Measuring costs: administrative claims data, clinical trials, and beyond.
BACKGROUND
Accurate estimation of medical care costs raises a host of issues, both practical and methodological.


OBJECTIVE
This article reviews methods for estimating the long-term medical care costs associated with a cancer diagnosis.


METHODS
The authors consider data from administrative claims databases and describe the analytic challenges posed by these increasingly common resources. They present a number of statistical methods that are valid under censoring and describe methods for estimating mean costs and controlling for covariates. In addition, the authors compare two different approaches for estimating the cancer-related costs; namely, the portion of the long-term costs that may be attributed to the disease. Examples from economic studies of breast and colorectal cancer are presented.


RESULTS
In an analysis of data on colorectal cancer costs from the SEER-Medicare database, the two methods used to estimate expected long-term costs (one model based, one not model-based) yielded similar results. However, in calculating expected cancer-related costs, a method that included future medical costs among controls yielded quite different results from the method that did not include these future costs.


CONCLUSIONS
Statistical methods for analyzing long-term medical costs under censoring are available and appropriate in many applications where total or disease-related costs are of interest. Several of these approaches are nonparametric and therefore may be expected to be robust against the non-standard features that are often encountered when analyzing medical cost data.
Etzioni
Ruth
R
Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
Riley
Gerald F
GF
Ramsey
Scott D
SD
Brown
Martin
M
D002986:Clinical Trials as Topic / Q000191:economics*; D015179:Colorectal Neoplasms / Q000191:economics / Q000628:therapy; D017281:Cost of Illness; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D006278:Medicare; D009369:Neoplasms / Q000191:economics* / Q000628:therapy; D017063:Outcome Assessment, Health Care / Q000191:economics* / Q000379:methods; D019057:Quality-Adjusted Life Years; D018426:SEER Program; D016019:Survival Analysis; D014481:United States