title: A two-part model for censored medical cost data.
abstract: The two-part model is often used to analyse medical cost data which contain a large proportion of zero cost and are highly skewed with some large costs. The total medical costs over a period of time are often censored due to incomplete follow-up, making the analysis difficult as the censoring can be informative. We propose to apply the inverse probability weighting method on a two-part model to analyse right-censored cumulative medical costs with informative censoring. We also introduce a set of simple functionals based on the intermediate cost history to be applied with the efficiency augmentation technique. In addition, we propose a practical model-checking technique based on the cumulative residuals. Simulation studies are conducted to evaluate the finite sample performance of the proposed method. We use a data set on the cardiovascular disease (CVD)-related Medicare costs to illustrate our proposed method.
authors.affiliation: Northwestern University, Chicago, IL 60611, U.S.A.
authors.forename: Lu
authors.initials: L
authors.lastname: Tian
authors.forename: Jie
authors.initials: J
authors.lastname: Huang
mesh_terms: D003362:Cost-Benefit Analysis / Q000706:statistics & numerical data; D003627:Data Interpretation, Statistical; D017048:Health Care Costs / Q000706:statistics & numerical data*; D015233:Models, Statistical