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The literature on how to combine efficiency and equity considerations in the social valuation of health allocations has borrowed extensively from applied welfare economics, including the literature on inequality measurement. By so doing, it has adopted normative assumptions that have been applied for evaluating the allocation of welfare (or income) rather than the allocation of health, including the assumption of a monotonically declining social marginal value of welfare/income/health. At the same time, empirical studies that have elicited social preferences for allocation of health have reported results that are seemingly incompatible with this assumption. There are two ways of addressing this inconsistency; we may censor the stated preferences by arguing that they cannot be supported by normative arguments, or we may reject or modify the analytical framework in order to accommodate the stated preferences. We argue that the stated preferences can be supported by normative reasoning and therefore conclude that one should be cautious in applying the standard welfare economic framework to the allocation of health.  相似文献   
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The present paper concerns the criteria people would prefer for prioritising health programmes. It differs from most empirical studies as subjects were not asked about their personal preferences for programmes per se. Rather, they were asked about the principles that should guide the choice of programmes. Four different principles were framed as arguments for alternative programmes. The results from population surveys in Australia and Norway suggest that people are least supportive of the principle that decision makers should follow the stated preferences of the public. Rather, respondents expressed more support for decisions based upon health maximisation, equality and urgency. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   
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Background Getting medical treatment is still difficult and expensive in western China. Improving the equity of basic health services is one of the tasks of the new healthcare reform in China. This study aimed to analyze the parallel and vertical equity of health service utilization of urban residents and then find its influencing factors.
Methods In August 2011, a household survey was conducted at 18 communities of Baoji City by multi-stage stratified random sampling. Based on the survey data, we calculated a concentration index of health service utilization for different income residents and a difference index of different ages. We then investigated the influencing factors of health service utilization by employing the Logistic regression model and log-linear regression model.
Results The two-week morbidity rate of sampled residents was 19.43%, the morbidity rate of chronic diseases was 21.68%, and the required hospitalization rate after medical diagnosis was 11.36%. Among out-patient service utilization, the two-week out-patient rate, number of two-week out-patients, and out-patient expense had good parallel and vertical equity, while out-patient compensation expense had poor parallel and vertical equity. The inpatient service utilization, hospitalization rate, number of inpatients, days stayed in the hospital, and inpatient expense had good parallel equity, while inpatient compensation expense had poor parallel equity. While the hospitalization rate and number of inpatients had vertical equity, the days stayed in hospital, inpatient expense, and inpatient compensation expense had vertical inequity.
Conclusions Urban residents’ health was at a low level and there was not good health service utilization. There existed rather poor equity of out-patient compensation expense. The equity of inpatient service utilization was quite poor. Income difference and the type of medical insurance had great effects on the equity of health service utilization.
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Objective: The objective of this study was to define an improved classification for allocating incentives to support the recruitment and retention of doctors in rural Australia. Design and setting: Geo‐coded data (n = 3636 general practitioners (GPs)) from the national Medicine in Australia: Balancing Employment and Life study were used to examine statistical variation in four professional indicators (total hours worked, public hospital work, on call after‐hours and difficulty taking time off) and two non‐professional indicators (partner employment and schooling opportunities) which are all known to be related to difficulties with recruitment and retention. Main outcome measures: The main outcome measure used for the study was an association of six sentinel indicators for GPs with practice location and population size of community. Results: Four distinct homogeneous population size groups were identified (0–5000, 5001‐15 000, 15 001–50 000 and >50 000). Although geographical remoteness (measured using the Australian Standard Geographical Classification – Remoteness Areas (ASGC‐RA)) was statistically associated with all six indicators (P < 0.001), population size provided a more sensitive measure in directing where recruitment and retention incentives should be provided. A new six‐level rurality classification is proposed, based on a combination of four population size groups and the five ASGC‐RA levels. A significant increase in statistical association is measured in four of six indicators (and a slight increase in one indicator) using the new six‐level classification versus the existing ASGC‐RA classification. Conclusions: This new six‐level geographical classification provides a better basis for equitable resource allocation of recruitment and retention incentives to doctors based on the attractiveness of non‐metropolitan communities, both professionally and non‐professionally, as places to work and live.  相似文献   
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陈龙  曾凯  李莎  陶璐  梁玮  王皓岑  杨如美 《中国全科医学》2023,26(19):2423-2427
随着信息技术的发展,人工智能为疾病诊疗带来重要价值。然而,人工智能中存在算法偏见现象,可导致医疗卫生资源分配不均等问题,严重损害患者的健康公平。算法偏见是人为偏见的技术化体现,其形成与人工智能开发过程密切相关,主要源于数据收集、训练优化和输出应用3个方面。医护工作者作为患者健康的直接参与者,应采取相应措施以预防算法偏见,避免其引发健康公平问题。医护工作者需保障健康数据真实无偏见、优化人工智能的公平性和加强其输出应用的透明度,同时需思考如何处理临床实践中算法偏见引发的不公平现象,全面保障患者健康公平。本研究就健康领域中算法偏见的形成原因和应对策略展开综述,以期提高医护工作者识别和处理算法偏见的意识与能力,为保障信息化时代中的患者健康公平提供参考。  相似文献   
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Objective: To examine whether measures of remoteness areas adequately reveal high need populations, measured against socioeconomic disadvantage and physician to population ratios. Design: Exploratory spatial analysis of relationships between remoteness areas, medical workforce supply and the index of relative socioeconomic disadvantage (IRSD). Bivariate analyses examined associations between remoteness areas and IRSD. From this analysis, a composite score of deprivation was constructed combining measures of remoteness areas, physician to population ratios and IRSD, and validated against health outcome measures. These measures included avoidable mortality per 100 000, risk behaviour rate per 1000, diabetes rate per 1000. All analyses were conducted at the statistical local area level and weighted to be population representative. Results: The percentage of small areas and populations within the most socioeconomically disadvantaged quintile rose with increasing remoteness. However, 12.8% of small areas within major cities and 40.7% of outer regional areas were also within the lowest socioeconomic quintile. There was a strong relationship between our composite score of deprivation and avoidable mortality, risk rate, diabetes rate and per cent Indigenous. Regression analysis examined the relationship between each element of the composite score and health outcomes. This revealed that the association between avoidable mortality and remoteness was lost after controlling for per cent Indigenous. Conclusions: Using remoteness areas alone to prioritise workforce incentive programs and training requirements has significant limitations. Including measures of socioeconomic disadvantage and workforce supply would better target health inequities and improve resource allocation in Australia.  相似文献   
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The HIV‐epidemic is one of the greatest public health crises to face South Africa. A health care response to the treatment needs of HIV‐positive people is a prime example of the desirability of an economic, rational approach to resource allocation in the face of scarcity. Despite this, almost no input based on economic analysis is currently used in national strategic planning. While cost‐utility analysis is theoretically able to establish technical efficiency, in practice this is accomplished by comparing an intervention's ICER to a threshold level representing society's maximum willingness to pay to avoid death and improve health‐related quality of life. Such an approach has been criticised for a number of reasons, including that it is inconsistent with a fixed budget for health care and that equity is not taken into account. It is also impractical if no national policy on the threshold exists. As an alternative, this paper proposes a mathematical programming approach that is capable of highlighting technical efficiency, equity, the equity/efficiency trade‐off and the affordability of alternative HIV‐treatment interventions. Government could use this information to plan an HIV‐treatment strategy that best meets equity and efficiency objectives within budget constraints. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   
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