IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this article or follow this journal

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

  • Partha Deb

    (Department of Economics, Indiana University-Purdue University Indianapolis, Indianapolis, USA)

  • Ann M. Holmes

    (School of Public and Environmental Affairs, Indiana University-Purdue University Indianapolis, Indianapolis, USA)

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 © 2000 John Wiley & Sons, Ltd.

To our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.

Article provided by John Wiley & Sons, Ltd. in its journal Health Economics.

Volume (Year): 9 (2000)
Issue (Month): 6 ()
Pages: 475-489

as
in new window

Handle: RePEc:wly:hlthec:v:9:y:2000:i:6:p:475-489
Contact details of provider: Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/5749

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

as in new window
  1. Morduch, Jonathan J. & Stern, Hal S., 1997. "Using mixture models to detect sex bias in health outcomes in Bangladesh," Journal of Econometrics, Elsevier, vol. 77(1), pages 259-276, March.
  2. Blough, David K. & Madden, Carolyn W. & Hornbrook, Mark C., 1999. "Modeling risk using generalized linear models," Journal of Health Economics, Elsevier, vol. 18(2), pages 153-171, April.
  3. Andrews, Donald W. K., 1988. "Chi-square diagnostic tests for econometric models : Introduction and applications," Journal of Econometrics, Elsevier, vol. 37(1), pages 135-156, January.
  4. Winfried Pohlmeier & Volker Ulrich, 1995. "An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care," Journal of Human Resources, University of Wisconsin Press, vol. 30(2), pages 339-361.
  5. Wang, Peiming & Cockburn, Iain M & Puterman, Martin L, 1998. "Analysis of Patent Data--A Mixed-Poisson-Regression-Model Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 27-41, January.
  6. Wedel, M, et al, 1993. "A Latent Class Poisson Regression Model for Heterogeneous Count Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 397-411, Oct.-Dec..
  7. Shinichi Sakata & Halbert White, 1998. "High Breakdown Point Conditional Dispersion Estimation with Application to S&P 500 Daily Returns Volatility," Econometrica, Econometric Society, vol. 66(3), pages 529-568, May.
  8. Sin, Chor-Yiu & White, Halbert, 1996. "Information criteria for selecting possibly misspecified parametric models," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 207-225.
  9. Haas-Wilson, Deborah & Scheffler, Richard & Cheadle, A, 1989. "Demand for Mental Health Services: An Episode of Treatment Approach," MPRA Paper 19862, University Library of Munich, Germany.
  10. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-26, April.
  11. Gritz, R. Mark, 1993. "The impact of training on the frequency and duration of employment," Journal of Econometrics, Elsevier, vol. 57(1-3), pages 21-51.
  12. Cameron, A Colin & Johansson, Per, 1997. "Count Data Regression Using Series Expansions: With Applications," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 203-23, May-June.
  13. John F. Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
  14. Deb, Partha & Trivedi, Pravin K, 1997. "Demand for Medical Care by the Elderly: A Finite Mixture Approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 12(3), pages 313-36, May-June.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:wly:hlthec:v:9:y:2000:i:6:p:475-489. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing)

or (Christopher F. Baum)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.