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Attributing Medical Spending to Conditions: A Comparison of Methods

Author

Listed:
  • David Cutler
  • Kaushik Ghosh
  • Irina Bondarenko
  • Kassandra Messer
  • Trivellore Raghunathan
  • Susan Stewart
  • Allison B. Rosen

Abstract

Partitioning medical spending into conditions is essential to understanding the cost burden of medical care. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition listed as its cause. The second decomposes total spending for a person over a year to the cumulative set of conditions they have. Traditionally, this has been done through regression analysis. This paper makes two contributions. First, we develop a new method to attribute spending to conditions using propensity score models. Second, we compare the claims attribution approach to the regression approach and our propensity score stratification method in a common set of beneficiaries age 65 and over drawn from the 2009 Medicare Current Beneficiary Survey. Our estimates show that the three methods have important differences in spending allocation and that the propensity score model likely offers the best theoretical and empirical combination.

Suggested Citation

  • David Cutler & Kaushik Ghosh & Irina Bondarenko & Kassandra Messer & Trivellore Raghunathan & Susan Stewart & Allison B. Rosen, 2018. "Attributing Medical Spending to Conditions: A Comparison of Methods," NBER Working Papers 25233, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:25233
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    1. F. Kreuter & K. Olson & J. Wagner & T. Yan & T. M. Ezzati‐Rice & C. Casas‐Cordero & M. Lemay & A. Peytchev & R. M. Groves & T. E. Raghunathan, 2010. "Using proxy measures and other correlates of survey outcomes to adjust for non‐response: examples from multiple surveys," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(2), pages 389-407, April.
    2. Allison B. Rosen & Kaushik Ghosh & Emily S. Pape & Marcelo Coca Perraillon & Irina Bondarenko & Kassandra L. Messer & Trivellore Raghunathan & Susan T. Stewart & David M. Cutler, 2017. "Strengthening National Data to Better Measure What We Are Buying in Health Care: Reconciling National Health Expenditures with Detailed Survey Data," NBER Working Papers 23290, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Kaushik Ghosh & Irina Bondarenko & Kassandra L Messer & Susan T Stewart & Trivellore Raghunathan & Allison B Rosen & David M Cutler, 2020. "Attributing medical spending to conditions: A comparison of methods," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-17, August.

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    JEL classification:

    • I1 - Health, Education, and Welfare - - Health

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