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Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method

Author

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  • Betty Tao
  • Massimo Pietropaolo
  • Mark Atkinson
  • Desmond Schatz
  • David Taylor

Abstract

Background: Diabetes costs represent a large burden to both patients and the health care system. However, few studies that examine the economic consequences of diabetes have distinguished between the two major forms, type 1 and type 2 diabetes, despite differences in underlying pathologies. Combining the two diseases implies that there is no difference between the costs of type 1 and type 2 diabetes to a patient. In this study, we examine the costs of type 1 diabetes, which is often overlooked due to the larger population of type 2 patients, and compare them to the estimated costs of diabetes reported in the literature. Methodology/Principal Findings: Using a nationally representative dataset, we estimate yearly and lifetime medical and indirect costs of type 1 diabetes by implementing a matching method to compare a patient with type 1 diabetes to a similar individual without the disease. We find that each year type 1 diabetes costs this country $14.4 billion (11.5–17.3) in medical costs and lost income. In terms of lost income, type 1 patients incur a disproportionate share of type 1 and type 2 costs. Further, if the disease were eliminated by therapeutic intervention, an estimated $10.6 billion (7.2–14.0) incurred by a new cohort and $422.9 billion (327.2–519.4) incurred by the existing number of type 1 diabetic patients over their lifetime would be avoided. Conclusions/Significance: We find that the costs attributed to type 1 diabetes are disproportionately higher than the number of type 1 patients compared with type 2 patients, suggesting that combining the two diseases when estimating costs is not appropriate. This study and another recent contribution provides a necessary first step in estimating the substantial costs of type 1 diabetes on the U.S.

Suggested Citation

  • Betty Tao & Massimo Pietropaolo & Mark Atkinson & Desmond Schatz & David Taylor, 2010. "Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method," PLOS ONE, Public Library of Science, vol. 5(7), pages 1-11, July.
    • Handle: RePEc:plo:pone00:0011501
    DOI: 10.1371/journal.pone.0011501
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    References listed on IDEAS

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    1. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    2. Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453.
    3. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    4. Leu, Robert E. & Schaub, Thomas, 1983. "Does smoking increase medical care expenditure?," Social Science & Medicine, Elsevier, vol. 17(23), pages 1907-1914, January.
    5. Kahn, Matthew E, 1998. "Health and Labor Market Performance: The Case of Diabetes," Journal of Labor Economics, University of Chicago Press, vol. 16(4), pages 878-899, October.
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    1. Tingting Liu & Hong Feng & Elizabeth Brandon, 2018. "Would you like to leave Beijing, Shanghai, or Shenzhen? An empirical analysis of migration effect in China," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-20, August.
    2. Charmaine Shuyu Ng & Matthias Paul Han Sim Toh & Yu Ko & Joyce Yu-Chia Lee, 2015. "Direct Medical Cost of Type 2 Diabetes in Singapore," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-11, March.
    3. François-Olivier Baudot & Anne-Sophie Aguadé & Thomas Barnay & Christelle Gastaldi-Ménager & Anne Fagot-Campagna, 2019. "Impact of type 2 diabetes on health expenditure: estimation based on individual administrative data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(5), pages 657-668, July.
    4. Eriksen, Tine Louise Mundbjerg & Gaulke, Amanda & Svensson, Jannet & Skipper, Niels & Thingholm, Peter Rønø, 2023. "Childhood Health Shocks and the Intergenerational Transmission of Inequality," IZA Discussion Papers 16447, Institute of Labor Economics (IZA).
    5. Sanjib Saha & Ulf Gerdtham, 2013. "Cost of illness studies on reproductive, maternal, newborn, and child health: a systematic literature review," Health Economics Review, Springer, vol. 3(1), pages 1-12, December.

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