied to the Irish setting to aid in future decision making in this area, but not without placing it in the local context first. Patients accepted the introduction of the 50c charge, however did voice concerns over a rising price. The challenge for policymakers is to find the ‘optimal copayment’ – whereby moral hazard is decreased, but access to essential chronic disease medicines that provide advantages at the population level is not deterred. This evidence presented in this thesis will be utilisable for future policy-making in Ireland.
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A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.
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The research and development costs of 68 randomly selected new drugs were obtained from a survey of 10 pharmaceutical firms. These data were used to estimate the average pre-tax cost of new drug development. The costs of compounds abandoned during testing were linked to the costs of compounds that obtained marketing approval. The estimated average out-of-pocket cost per new drug is 403 million US dollars (2000 dollars). Capitalizing out-of-pocket costs to the point of marketing approval at a real discount rate of 11% yields a total pre-approval cost estimate of 802 million US dollars (2000 dollars). When compared to the results of an earlier study with a similar methodology, total capitalized costs were shown to have increased at an annual rate of 7.4% above general price inflation.