Attributing Medical Spending to Conditions: A Comparison of Methods

86 Pages Posted: 13 Nov 2018

See all articles by David M. Cutler

David M. Cutler

Harvard University - Department of Economics; National Bureau of Economic Research (NBER); Harvard University - Harvard Kennedy School (HKS)

Kaushik Ghosh

National Bureau of Economic Research (NBER)

Irina Bondarenko

University of Michigan at Ann Arbor

Kassandra Messer

University of Michigan at Ann Arbor

Trivellore Raghunathan

University of Michigan at Ann Arbor - Survey Research Center, Survey Methodology Program; University of Michigan at Ann Arbor - School of Public Health, Department of Biostatistics

Susan T. Stewart

Harvard University

Allison Rosen

University of Massachusetts Worcester - Medical School

Date Written: November 2018

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

Cutler, David M. and Ghosh, Kaushik and Bondarenko, Irina and Messer, Kassandra and Raghunathan, Trivellore and Stewart, Susan T. and Rosen, Allison, Attributing Medical Spending to Conditions: A Comparison of Methods (November 2018). NBER Working Paper No. w25233. Available at SSRN: https://ssrn.com/abstract=3282897

David M. Cutler (Contact Author)

Harvard University - Department of Economics ( email )

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National Bureau of Economic Research (NBER) ( email )

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Harvard University - Harvard Kennedy School (HKS) ( email )

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Kaushik Ghosh

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Irina Bondarenko

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Kassandra Messer

University of Michigan at Ann Arbor ( email )

500 S. State Street
Ann Arbor, MI 48109
United States

Trivellore Raghunathan

University of Michigan at Ann Arbor - Survey Research Center, Survey Methodology Program ( email )

426 Thompson Street
Institute for Social Research
Ann Arbor, MI 48106-1248
United States
(734) 647-4619 (Phone)

University of Michigan at Ann Arbor - School of Public Health, Department of Biostatistics ( email )

1415 Washington Heights
Ann Arbor, MI 48109-2029
United States

Susan T. Stewart

Harvard University ( email )

Cambridge, MA 02138
United States

Allison Rosen

University of Massachusetts Worcester - Medical School ( email )

55 Lake Avenue North
Worcester, MA 01655
United States

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