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Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs.

机译:在多中心经济评估中改进成本核算方法:对单位成本使用多重估算。

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摘要

Economic evaluations must use appropriate costing methods. However, in multicentre cost-effectiveness analyses (CEA) a fundamental issue of how best to measure and analyse unit costs has been neglected. Multicentre CEA commonly take the mean unit cost from a national database, such as NHS reference costs. This approach does not recognise that unit costs vary across centres and are unavailable in some centres. This paper proposes the use of multiple imputation (MI) to predict those centre-specific unit costs that are not available, while recognising the statistical uncertainty surrounding this imputation.We illustrate MI with a CEA of a multicentre randomised trial (1014 patients, 60 centres), implemented using multilevel modelling. We use MI to derive centre-specific unit costs, based on centre characteristics including average casemix, and compare this to using mean NHS reference costs. In this case study, using MI unit costs rather than mean reference costs led to less heterogeneity across centres, more precise estimates of incremental cost, but similar estimates of incremental cost-effectiveness.We conclude that using MI to predict unit costs can preserve correlations, maximise the use of available data, and, when combined with multilevel modelling is an appropriate method for recognising the statistical uncertainty in multicentre CEA.
机译:经济评估必须使用适当的成本核算方法。但是,在多中心成本效益分析(CEA)中,如何最好地衡量和分析单位成本的基本问题已被忽略。多中心CEA通常从国家数据库中获取平均单位成本,例如NHS参考成本。这种方法没有认识到各个中心的单位成本是不同的,并且在某些中心中是不可用的。本文提出了使用多重估算(MI)来预测那些无法获得的中心特定单位成本,同时又认识到这种估算存在的统计不确定性。我们通过一项多中心随机试验的CEA来说明MI(1014例患者,60个中心),使用多级建模来实现。我们根据中心特征(包括平均案例组合),使用MI得出中心特定的单位成本,并将其与使用NHS平均参考成本进行比较。在本案例研究中,使用MI单位成本而不是平均参考成本可以减少中心之间的异质性,可以更精确地估算增量成本,但是可以估算出增量成本效益类似。最大限度地利用可用数据,并且在与多级建模结合使用时,这是一种识别多中心CEA中统计不确定性的合适方法。

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