Issues for the Next Generation of Health Care Cost Analyses

被引:96
作者
Basu, Anirban [1 ,2 ]
Manning, Willard G. [3 ]
机构
[1] Univ Chicago, Dept Med, Ctr Hlth & Social Sci, Chicago, IL 60637 USA
[2] Natl Bur Econ Res, Cambridge, MA 02138 USA
[3] Univ Chicago, Dept Hlth Studies, Harris Sch Publ Policy Studies, Chicago, IL 60637 USA
基金
美国医疗保健研究与质量局;
关键词
health care costs; skewness; transformation; generalized linear models; censored costs; INSTRUMENTAL VARIABLES; ALTERNATIVE MODELS; MEDICAL COSTS; REGRESSION; RETRANSFORMATION; ESTIMATORS; DIAGNOSES; DEMAND; TESTS; ADO;
D O I
10.1097/MLR.0b013e31819c94a1
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
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.
引用
收藏
页码:S109 / S114
页数:6
相关论文
共 58 条
[1]  
Angrist JD, 1996, J AM STAT ASSOC, V91, P444, DOI 10.2307/2291629
[2]  
[Anonymous], NATL BUREAU EC RES W
[3]  
Ash AS, 2000, HEALTH CARE FINANC R, V21, P7
[4]   Estimating medical costs with censored data [J].
Bang, H ;
Tsiatis, AA .
BIOMETRIKA, 2000, 87 (02) :329-343
[5]  
Baser O., 2007, Applied Economics Research, V1, P1
[6]   Estimating marginal and incremental effects on health outcomes using flexible link and variance function models [J].
Basu, A ;
Rathouz, PJ .
BIOSTATISTICS, 2005, 6 (01) :93-109
[7]   Comparing alternative models: log vs Cox proportional hazard? [J].
Basu, A ;
Manning, WG ;
Mullahy, J .
HEALTH ECONOMICS, 2004, 13 (08) :749-765
[8]   Use of instrumental variables in the presence of heterogeneity and self-selection: An application to treatments of breast cancer patients [J].
Basu, Anirban ;
Heckman, James J. ;
Navarro-Lozano, Salvador ;
Urzua, Sergio .
HEALTH ECONOMICS, 2007, 16 (11) :1133-1157
[9]   Scale of interest versus scale of estimation: Comparing alternative estimators for the incremental costs of a comorbidity [J].
Basu, Anirban ;
Arondekar, Bhakti V. ;
Rathouz, Paul J. .
HEALTH ECONOMICS, 2006, 15 (10) :1091-1107
[10]   Estimating probit models with self-selected treatments [J].
Bhattacharya, J ;
Goldman, D ;
McCaffrey, D .
STATISTICS IN MEDICINE, 2006, 25 (03) :389-413