Center for Financing, Access and Cost Trends, Agency for Healthcare Research and Quality, Rockville, MD 20850, USA.
Health Econ. 2010 May;19(5):608-27. doi: 10.1002/hec.1498.
Health-care expenditure regressions are used in a wide variety of economic analyses including risk adjustment and program and treatment evaluations. Recent articles demonstrated that generalized gamma models (GGMs) and extended estimating equations (EEE) models provide flexible approaches to deal with a variety of data problems encountered in expenditure estimation. To date there have been few empirical applications of these models to expenditures. We use data from the US Medical Expenditure Panel Survey to compare the bias, predictive accuracy, and marginal effects of GGM and EEE models with other commonly used regression models in a cross-validation study design. Health-care expenditure distributions vary in the degree of heteroskedasticity, skewness, and kurtosis by type of service and population. To examine the ability of estimators to address a range of data problems, we estimate models of total health expenditures and prescription drug expenditures for two populations, the elderly and privately insured adults. Our findings illustrate the need for researchers to examine their assumptions about link functions: the appropriate link function varies across our four distributions. The EEE model, which has a flexible link function, is a robust estimator that performs as well, or better, than the other models in each distribution.
医疗支出回归分析被广泛应用于各种经济分析中，包括风险调整、项目和治疗评估。最近的一些文章表明，广义伽马模型（GGM）和扩展的估计方程（EEE）模型为解决支出估计中遇到的各种数据问题提供了灵活的方法。迄今为止，这些模型在支出方面的实证应用很少。我们使用美国医疗支出面板调查的数据，在交叉验证研究设计中，将 GGM 和 EEE 模型与其他常用回归模型进行比较，以评估其偏差、预测准确性和边际效应。医疗支出分布在不同类型的服务和人群中呈现出不同程度的异方差、偏度和峰度。为了检验估计器解决一系列数据问题的能力，我们为两个人群，即老年人和私人保险成年人，估计了总医疗支出和处方药支出模型。我们的研究结果表明，研究人员需要检查他们对链接函数的假设：适当的链接函数因我们的四个分布而异。EEE 模型具有灵活的链接函数，是一种稳健的估计器，在每个分布中，其表现与其他模型一样好，甚至更好。
