Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold
Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold
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DOI：
10.3310/hta19140
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发表时间：
2015-02-01
影响因子：
3.6
通讯作者：
Sculpher, Mark
中科院分区：
文献类型：
--
作者：
Claxton, Karl;Martin, Steve;Sculpher, Mark
背景：成本效益分析涉及到一项新技术的增量成本效益比与成本效益阈值的比较，该技术比现有的替代技术成本更高。这表明预期从其使用中获得的健康是否超过由于其他保健活动被取代而预计在其他地方失去的健康。因此，这个阈值代表了由于流离失所而放弃1个质量调整生命年（QALY）必须强加给该系统的额外成本。国家健康和护理卓越研究所使用的成本效益阈值没有经验估计。目标：(1)提供定义成本效益阈值的概念框架，并为其经验估计提供基础。(2)利用英国国民保健服务的项目预算数据，估计国民保健服务总支出变化与死亡率变化之间的关系。(3)通过估算与对生命年的影响和对生命质量本身的额外直接影响相关的生活质量（QoL），将这种衡量支出变化对健康影响的死亡率指标扩展到生命年和生活质量年。(4)为政策目的提供成本效益阈值的最佳估计。方法：早期的计量经济学分析估计了跨规划预算类别（pbc）的初级保健信托（PCT）支出差异与相关疾病特异性死亡率之间的关系。这项研究在几个方面进行了扩展，包括估计NHS总体支出边际增加或减少对23个PBCs中每个国家支出的影响。进一步的工作阶段将计量经济学与质量年方面更广泛的健康影响联系起来。结果：最相关的“中心”阈值估计为每QALY 12,936美元（2008年支出，2008-10年死亡率）。不确定性分析表明，每个QALY阈值< f20,000的概率为0.89，每个QALY阈值< f30,000的概率为0.97。额外的“结构性”不确定性表明，总的来说，如果有的话，中心或最佳估计可能是高估。当pct面临更大的财政压力并且更有可能撤资而不是投资时，支出变化对健康的影响更大。这表明，对于所有对NHS造成净成本的技术，阈值的中心估计可能是高估的，对于对NHS成本有较大影响的技术，适用的适当阈值应该更低。局限性：中心估计数的基础是，在每一阶段确定一种首选分析，这种分析是根据最充分利用现有信息的分析，所要求的假设是否比现有的其他替代方法更合理，以及能否更全面地了解支出变化可能对健康产生的影响。然而，目前可用数据的局限性意味着总体阈值的估计存在很大的不确定性。结论：在考虑与新技术相关的健康效益是否大于NHS其他方面可能失去的健康效益时，这些方法在某种程度上提供了NHS面临的机会成本规模的经验估计。未来研究的优先事项包括估计后续支出和结果数据浪潮的阈值，例如利用临床委托组一级现有的支出和结果，以及收集的关于生活质量的额外数据和发病率（按年龄和性别）和疾病持续时间的最新估计。尽管如此，这项研究也开始使其他NHS患者（最终承担此类决策的机会成本）在社会决策中变得不那么抽象，而更加“为人所知”。
Background: Cost-effectiveness analysis involves the comparison of the incremental cost-effectiveness ratio of a new technology, which is more costly than existing alternatives, with the cost-effectiveness threshold. This indicates whether or not the health expected to be gained from its use exceeds the health expected to be lost elsewhere as other health-care activities are displaced. The threshold therefore represents the additional cost that has to be imposed on the system to forgo 1 quality-adjusted life-year (QALY) of health through displacement. There are no empirical estimates of the cost-effectiveness threshold used by the National Institute for Health and Care Excellence.Objectives: (1) To provide a conceptual framework to define the cost-effectiveness threshold and to provide the basis for its empirical estimation. (2) Using programme budgeting data for the English NHS, to estimate the relationship between changes in overall NHS expenditure and changes in mortality. (3) To extend this mortality measure of the health effects of a change in expenditure to life-years and to QALYs by estimating the quality-of-life (QoL) associated with effects on years of life and the additional direct impact on QoL itself. (4) To present the best estimate of the cost-effectiveness threshold for policy purposes.Methods: Earlier econometric analysis estimated the relationship between differences in primary care trust (PCT) spending, across programme budget categories (PBCs), and associated disease-specific mortality. This research is extended in several ways including estimating the impact of marginal increases or decreases in overall NHS expenditure on spending in each of the 23 PBCs. Further stages of work link the econometrics to broader health effects in terms of QALYs.Results: The most relevant 'central' threshold is estimated to be f 12,936 per QALY (2008 expenditure, 2008-10 mortality). Uncertainty analysis indicates that the probability that the threshold is < f 20,000 per QALY is 0.89 and the probability that it is < f 30,000 per QALY is 0.97. Additional 'structural' uncertainty suggests, on balance, that the central or best estimate is, if anything, likely to be an overestimate. The health effects of changes in expenditure are greater when PCTs are under more financial pressure and are more likely to be disinvesting than investing. This indicates that the central estimate of the threshold is likely to be an overestimate for all technologies which impose net costs on the NHS and the appropriate threshold to apply should be lower for technologies which have a greater impact on NHS costs.Limitations: The central estimate is based on identifying a preferred analysis at each stage based on the analysis that made the best use of available information, whether or not the assumptions required appeared more reasonable than the other alternatives available, and which provided a more complete picture of the likely health effects of a change in expenditure. However, the limitation of currently available data means that there is substantial uncertainty associated with the estimate of the overall threshold.Conclusions: The methods go some way to providing an empirical estimate of the scale of opportunity costs the NHS faces when considering whether or not the health benefits associated with new technologies are greater than the health that is likely to be lost elsewhere in the NHS. Priorities for future research include estimating the threshold for subsequent waves of expenditure and outcome data, for example by utilising expenditure and outcomes available at the level of Clinical Commissioning Groups as well as additional data collected on QoL and updated estimates of incidence (by age and gender) and duration of disease. Nonetheless, the study also starts to make the other NHS patients, who ultimately bear the opportunity costs of such decisions, less abstract and more 'known' in social decisions.