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NIH Disease Funding Levels and Burden of Disease

BACKGROUND: An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; th...

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Autores principales: Gillum, Leslie A., Gouveia, Christopher, Dorsey, E. Ray, Pletcher, Mark, Mathers, Colin D., McCulloch, Charles E., Johnston, S. Claiborne
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3044706/
https://www.ncbi.nlm.nih.gov/pubmed/21383981
http://dx.doi.org/10.1371/journal.pone.0016837
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author Gillum, Leslie A.
Gouveia, Christopher
Dorsey, E. Ray
Pletcher, Mark
Mathers, Colin D.
McCulloch, Charles E.
Johnston, S. Claiborne
author_facet Gillum, Leslie A.
Gouveia, Christopher
Dorsey, E. Ray
Pletcher, Mark
Mathers, Colin D.
McCulloch, Charles E.
Johnston, S. Claiborne
author_sort Gillum, Leslie A.
collection PubMed
description BACKGROUND: An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time. METHODS: We analyzed public data on 2006 NIH funding for 29 common conditions. Measures of US disease burden in 2004 were obtained from the World Health Organization's Global Burden of Disease study and national databases. We assessed the relationship between disease burden and NIH funding dollars in univariate and multivariable log-linear models that evaluated all measures of disease burden. Sensitivity analyses examined associations with future US burden, current and future measures of world disease burden, and a newly standardized NIH accounting method. RESULTS: In univariate and multivariable analyses, disease-specific NIH funding levels increased with burden of disease measured in DALYs (p = 0.001), which accounted for 33% of funding level variation. No other factor predicted funding in multivariable models. Conditions receiving the most funding greater than expected based on disease burden were AIDS ($2474 M), diabetes mellitus ($390 M), and perinatal conditions ($297 M). Depression ($719 M), injuries ($691 M), and chronic obstructive pulmonary disease ($613 M) were the most underfunded. Results were similar using estimates of future US burden, current and future world disease burden, and alternate NIH accounting methods. CONCLUSIONS: Current levels of NIH disease-specific research funding correlate modestly with US disease burden, and correlation has not improved in the last decade.
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spelling pubmed-30447062011-03-07 NIH Disease Funding Levels and Burden of Disease Gillum, Leslie A. Gouveia, Christopher Dorsey, E. Ray Pletcher, Mark Mathers, Colin D. McCulloch, Charles E. Johnston, S. Claiborne PLoS One Research Article BACKGROUND: An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time. METHODS: We analyzed public data on 2006 NIH funding for 29 common conditions. Measures of US disease burden in 2004 were obtained from the World Health Organization's Global Burden of Disease study and national databases. We assessed the relationship between disease burden and NIH funding dollars in univariate and multivariable log-linear models that evaluated all measures of disease burden. Sensitivity analyses examined associations with future US burden, current and future measures of world disease burden, and a newly standardized NIH accounting method. RESULTS: In univariate and multivariable analyses, disease-specific NIH funding levels increased with burden of disease measured in DALYs (p = 0.001), which accounted for 33% of funding level variation. No other factor predicted funding in multivariable models. Conditions receiving the most funding greater than expected based on disease burden were AIDS ($2474 M), diabetes mellitus ($390 M), and perinatal conditions ($297 M). Depression ($719 M), injuries ($691 M), and chronic obstructive pulmonary disease ($613 M) were the most underfunded. Results were similar using estimates of future US burden, current and future world disease burden, and alternate NIH accounting methods. CONCLUSIONS: Current levels of NIH disease-specific research funding correlate modestly with US disease burden, and correlation has not improved in the last decade. Public Library of Science 2011-02-24 /pmc/articles/PMC3044706/ /pubmed/21383981 http://dx.doi.org/10.1371/journal.pone.0016837 Text en Gillum 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
Gillum, Leslie A.
Gouveia, Christopher
Dorsey, E. Ray
Pletcher, Mark
Mathers, Colin D.
McCulloch, Charles E.
Johnston, S. Claiborne
NIH Disease Funding Levels and Burden of Disease
title NIH Disease Funding Levels and Burden of Disease
title_full NIH Disease Funding Levels and Burden of Disease
title_fullStr NIH Disease Funding Levels and Burden of Disease
title_full_unstemmed NIH Disease Funding Levels and Burden of Disease
title_short NIH Disease Funding Levels and Burden of Disease
title_sort nih disease funding levels and burden of disease
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3044706/
https://www.ncbi.nlm.nih.gov/pubmed/21383981
http://dx.doi.org/10.1371/journal.pone.0016837
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