Federal Funding and Citation Metrics of Biomedical Research in the USA release_ribha2qcxreo5dodw65ab6uzvu

by John Ioannidis, Iztok Hozo, Benjamin Djulbegovic

Released as a post by Cold Spring Harbor Laboratory.



Both citation and funding metrics converge in shaping current perceptions of academic success. We aimed to evaluate what proportion of the most-cited USA-based biomedical scientists are funded by biomedical federal agencies and whether funded scientists are more cited than not funded ones. We linked a Scopus-based database on top-cited researchers (n=75,316 USA-based) and the NIH RePORTER database of 33 biomedical federal agencies (n=204,603 grant records) with matching based on name and institution. The 40,887 USA-based top-cited scientists who were allocated to any of 69 scientific subfields highly related to biomedicine were considered in the main analysis. The proportion of USA-based top-cited biomedical scientists (based on career-long citation impact) who had received any federal funding from biomedical research agencies was 63% for any funding (1996-2022), 21% for recent funding (2015-2022), and 14% for current funding (2021-2022). Respective proportions were 65%, 31%, and 21%, when top-cited scientists based on recent single year impact were considered. There was large variability across scientific subfields. No subfield had more than 31% of its top-cited USA-based scientists (career-long impact) currently funded. Funded top-cited researchers were overall more cited than non-funded top-cited scientists, e.g. mean (median) 14,420 (8983) versus 8,445 (4613) (p<0.001) and a substantial difference remained (, after adjusting for subfield and years since first publication. Differences were more prominent in some specific biomedical subfields. Overall, biomedical federal funding has offered support to approximately two-thirds of the top-cited biomedical scientists at some point during the last quarter century, but only a small minority of top-cited scientists have current federal biomedical funding. The large unevenness across subfields needs to be addressed with ways that improve equity, efficiency, excellence, and translational potential.
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