Using the NIH Research, Condition and Disease Categorization Database for research advocacy: Schizophrenia research at NIMH as an example

Author:

Torrey E. FullerORCID,Knable Michael B.,Rush A. John,Simmons Wendy W.,Snook John,Jaffe D. J.

Abstract

In 2008 the National Institutes of Health established the Research, Condition and Disease Categorization Database (RCDC) that reports the amount spent by NIH institutes for each disease. Its goal is to allow the public “to know how the NIH spends their tax dollars,” but it has been little used. The RCDC for 2018 was used to assess 428 schizophrenia-related research projects funded by the National Institute of Mental Health. Three senior psychiatrists independently rated each on its likelihood (“likely”, “possible”, “very unlikely”) of improving the symptoms and/or quality of life for individuals with schizophrenia within 20 years. At least one reviewer rated 386 (90%), and all three reviewers rated 302 (71%), of the research projects as very unlikely to provide clinical improvement within 20 years. Reviewer agreement for the “very unlikely” category was good; for the “possible” category was intermediate; and for the “likely” category was poor. At least one reviewer rated 30 (7%) of the research projects as likely to provide clinical improvement within 20 years. The cost of the 30 projects was 5.5% of the total NIMH schizophrenia-related portfolio or 0.6% of the total NIMH budget. Study results confirm previous 2016 criticisms that the NIMH schizophrenia-related research portfolio disproportionately underfunds clinical research that might help people currently affected. Although the results are preliminary, since the RCDC database has not previously been used in this manner and because of the subjective nature of the assessment, the database would appear to be a useful tool for disease advocates who wish to ascertain how NIH spends its public funds.

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference18 articles.

1. Public Law 109–482, Section 402, Electronic Coding of Grants and Activities. https://www.congress.gov/109/plaws/publ482/PLAW-109publ482.pdf.

2. https://report.nih.gov/rcdc/faqs.aspx.

3. A best-fit model for concept vectors in biomedical research grants;C Johnson;AMIA Annu Symp Proc,2008

4. New evidence on the allocation of NIH funds across diseases;BN Sampat;Milbank Quart,2013

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