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Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method
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. Combinin...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901386/ https://www.ncbi.nlm.nih.gov/pubmed/20634976 http://dx.doi.org/10.1371/journal.pone.0011501 |
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author | Tao, Betty Pietropaolo, Massimo Atkinson, Mark Schatz, Desmond Taylor, David |
author_facet | Tao, Betty Pietropaolo, Massimo Atkinson, Mark Schatz, Desmond Taylor, David |
author_sort | Tao, Betty |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2901386 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-29013862010-07-15 Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method Tao, Betty Pietropaolo, Massimo Atkinson, Mark Schatz, Desmond Taylor, David PLoS One Research Article 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. Public Library of Science 2010-07-09 /pmc/articles/PMC2901386/ /pubmed/20634976 http://dx.doi.org/10.1371/journal.pone.0011501 Text en Tao 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Tao, Betty Pietropaolo, Massimo Atkinson, Mark Schatz, Desmond Taylor, David Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title | Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title_full | Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title_fullStr | Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title_full_unstemmed | Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title_short | Estimating the Cost of Type 1 Diabetes in the U.S.: A Propensity Score Matching Method |
title_sort | estimating the cost of type 1 diabetes in the u.s.: a propensity score matching method |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2901386/ https://www.ncbi.nlm.nih.gov/pubmed/20634976 http://dx.doi.org/10.1371/journal.pone.0011501 |
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