Bang Heejung
Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, 411 East 69th Street, New York, NY 10021, USA.
Contemp Clin Trials. 2005 Oct;26(5):586-97. doi: 10.1016/j.cct.2005.05.004.
Incompleteness is a key feature of most survival data. Numerous well established statistical methodologies and algorithms exist for analyzing life or failure time data. However, induced censorship invalidates the use of those standard analytic tools for some survival-type data such as medical costs. In this paper, some valid methods currently available for analyzing censored medical cost data are reviewed. Some cautionary findings under different assumptions are envisioned through application to medical costs from colorectal cancer patients. Cost analysis should be suitably planned and carefully interpreted under various meaningful scenarios even with judiciously selected statistical methods. This approach would be greatly helpful to policy makers who seek to prioritize health care expenditures and to assess the elements of resource use.
不完整性是大多数生存数据的一个关键特征。存在许多成熟的统计方法和算法用于分析寿命或失效时间数据。然而,诱导审查会使那些标准分析工具不适用于某些生存类型的数据,如医疗费用。本文回顾了目前可用于分析审查后的医疗费用数据的一些有效方法。通过应用于结直肠癌患者的医疗费用,设想了在不同假设下的一些警示性发现。即使采用精心选择的统计方法,成本分析也应在各种有意义的情况下进行适当规划并仔细解释。这种方法将对寻求确定医疗保健支出优先级和评估资源使用要素的政策制定者有很大帮助。