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Machines that Go ‘Ping’: Medical Technology and Health Expenditures in OECD Countries

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  • Peter Willemé
  • Michel Dumont

Abstract

Technology is believed to be a major determinant of increasing health spending. The main difficulty to quantify its effect is to find suitable proxies to measure medical technological innovation. This paper's main contribution is the use of data on approved medical devices and drugs to proxy for medical technology. The effects of these variables on total real per capita health spending are estimated using a panel model for 18 Organisation for Economic Co‐operation and Development (OECD) countries covering the period 1981–2012. The results confirm the substantial cost‐increasing effect of medical technology, which accounts for almost 50% of the explained historical growth of spending. Despite the overall net positive effect of technology, the effect of two subgroups of approvals on expenditure is significantly negative. These subgroups can be thought of as representing ‘incremental medical innovation’, whereas the positive effects are related to radically innovative pharmaceutical products and devices. A separate time series model was estimated for the USA because the FDA approval data in fact only apply to the USA, while they serve as proxies for the other OECD countries. Our empirical model includes an indicator of obesity, and estimations confirm the substantial contribution of this lifestyle variable to health spending growth in the countries studied. Copyright © 2014 John Wiley & Sons, Ltd.

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  • Peter Willemé & Michel Dumont, 2015. "Machines that Go ‘Ping’: Medical Technology and Health Expenditures in OECD Countries," Health Economics, John Wiley & Sons, Ltd., vol. 24(8), pages 1027-1041, August.
  • Handle: RePEc:wly:hlthec:v:24:y:2015:i:8:p:1027-1041
    DOI: 10.1002/hec.3089
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    Cited by:

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    2. Karine Lamiraud & Stéphane Lhuillery, 2015. "Endogenous Technology Adoption and Medical Costs," Working Papers hal-01218064, HAL.
    3. Son Hong Nghiem & Luke Brian Connelly, 2017. "Convergence and determinants of health expenditures in OECD countries," Health Economics Review, Springer, vol. 7(1), pages 1-11, December.
    4. Mauro Laudicella & Paolo Li Donni & Kim Rose Olsen & Dorte Gyrd‐Hansen, 2022. "Age, morbidity, or something else? A residual approach using microdata to measure the impact of technological progress on health care expenditure," Health Economics, John Wiley & Sons, Ltd., vol. 31(6), pages 1184-1201, June.
    5. Karmann Alexander & Rösel Felix & Schneider Markus, 2016. "Produktivitätsmotor Gesundheitswirtschaft: Finanziert sich der medizinisch-technische Fortschritt selbst?," Perspektiven der Wirtschaftspolitik, De Gruyter, vol. 17(1), pages 54-67, April.
    6. Kris Ivanovski & Sefa Awaworyi Churchill, 2021. "Has healthcare expenditure converged across Australian states and territories?," Empirical Economics, Springer, vol. 61(6), pages 3401-3417, December.
    7. Elisabet Rodriguez Llorian & Janelle Mann, 2022. "Exploring the technology–healthcare expenditure nexus: a panel error correction approach," Empirical Economics, Springer, vol. 62(6), pages 3061-3086, June.
    8. Okunade, Albert A. & Osmani, Ahmad Reshad, 2018. "Technology, Productivity, and Costs in Healthcare," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 1-21.
    9. Aleksandra Torbica & Helen Banks & Cinzia Valzania & Giuseppe Boriani & Giovanni Fattore, 2017. "Investigating Regional Variation of Cardiac Implantable Electrical Device Implant Rates in European Healthcare Systems: What Drives Differences?," Health Economics, John Wiley & Sons, Ltd., vol. 26(S1), pages 30-45, February.
    10. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.

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