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Does managed care affect the diffusion of psychotropic medications?

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  • Marisa E. Domino

Abstract

Newer technologies to treat many mental illnesses have shown substantial heterogeneity in diffusion rates across states. In this paper, I investigate whether variation in the level of managed care penetration is associated with changes in state‐level diffusion of three newer classes of psychotropic medications in fee‐for‐service Medicaid programs from 1991 to 2005. Three different types of managed care programs are examined: capitated managed care, any type of managed care and behavioral health carve‐outs. A fourth‐order polynomial fixed effect regression model is used to model the diffusion path of newer antidepressant and antipsychotic medications controlling for time‐varying state characteristics. Substantial differences are found in the diffusion paths by the degree of managed care use in each state Medicaid program. The largest effect is seen through spillover effects of capitated managed care programs; states with greater capitated managed care have greater initial shares of newer psychotropic medications. The influence of carve‐outs and of all types of managed care combined on the diffusion path was modest. Copyright © 2011 John Wiley & Sons, Ltd.

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  • Marisa E. Domino, 2012. "Does managed care affect the diffusion of psychotropic medications?," Health Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 428-443, April.
  • Handle: RePEc:wly:hlthec:v:21:y:2012:i:4:p:428-443
    DOI: 10.1002/hec.1723
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    1. Pradeep Chintagunta & Renna Jiang & Ginger Jin, 2009. "Information, learning, and drug diffusion: The case of Cox-2 inhibitors," Quantitative Marketing and Economics (QME), Springer, vol. 7(4), pages 399-443, December.
    2. Sara Ellison Fisher & Iain Cockburn & Zvi Griliches & Jerry Hausman, 1997. "Characteristics of Demand for Pharmaceutical Products: An Examination of Four Cephalosporins," RAND Journal of Economics, The RAND Corporation, vol. 28(3), pages 426-446, Autumn.
    3. Stern, S. & Trajtenberg, M., 1998. "Empirical Implications of Physician Authority in Pharmaceutical Decisionmaking," Papers 24-98, Tel Aviv.
    4. Diego Comin & Bart Hobijn & Emilie Rovito, 2006. "Five Facts You Need to Know About Technology Diffusion," NBER Working Papers 11928, National Bureau of Economic Research, Inc.
    5. Phelps, Charles E., 2000. "Information diffusion and best practice adoption," Handbook of Health Economics, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 5, pages 223-264, Elsevier.
    6. Peay, Marilyn Y. & Peay, Edmund R., 1994. "Innovation in high risk drug therapy," Social Science & Medicine, Elsevier, vol. 39(1), pages 39-52, July.
    7. Birgitte Andersen, 1999. "The hunt for S-shaped growth paths in technological innovation: a patent study," Journal of Evolutionary Economics, Springer, vol. 9(4), pages 487-526.
    8. Judith K. Hellerstein, 1998. "The Importance of the Physician in the Generic Versus Trade-Name Prescription Decision," RAND Journal of Economics, The RAND Corporation, vol. 29(1), pages 108-136, Spring.
    9. Dana Goldman & James P. Smith, 2005. "Socioeconomic Differences in the Adoption of New Medical Technologies," American Economic Review, American Economic Association, vol. 95(2), pages 234-237, May.
    10. Jonathan Skinner & Douglas Staiger, 2015. "Technology Diffusion and Productivity Growth in Health Care," The Review of Economics and Statistics, MIT Press, vol. 97(5), pages 951-964, December.
    11. Mas, Núria & Seinfeld, Janice, 2008. "Is managed care restraining the adoption of technology by hospitals?," Journal of Health Economics, Elsevier, vol. 27(4), pages 1026-1045, July.
    12. Jonathan Skinner & Douglas Staiger, 2007. "Technology Adoption from Hybrid Corn to Beta-Blockers," NBER Chapters, in: Hard-to-Measure Goods and Services: Essays in Honor of Zvi Griliches, pages 545-570, National Bureau of Economic Research, Inc.
    13. Marisa Elena Domino & David S. Salkever, 2003. "Price elasticity and pharmaceutical selection: the influence of managed care," Health Economics, John Wiley & Sons, Ltd., vol. 12(7), pages 565-586, July.
    14. Diego Comin & Bart Hobijn & Emilie Rovito, 2008. "A new approach to measuring technology with an application to the shape of the diffusion curves," The Journal of Technology Transfer, Springer, vol. 33(2), pages 187-207, April.
    15. Berndt Ernst R. & Cockburn Iain M. & Cocks Douglas L. & Epstein Arnold M. & Griliches Zvi, 1998. "Is Price Inflation Different for the Elderly? An Empirical Analysis of Prescription Drugs," Forum for Health Economics & Policy, De Gruyter, vol. 1(1), pages 1-45, January.
    16. Davina C. Ling & Ernst R. Berndt & Richard G. Frank, 2008. "Economic Incentives And Contracts: The Use Of Psychotropic Medications," Contemporary Economic Policy, Western Economic Association International, vol. 26(1), pages 49-72, January.
    17. Meyerhoefer Chad D. & Zuvekas Samuel H, 2008. "The Shape of Demand: What Does It Tell Us about Direct-to-Consumer Marketing of Antidepressants?," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(2), pages 1-34, January.
    18. Minhi Hahn & Sehoon Park & Lakshman Krishnamurthi & Andris A. Zoltners, 1994. "Analysis of New Product Diffusion Using a Four-Segment Trial-Repeat Model," Marketing Science, INFORMS, vol. 13(3), pages 224-247.
    19. Coscelli, Andrea & Shum, Matthew, 2004. "An empirical model of learning and patient spillovers in new drug entry," Journal of Econometrics, Elsevier, vol. 122(2), pages 213-246, October.
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    2. Schmitz, Hendrik & Stroka, Magdalena A., 2013. "Health and the double burden of full-time work and informal care provision — Evidence from administrative data," Labour Economics, Elsevier, vol. 24(C), pages 305-322.
    3. Giuliano Masiero & Fabrizio Mazzonna & Olaf Verbeek, 2018. "What drives the rise of antidepressant consumption? Evidence from Switzerland," IdEP Economic Papers 1801, USI Università della Svizzera italiana.
    4. Katolik, Aleksandra & Oswald, Andrew J., 2017. "Antidepressants for Economists and Business-School Researchers: An Introduction and Review," CAGE Online Working Paper Series 338, Competitive Advantage in the Global Economy (CAGE).

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