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Attributing medical spending to conditions: A comparison of methods
To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes tot...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416958/ https://www.ncbi.nlm.nih.gov/pubmed/32776954 http://dx.doi.org/10.1371/journal.pone.0237082 |
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author | Ghosh, Kaushik Bondarenko, Irina Messer, Kassandra L. Stewart, Susan T. Raghunathan, Trivellore Rosen, Allison B. Cutler, David M. |
author_facet | Ghosh, Kaushik Bondarenko, Irina Messer, Kassandra L. Stewart, Susan T. Raghunathan, Trivellore Rosen, Allison B. Cutler, David M. |
author_sort | Ghosh, Kaushik |
collection | PubMed |
description | To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes total spending for a person over a year to their cumulative set of health conditions. Traditionally, this has been done through regression analysis. This paper has two contributions. First, we develop a new cost attribution method to attribute spending to conditions using a more flexible attribution approach, based on propensity score analysis. Second, we compare the propensity score approach to the claims-based approach and the regression approach in a common set of beneficiaries age 65 and older in 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. |
format | Online Article Text |
id | pubmed-7416958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74169582020-08-19 Attributing medical spending to conditions: A comparison of methods Ghosh, Kaushik Bondarenko, Irina Messer, Kassandra L. Stewart, Susan T. Raghunathan, Trivellore Rosen, Allison B. Cutler, David M. PLoS One Research Article To understand the cost burden of medical care it is essential to partition medical spending into conditions. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition that physicians list as its cause. The second decomposes total spending for a person over a year to their cumulative set of health conditions. Traditionally, this has been done through regression analysis. This paper has two contributions. First, we develop a new cost attribution method to attribute spending to conditions using a more flexible attribution approach, based on propensity score analysis. Second, we compare the propensity score approach to the claims-based approach and the regression approach in a common set of beneficiaries age 65 and older in 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. Public Library of Science 2020-08-10 /pmc/articles/PMC7416958/ /pubmed/32776954 http://dx.doi.org/10.1371/journal.pone.0237082 Text en © 2020 Ghosh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ghosh, Kaushik Bondarenko, Irina Messer, Kassandra L. Stewart, Susan T. Raghunathan, Trivellore Rosen, Allison B. Cutler, David M. Attributing medical spending to conditions: A comparison of methods |
title | Attributing medical spending to conditions: A comparison of methods |
title_full | Attributing medical spending to conditions: A comparison of methods |
title_fullStr | Attributing medical spending to conditions: A comparison of methods |
title_full_unstemmed | Attributing medical spending to conditions: A comparison of methods |
title_short | Attributing medical spending to conditions: A comparison of methods |
title_sort | attributing medical spending to conditions: a comparison of methods |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7416958/ https://www.ncbi.nlm.nih.gov/pubmed/32776954 http://dx.doi.org/10.1371/journal.pone.0237082 |
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