Medical cost analysis: application to colorectal cancer data from the SEER Medicare database.
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.
Bang
Heejung
H
Division of Biostatistics and Epidemiology, Department of Public Health, Weill Medical College of Cornell University, 411 East 69th Street, New York, NY 10021, USA. heb2013@med.cornell.edu
D000368:Aged; D015179:Colorectal Neoplasms / Q000191:economics*; D003365:Costs and Cost Analysis; D019992:Databases as Topic; D005260:Female; D006801:Humans; D008297:Male; D006278:Medicare / Q000191:economics; D012044:Regression Analysis; D018426:SEER Program; D016019:Survival Analysis