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OBJECTIVES: The aim of this study was to estimate the impact of new medical technologies on public healthcare expenditures in Israel over the period 2000-07. METHODS: For each year, government estimates for the costs of new technologies recommended as high-priority for public funding were summarized. The ratio of projected costs of these technologies to total public healthcare expenditures was calculated and compared with actual governmental budget allocations for new technologies. RESULTS: Funding all new high-priority medical technologies would have increased healthcare expenditures by 2.1 percent per year. Government allocations for new technologies raised expenditures by 1.0 percent per year. CONCLUSIONS: New medical technologies significantly increase healthcare expenditures in Israel. Budgetary constraints have reduced their actual impact by 52 percent. This study indicates the need for an annual addition of 2 percent to public healthcare budget for funding new high-priority technologies.  相似文献   

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This study compares the impact of sugar‐sweetened beverages (SSBs) tax between moderate and high consumers in Australia. The key methodological contribution is that price response heterogeneity is identified while controlling for censoring of consumption at zero and endogeneity of expenditure by using a finite mixture instrumental variable Tobit model. The SSB price elasticity estimates show a decreasing trend across increasing consumption quantiles, from ?2.3 at the median to ?0.2 at the 95th quantile. Although high consumers of SSBs have a less elastic demand for SSBs, their very high consumption levels imply that a tax would achieve higher reduction in consumption and higher health gains. Our results also suggest that an SSB tax would represent a small fiscal burden for consumers whatever their pre‐policy level of consumption, and that an excise tax should be preferred to an ad valorem tax. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

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Economic theory suggests that income growth could lead to changes in consumption quantity and quality as the spending on a commodity changes. Similarly, the volume and quality of healthcare consumption could rise with incomes because of demographic changes, usage of innovative medical technologies, and other factors. Hospital healthcare spending is the largest component of aggregate US healthcare expenditures. The novel contribution of our paper is estimating and decomposing the income elasticity of hospital care expenditures (HOCEXP) into its quantity and quality components. By using a 1999–2008 panel dataset of the 50 US states, results from the seemingly unrelated regressions model estimation reveal the income elasticity of HOCEXP to be 0.427 (std. error = 0.044), with about 0.391 (calculated std. error = 0.044) arising from care quality improvements and 0.035 (std. error = 0.050) emanating from the rise in usage volume. Our novel research findings suggest the following: (i) the quantity part of hospital expenditure is inelastic to income change; (ii) almost the entire income‐induced rise in hospital expenditure comes from care quality changes; and (iii) the 0.427 income elasticity of HOCEXP, the largest component of total US healthcare expenditure, makes hospital care a normal commodity and a much stronger technical necessity than aggregate healthcare. Policy implications are discussed. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

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This paper extends the line‐segment parametrization of the structural measurement error (ME) model to situations in which the error variance on both variables is not constant over all observations. Under these conditions, we develop a method‐of‐moments estimate of the slope, and derive its asymptotic variance. We further derive an accurate estimator of the variability of the slope estimate based on sample data in a rather general setting. We perform simulations that validate our results and demonstrate that our estimates are more precise than estimates under a different model when the ME variance is not small. Finally, we illustrate our estimation approach using real data involving heteroscedastic ME, and compare its performance with that of earlier models. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

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The roles of income and technology as the major determinants of aggregate healthcare expenditure (HEXP) continue to interest economists and health policy researchers. Concepts and measures of medical technologies remain complex; however, income (on the demand side) and technology (on the supply side) are important drivers of HEXP. This paper presents analysis of Australia's HEXP, using time‐series econometrics modeling techniques applied to 1971–2011 annual aggregate data. Our work fills two important gaps in the literature. First, we model the determinants of Australia's HEXP using the latest and longest available data series. Second, this novel study investigates several alternative technology proxies (input and output measures), including economy‐wide research and development expenditures, hospital research expenditures, mortality rate, and two technology indexes based on medical devices. We then apply the residual component method and the technology proxy approach to quantify the technology effects on HEXP. Our empirical results suggest that Australian aggregate healthcare is a normal good and a technical necessity with the income elasticity estimates ranging from 0.51 to 0.97, depending on the model. The estimated technology effects on HEXP falling in the 0.30–0.35 range and mimicking those in the literature using the US data, reinforce the global spread of healthcare technology. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

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We estimate the causal impact of having full health insurance on healthcare expenditures. We take advantage of a unique quasi‐experimental setup in which deductibles and co‐payments were zero in a managed care plan and nonzero in regular insurance, until a policy change forced all individuals with an active plan to cover a minimum amount of their expenses. Using panel data and a nonlinear difference‐in‐differences strategy, we find a demand elasticity of about ?0.14 comparing full insurance with the cost‐sharing model and a significant upward shift in the likelihood to generate costs. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

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This paper is the first to use the method of instrumental variables (IV) to estimate the impact of obesity on medical costs in order to address the endogeneity of weight and to reduce the bias from reporting error in weight. Models are estimated using restricted-use data from the Medical Expenditure Panel Survey for 2000-2005. The IV model, which exploits genetic variation in weight as a natural experiment, yields estimates of the impact of obesity on medical costs that are considerably higher than the estimates reported in the previous literature. For example, obesity is associated with $656 higher annual medical care costs, but the IV results indicate that obesity raises annual medical costs by $2741 (in 2005 dollars). These results imply that the previous literature has underestimated the medical costs of obesity, resulting in underestimates of the economic rationale for government intervention to reduce obesity-related externalities.  相似文献   

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Fixed‐effects meta‐analysis has been criticized because the assumption of homogeneity is often unrealistic and can result in underestimation of parameter uncertainty. Random‐effects meta‐analysis and meta‐regression are therefore typically used to accommodate explained and unexplained between‐study variability. However, it is not unusual to obtain a boundary estimate of zero for the (residual) between‐study standard deviation, resulting in fixed‐effects estimates of the other parameters and their standard errors. To avoid such boundary estimates, we suggest using Bayes modal (BM) estimation with a gamma prior on the between‐study standard deviation. When no prior information is available regarding the magnitude of the between‐study standard deviation, a weakly informative default prior can be used (with shape parameter 2 and rate parameter close to 0) that produces positive estimates but does not overrule the data, leading to only a small decrease in the log likelihood from its maximum. We review the most commonly used estimation methods for meta‐analysis and meta‐regression including classical and Bayesian methods and apply these methods, as well as our BM estimator, to real datasets. We then perform simulations to compare BM estimation with the other methods and find that BM estimation performs well by (i) avoiding boundary estimates; (ii) having smaller root mean squared error for the between‐study standard deviation; and (iii) better coverage for the overall effects than the other methods when the true model has at least a small or moderate amount of unexplained heterogeneity. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

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