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Time is money: Outpatient waiting times and health insurance choices of elderly veterans in the United States

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  • Pizer, Steven D.
  • Prentice, Julia C.
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    Abstract

    Growth in the number of days between an appointment request and the actual appointment reduces demand. Although such waiting times are relatively low in the US, current policy initiatives could cause them to increase. We estimate multiple-equation models of physician utilization and insurance plan choice for Medicare-eligible veterans. We find that a 10% increase in VA waiting times increases demand for Medigap insurance by 5%, implying that a representative patient would be indifferent between waiting an average of 5 more days for VA appointments and paying $300 more in annual premium.

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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Health Economics.

    Volume (Year): 30 (2011)
    Issue (Month): 4 (July)
    Pages: 626-636

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    Handle: RePEc:eee:jhecon:v:30:y:2011:i:4:p:626-636

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    Web page: http://www.elsevier.com/locate/inca/505560

    Related research

    Keywords: Outpatient waiting times Insurance choice Medicare;

    References

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    1. Goddard, Maria & Smith, Peter, 2001. "Equity of access to health care services: : Theory and evidence from the UK," Social Science & Medicine, Elsevier, Elsevier, vol. 53(9), pages 1149-1162, November.
    2. Town, Robert & Liu, Su, 2003. " The Welfare Impact of Medicare HMOs," RAND Journal of Economics, The RAND Corporation, vol. 34(4), pages 719-36, Winter.
    3. Nevo, Aviv, 1999. "Measuring Market Power in the Ready-to-Eat Cereal Industry," Competition Policy Center, Working Paper Series, Competition Policy Center, Institute for Business and Economic Research, UC Berkeley qt7cm5p858, Competition Policy Center, Institute for Business and Economic Research, UC Berkeley.
    4. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
    5. Tim Besley & John Hall & Ian Preston, 1996. "The demand for private health insurance: do waiting lists matter?," IFS Working Papers, Institute for Fiscal Studies W96/07, Institute for Fiscal Studies.
    6. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, Econometric Society, vol. 62(2), pages 467-75, March.
    7. Cullis, John G. & Jones, Philip R. & Propper, Carol, 2000. "Waiting lists and medical treatment: Analysis and policies," Handbook of Health Economics, Elsevier, in: A. J. Culyer & J. P. Newhouse (ed.), Handbook of Health Economics, edition 1, volume 1, chapter 23, pages 1201-1249 Elsevier.
    8. Lindsay, Cotton M & Feigenbaum, Bernard, 1984. "Rationing by Waiting Lists," American Economic Review, American Economic Association, American Economic Association, vol. 74(3), pages 404-17, June.
    9. Steven D. Pizer & Austin B. Frakt & Roger Feldman, 2008. "Predicting risk selection following major changes in medicare," Health Economics, John Wiley & Sons, Ltd., vol. 17(4), pages 453-468.
    10. Steven Pizer & Austin Frakt & Roger Feldman, 2009. "Nothing for something? Estimating cost and value for beneficiaries from recent medicare spending increases on HMO payments and drug benefits," International Journal of Health Care Finance and Economics, Springer, Springer, vol. 9(1), pages 59-81, March.
    11. Propper, Carol, 2000. "The demand for private health care in the UK," Journal of Health Economics, Elsevier, Elsevier, vol. 19(6), pages 855-876, November.
    12. Terza, Joseph V. & Basu, Anirban & Rathouz, Paul J., 2008. "Two-stage residual inclusion estimation: Addressing endogeneity in health econometric modeling," Journal of Health Economics, Elsevier, Elsevier, vol. 27(3), pages 531-543, May.
    13. Gravelle, Hugh & Siciliani, Luigi, 2008. "Optimal quality, waits and charges in health insurance," Journal of Health Economics, Elsevier, Elsevier, vol. 27(3), pages 663-674, May.
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    Cited by:
    1. Gregori Baetschmann & Rainer Winkelmann, 2012. "Modelling zero-inflated count data when exposure varies: with an application to sick leave," ECON - Working Papers, Department of Economics - University of Zurich 061, Department of Economics - University of Zurich.
    2. Neil J. Buckley & Katherine Cuff & Jeremiah Hurley & Logan McLeod & Stuart Mestelman & David Cameron, 2012. "An Experimental Investigation of Mixed Systems of Public and Private Health Care Finance," Department of Economics Working Papers 2012-02, McMaster University.
    3. Markus Jochmann, 2013. "What belongs where? Variable selection for zero-inflated count models with an application to the demand for health care," Computational Statistics, Springer, Springer, vol. 28(5), pages 1947-1964, October.
    4. Gregori Baetschmann & Rainer Winkelmann, 2014. "A dynamic hurdle model for zero-inflated count data: with an application to health care utilization," ECON - Working Papers, Department of Economics - University of Zurich 151, Department of Economics - University of Zurich.
    5. Gregori Baetschmann & Rainer Winkelmann, 2014. "A Dynamic Hurdle Model for Zero-Inflated Count Data: With an Application to Health Care Utilization," SOEPpapers on Multidisciplinary Panel Data Research 648, DIW Berlin, The German Socio-Economic Panel (SOEP).

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