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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.

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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  • Pizer, Steven D. & Prentice, Julia C., 2011. "Time is money: Outpatient waiting times and health insurance choices of elderly veterans in the United States," Journal of Health Economics, Elsevier, vol. 30(4), pages 626-636, July.
    • Handle: RePEc:eee:jhecon:v:30:y:2011:i:4:p:626-636
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    Cited by:

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    2. Buckley, Neil J. & Cuff, Katherine & Hurley, Jeremiah & McLeod, Logan & Mestelman, Stuart & Cameron, David, 2012. "An experimental investigation of mixed systems of public and private health care finance," Journal of Economic Behavior & Organization, Elsevier, vol. 84(3), pages 713-729.
    3. 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).
    4. Gregori Baetschmann & Rainer Winkelmann, 2012. "Modelling zero-inflated count data when exposure varies: with an application to sick leave," ECON - Working Papers 061, Department of Economics - University of Zurich.
    5. Christine A. Yee & Kyle Barr & Taeko Minegishi & Austin Frakt & Steven D. Pizer, 2022. "Provider supply and access to primary care," Health Economics, John Wiley & Sons, Ltd., vol. 31(7), pages 1296-1316, July.
    6. 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, vol. 28(5), pages 1947-1964, October.
    7. Christine A. Yee & Aaron Legler & Michael Davies & Julia Prentice & Steven Pizer, 2020. "Priority access to health care: Evidence from an exogenous policy shock," Health Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 306-323, March.
    8. Van Ommeren, Jos N. & Van der Vlist, Arno J., 2016. "Households' willingness to pay for public housing," Journal of Urban Economics, Elsevier, vol. 92(C), pages 91-105.
    9. Strobel, Stephenson, 2024. "Who responds to longer wait times? The effects of predicted emergency wait times on the health and volume of patients who present for care," Journal of Health Economics, Elsevier, vol. 96(C).
    10. Kevin E. Staub & Rainer Winkelmann, 2013. "Consistent Estimation Of Zero‐Inflated Count Models," Health Economics, John Wiley & Sons, Ltd., vol. 22(6), pages 673-686, June.

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