Estimates of use and costs of behavioural health care: A comparison of standard and finite mixture models

被引:1
|
作者
Deb, P
Holmes, AM
机构
[1] Indiana Univ Purdue Univ, Dept Econ, Indianapolis, IN 46202 USA
[2] Indiana Univ Purdue Univ, Sch Publ & Environm Affairs, Indianapolis, IN 46202 USA
关键词
finite mixture models; behavioural health; costs; utilization; rate-setting;
D O I
10.1002/1099-1050(200009)9:6<475::AID-HEC544>3.0.CO;2-H
中图分类号
F [经济];
学科分类号
02 ;
摘要
Estimates of health care demand are known to depend on the empirical specification used in the analysis. In this paper, an innovative specification, the finite mixture model (FMM), is employed to estimate the utilization of and expenditures on behavioural health care. Unlike standard specifications, the FMM has the ability to distinguish between distinct classes of users of behavioural health care (e.g. the 'worried well' and the severely mentally ill). This new model is tested against standard empirical specifications using data from the National Medical Expenditure Survey. Using common risk stratifiers, estimates of utilization and costs are generated with each specification. It is found that the FMM provides a much better fit of both expenditure and utilization data than standard specifications, particularly among high intensity users that standard models have been unable to represent adequately. Furthermore, the results provide preliminary evidence that there are (at least) two distinct groups of users of behavioural health care. The empirical advantages of the FMM translate into superior estimates of mean costs and utilization that have widespread application in rate-setting exercises. Copyright (C) 2000 John Wiley & Sons, Ltd.
引用
收藏
页码:475 / 489
页数:15
相关论文
共 50 条
  • [1] STATISTICAL MODELS TO PREDICT HEALTH CARE COSTS: A COMPARISON
    Narduzzi, S.
    Cascini, S.
    Arca, M.
    Belleudi, V
    Colais, P.
    Fusco, D.
    EPIDEMIOLOGIA & PREVENZIONE, 2010, 34 (5-6): : 155 - 155
  • [2] ANALYSIS OF HEALTH CARE COSTS IN ELDERLY PATIENTS WITH MULTIPLE CHRONIC CONDITIONS USING A FINITE MIXTURE OF GENERALIZED LINEAR MODELS
    Eckardt, M.
    Brettschneider, C.
    van den Bussche, H.
    Koenig, H. H.
    VALUE IN HEALTH, 2013, 16 (07) : A581 - A581
  • [3] Analysis of Health Care Costs in Elderly Patients with Multiple Chronic Conditions Using a Finite Mixture of Generalized Linear Models
    Eckardt, Matthias
    Brettschneider, Christian
    van den Bussche, Hendrik
    Koenig, Hans-Helmut
    HEALTH ECONOMICS, 2017, 26 (05) : 582 - 599
  • [4] Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults
    Kan, Hong J.
    Kharrazi, Hadi
    Chang, Hsien-Yen
    Bodycombe, Dave
    Lemke, Klaus
    Weiner, Jonathan P.
    PLOS ONE, 2019, 14 (03):
  • [5] Restricted Maximum Likelihood Estimates in Finite Mixture Models
    陈家骅
    成平
    东北数学, 1995, (03) : 365 - 370+071+372-374
  • [6] Penalized minimum-distance estimates in finite mixture models
    Chen, JH
    Kalbfleisch, JD
    CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE, 1996, 24 (02): : 167 - 175
  • [7] Comparison of Health Care Use and Costs in Newly Diagnosed and Established Patients With Fibromyalgia
    White, Leigh Ann
    Robinson, Rebecca L.
    Yu, Andrew P.
    Kaltenboeck, Anna
    Samuels, Seth
    Mallett, David
    Birnbaum, Howard G.
    JOURNAL OF PAIN, 2009, 10 (09): : 976 - 983
  • [8] A comparison of cardiologist and noncardiologist use of echocardiograms: Implications for containing health care costs
    Vaghari, Benjamin A.
    Goldman, Martin E.
    MOUNT SINAI JOURNAL OF MEDICINE, 2006, 73 (05): : 802 - 805
  • [9] STANDARD COSTS FOR HEALTH ECONOMIC EVALUATIONS: AN INTERNATIONAL COMPARISON
    Mostardt, S.
    Sandmann, F. G.
    Seidl, A.
    Zhou, M.
    Gerber-Grote, A. U.
    VALUE IN HEALTH, 2014, 17 (07) : A427 - A427
  • [10] The use of finite mixture models to estimate the distribution of the health utilities index in the presence of a ceiling effect
    Austin, PC
    Escobar, MD
    JOURNAL OF APPLIED STATISTICS, 2003, 30 (08) : 909 - 923