期刊
MEDICAL CARE
卷 47, 期 7, 页码 S109-S114出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/MLR.0b013e31819c94a1
关键词
health care costs; skewness; transformation; generalized linear models; censored costs
类别
资金
- National Cancer Institute
- Agency for Healthcare Research and Quality
- Harris School of Public Policy Studies
- Department of Medicine
Background: Given the characteristics of health care expenditure/cost data-a mass of observations at zero, and skewed positive expenditures, various alternative estimators have been developed that can address the analytical issues these characteristics raise. The field continues to develop new approaches and to evaluate the performance of the existing ones. Objectives: We discuss the strengths and limitations in existing methods for estimation and for model specification and checking. We suggest some areas that need fuller development or a better understanding of how the estimation approach performs when the outcome exhibits the skewness and heavy right tails that are typical of health care data. We also address various other aspects of cost analysis that include dealing with induced censoring, estimating casual effects, and generating reliable predictions that may apply to many studies. Results: No current method is optimal or dominant for all cost applications. Many of the diagnostics used in choosing among alternatives have limitations that need more careful Study. Several avenues in modeling cost data remain unexplored. Conclusions: Taken together, we hope that this essay would serve as a guide to the choice among methods and to the next generation of methodological research in this field.
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