Abstract

The idea that medical treatment costs and outcomes might be connected is not new. Likewise, as long as researchers have been designing clinical trials and public opinion polls, there has been interest in the sample size necessary to obtain a desired level of precision and certainty before collecting the data. However, researchers continue to adapt cost-effectiveness models for scenarios of ever-increasing complexity, and equally adaptable sample size determination schemes are required. Of interest for the current study are those instances wherein a non-trivial proportion of patients incur zero costs associated with their treatment. We propose a sample size determination scheme for a cost-effectiveness model fit to such a scenario. Furthermore, we display our method’s usefulness on multiple parameter configurations derived from applications presented in already published research.

摘要

医疗成本和结果可能相关的想法并不新鲜。同样，只要研究人员一直在设计临床试验和民意调查，就会对在收集数据之前获得所需精度和确定性水平所需的样本量感兴趣。然而，研究人员继续针对不断增加的复杂性场景调整成本效益模型，并且需要同样适应性强的样本量确定方案。当前研究感兴趣的是那些实例，其中相当一部分患者的治疗相关费用为零。我们为适合这种情况的成本效益模型提出了样本量确定方案。此外，