IDEAS home Printed from https://ideas.repec.org/a/wly/hlthec/v9y2000i6p475-489.html
   My bibliography  Save this article

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

Author

Listed:
  • Partha Deb
  • Ann M. Holmes

Abstract

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.

Suggested Citation

  • Partha Deb & Ann M. Holmes, 2000. "Estimates of use and costs of behavioural health care: a comparison of standard and finite mixture models," Health Economics, John Wiley & Sons, Ltd., vol. 9(6), pages 475-489, September.
    • Handle: RePEc:wly:hlthec:v:9:y:2000:i:6:p:475-489
    DOI: 10.1002/1099-1050(200009)9:6<475::AID-HEC544>3.0.CO;2-H
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/1099-1050(200009)9:63.0.CO;2-H
    Download Restriction: no
    File URL: https://libkey.io/10.1002/1099-1050(200009)9:6<475::AID-HEC544>3.0.CO;2-H?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    5. John Geweke & Michael P. Keane, 1997. "Mixture of normals probit models," Staff Report 237, Federal Reserve Bank of Minneapolis.
    6. 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 313-336, May-June.
    7. 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.
    8. 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.
    9. 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.
    10. 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..
    11. 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 115-126, April.
    12. 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.
    13. 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.
    14. 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 203-223, May-June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Deb, Partha & Trivedi, Pravin K., 2002. "The structure of demand for health care: latent class versus two-part models," Journal of Health Economics, Elsevier, vol. 21(4), pages 601-625, July.
    2. Vincenzo Atella & Francesco Brindisi & Partha Deb & Furio C. Rosati, 2004. "Determinants of access to physician services in Italy: a latent class seemingly unrelated probit approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(7), pages 657-668, July.
    3. Conway, Karen Smith & Deb, Partha, 2005. "Is prenatal care really ineffective? Or, is the 'devil' in the distribution?," Journal of Health Economics, Elsevier, vol. 24(3), pages 489-513, May.
    4. Deb, Partha & TRIVEDI, PRAVIN K, 1998. "Moment-based Estimation of Latent Class Models of Event Counts," University of California at San Diego, Economics Working Paper Series qt6r282286, Department of Economics, UC San Diego.
    5. Óscar Lourenço & Carlota Quintal & Pedro Lopes Ferreira & Pedro Pita Barros, 2007. "A equidade na utilização de cuidados de saúde em Portugal: Uma avaliação baseada em modelos de contagem," Notas Económicas, Faculty of Economics, University of Coimbra, issue 25, pages 6-26, June.
    6. Brutscher, P., 2012. "Self-Disconnection Among Pre-Payment Customers - A Behavioural Analysis," Cambridge Working Papers in Economics 1214, Faculty of Economics, University of Cambridge.
    7. Deb, Partha & Gallo, William T. & Ayyagari, Padmaja & Fletcher, Jason M. & Sindelar, Jody L., 2011. "The effect of job loss on overweight and drinking," Journal of Health Economics, Elsevier, vol. 30(2), pages 317-327, March.
    8. Jones, A. & Lomas, J. & Rice, N., 2014. "Going Beyond the Mean in Healthcare Cost Regressions: a Comparison of Methods for Estimating the Full Conditional Distribution," Health, Econometrics and Data Group (HEDG) Working Papers 14/26, HEDG, c/o Department of Economics, University of York.
    9. Padmaja Ayyagari & Partha Deb & Jason Fletcher & William Gallo & Jody L. Sindelar, 2013. "Understanding Heterogeneity In Price Elasticities In The Demand For Alcohol For Older Individuals," Health Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 89-105, January.
    10. Partha Deb & William T. Gallo & Padmaja Ayyagari & Jason M. Fletcher & Jody L. Sindelar, 2009. "Job Loss: Eat, drink and try to be merry?," NBER Working Papers 15122, National Bureau of Economic Research, Inc.
    11. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.
    12. Andrés Romeu & Marcos Vera-Hernández, 2005. "Counts with an endogenous binary regressor: A series expansion approach," Econometrics Journal, Royal Economic Society, vol. 8(1), pages 1-22, March.
    13. Michael Creel & Montserrat Farell, 2005. "Modeling Usage of Medical Care Services: The Medical Expenditure Panel Survey Data, 1996-2000," UFAE and IAE Working Papers 646.05, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    14. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.
    15. Teresa Bago d'Uva, 2005. "Latent class models for use of primary care: evidence from a British panel," Health Economics, John Wiley & Sons, Ltd., vol. 14(9), pages 873-892, September.
    16. Harris, Matthew & Kohn, Jennifer, 2015. "Reference dependent utility from health and the demand for medical care," MPRA Paper 61926, University Library of Munich, Germany.
    17. Padmaja Ayyagari & Partha Deb & Jason Fletcher & William T. Gallo & Jody L. Sindelar, 2009. "Sin Taxes: Do Heterogeneous Responses Undercut Their Value?," NBER Working Papers 15124, National Bureau of Economic Research, Inc.
    18. João Cotter Salvado, 2008. "The Determinants of Health Care Utilization in Portugal: An Approach with Count Data Models," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 144(III), pages 437-458, September.
    19. Padma Sharma, 2022. "Assessing Regulatory Responses to Banking Crises," Research Working Paper RWP 22-04, Federal Reserve Bank of Kansas City.
    20. Besstremyannaya, Galina, 2017. "Measuring income equity in the demand for healthcare with finite mixture models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 5-29.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. 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.

    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 CitEc recognized a bibliographic reference but did not link an item in RePEc 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 RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www3.interscience.wiley.com/cgi-bin/jhome/5749 .

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.