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Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatments, due to skyrocketing health care costs and limited resource available. Censored costs data poses a unique problem for cost estimation due to "induced informative censoring" problem. Thus, many standard approaches for survival analysis are not valid for the analysis of cost data. We first derive the confidence interval for the incremental cost-effectiveness ratio for a special case, when terminating events are different for survival time and costs. Then we study how to intuitively explain some existing estimators for costs, based on the generalized redistribute-to-the-right algorithm. Motivated by that idea, we also propose two improved survival estimators of costs, based on generalized redistribute-to-the-right algorithm and kernel method. We first consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on the counting process theory and the general theory for missing data process. The simulation studies and real data example show that our method performs very well for some practical settings. In addition, we provide intuitive explanation to a mean cost estimator and a survival estimator for costs, based on generalized redistribute-to-the-right algorithm. Since those estimators are derived based on the inverse probability weighting principle and semiparametric efficiency theory, it is not always easy to understand how these methods work. Therefore, our work engenders a better understanding of those theoretically derived cost estimators. Motivated by the idea of generalized redistribute-to-the-right algorithm, we propose an estimator for the survival function of costs. The proposed estimator is naturally monotone, more efficient than some existing survival estimators, and has a quite small bias in many realistic settings. We further propose a kernel-based survival estimator for costs. The latter estimator, which is asymptotically unbiased, overcomes the deficiency of the former estimator, while preserving the nice properties. Our proposed estimators outperform existing estimators under various scenarios in simulation and real data example. The electronic version of this dissertation is accessible from http://hdl.handle.net/1969.1/155096
Cost-effectiveness analysis is widely conducted in the economic evaluation of new treatment options. In many clinical and observational studies of costs, data are often censored. Censoring brings challenges to both medical cost estimation and cost-effectiveness analysis. Although methods have been proposed for estimating the mean costs with censored data, they are often derived from theory and it is not always easy to understand how these methods work. We provide an alternative method for estimating the mean cost more efficiently based on a replace-from-the-right algorithm, and show that this estimator is equivalent to an existing estimator based on the inverse probability weighting principle and semiparametric efficiency theory. Therefore, we provide an intuitive explanation to a theoretically derived mean cost estimator. In many applications, it is also important to estimate the survival function of costs. We propose a generalized redistribute-to-the right algorithm for estimating the survival function of costs with censored data, and show that it is equivalent to a simple weighted survival estimator of costs based on inverse probability weighting techniques. Motivated by this redistribute-to-the-right principle, we also develop a more efficient survival estimator for costs, which has the desirable property of being monotone, and more efficient, although not always consistent. We conduct simulation to compare our method with some existing survival estimators for costs, and find the bias seems quite small. Thus, it may be considered as a candidate for survival estimator for costs in a real setting when the censoring is heavy and cost history information is available. Finally, we consider one special situation in conducting cost-effectiveness analysis, when the terminating events for survival time and costs are different. Traditional methods for statistical inference cannot deal with such data. We propose a new method for deriving the confidence interval for the incremental cost-effectiveness ratio under this situation, based on counting process and the general theory for missing data process. The simulation studies show that our method performs very well for some practical settings. Our proposed method has a great potential of being applied to a real setting when different terminating events exist for survival time and costs.
The extent to which consumers respond to marginal prices for medical care is important for policy. Using recent data and a new censored quantile instrumental variable (CQIV) estimator, I estimate the price elasticity of expenditure on medical care. The CQIV estimator allows the estimates to vary across the skewed expenditure distribution, it allows for censoring at zero expenditure nonparametrically, and it allows for the insurance-induced endogenous relationship between price and expenditure. For identification, I rely on cost sharing provisions that generate marginal price differences between individuals who have injured family members and individuals who do not. I estimate the price elasticity of expenditure on medical care to be stable at -2.3 across the .65 to .95 conditional quantiles of the expenditure distribution. These quantile estimates are an order of magnitude larger than previous mean estimates. I consider several explanations for why price responsiveness is larger than previous estimates would suggest.
The extent to which consumers respond to marginal prices for medical care is important for policy. Using recent data and a new censored quantile instrumental variable (CQIV) estimator, I estimate the price elasticity of expenditure on medical care. The CQIV estimator allows the estimates to vary across the skewed expenditure distribution, it allows for censoring at zero expenditure nonparametrically, and it allows for the insurance-induced endogenous relationship between price and expenditure. For identification, I rely on cost sharing provisions that generate marginal price differences between individuals who have injured family members and individuals who do not. I estimate the price elasticity of expenditure on medical care to be stable at -2.3 across the .65 to .95 conditional quantiles of the expenditure distribution. These quantile estimates are an order of magnitude larger than previous mean estimates. I consider several explanations for why price responsiveness is larger than previous estimates would suggest.
Understanding Health Outcomes and Pharmacoeconomics presents an overview of the tools used to assess patient-related health status including associated health outcomes and the analyses that are used to determine cost-effectiveness in evaluating pharmacotherapeutic interventions to improve health. Including data and examples from several different countries, this comprehensive text will help students understand the basis for decisions made at the local and governmental level that impact the use of pharmaceuticals and provide a strong foundation for understanding the principles used in cost-effective decision making. With commentaries, cases studies, and highlighting international differences, this text concludes with a discussion of the need for a universal system for documenting medication use. Understanding Health Outcomes and Pharmacoeconomics provides definitions of comparative effectiveness research (CER) and comparisons of pharmacoeconomic models (including cost-effectivess, cost-benefit, and cost utility analyses). This inclusive text provides describes how CER is linked to various pharmacoeconomic models by providing examples from clinical trials with comparative pharmacotherapy and cost parameters. From the Introduction: "The need for interprofessional education was made apparent in the 2003 Health Professions Education: A Bridge to Quality report. All healthcare professionals must be educated to deliver patient-centered care as members of an interprofessional team, emphasizing evidence-based practice, quality improvement approaches, and informatics. An enhanced understanding of pharmacoeconomic principles is a step in the right direction for healthcare practitioners as we do our best to ensure optimal medication therapy outcomes for patients and society at-large." -- George E. MacKinnon III, PhD, RPh, FASHP