Statistical analysis of the National Institutes of Health peer review system.
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ABSTRACT:
SUBMITTER: Johnson VE
PROVIDER: S-EPMC2488382 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The National Institutes of Health (NIH) is the largest source of funding for biomedical research in the world. This funding is largely effected through a competitive grants process. Each year the Center for Scientific Review (CSR) at NIH manages the evaluation, by peer review, of more than 55,000 grant applications. A relevant management question is how this scientific evaluation system, supported by finite resources, could be continuously evaluated and improved for maximal benefit to the scientific community and the taxpaying public. Towards this purpose, we have created the first system-level description of peer review at CSR by applying text analysis, bibliometric, and graph visualization techniques to administrative records. We identify otherwise latent relationships across scientific clusters, which in turn suggest opportunities for structural reorganization of the system based on expert evaluation. Such studies support the creation of monitoring tools and provide transparency and knowledge to stakeholders.
| S-EPMC4132088 | biostudies-literature
Project description:A previous report found an association of topic choice with race-based funding disparities among R01 applications submitted to the National Institutes of Health ('NIH') between 2011 and 2015. Applications submitted by African American or Black ('AAB') Principal Investigators ('PIs') skewed toward a small number of topics that were less likely to be funded (or 'awarded'). It was suggested that lower award rates may be related to topic-related biases of peer reviewers. However, the report did not account for differential funding ecologies among NIH Institutes and Centers ('ICs'). In a re-analysis, we find that 10% of 148 topics account for 50% of applications submitted by AAB PIs. These applications on 'AAB Preferred' topics were funded at lower rates, but peer review outcomes were similar. The lower rate of funding for these topics was primarily due to their assignment to ICs with lower award rates, not to peer-reviewer preferences.
| S-EPMC8087446 | biostudies-literature
Project description:ObjectiveTo determine trends in National Institutes of Health (NIH) funding for cardiac surgeons, hypothesizing they are at a disadvantage in obtaining funding owing to intensive clinical demands.MethodsCardiac surgeons (adult/congenital) currently at the top 141 NIH-funded institutions were identified using institutional websites. The NIH funding history for each cardiac surgeon was queried using the NIH Research Portfolio Online Reporting Tools Expenditures and Results (RePORTER). Total grant funding, publications, and type was collected. Academic rank, secondary degrees, and fellowship information was collected from faculty pages. Grant productivity was calculated using a validated grant impact metric.ResultsA total of 818 academic cardiac surgeons were identified, of whom 144 obtained 293 NIH grants totaling $458 million and resulting in 6694 publications. We identified strong associations between an institution's overall NIH funding rank and the number of cardiac surgeons, NIH grants to cardiac surgeons, and amount of NIH funding to cardiac surgeons (P < .0001 for all). The majority of NIH funding to cardiac surgeons is concentrated in the top quartile of institutions. Cardiac surgeons had a high conversion rates from K awards (mentored development awards) to R01s (6 of 14; 42.9%). Finally, we demonstrate that the rate of all NIH grants awarded to cardiac surgeons has increased, driven primarily by P and U (collaborative project) grants.ConclusionsNIH-funded cardiac surgical research has had a significant impact over the last 3 decades. Aspiring cardiac surgeon-scientists may be more successful at top quartile institutions owing to better infrastructure and mentorship.
| S-EPMC7546359 | biostudies-literature
Project description:Understanding the factors associated with successful funding outcomes of research project grant (R01) applications is critical for the biomedical research community. R01 applications are evaluated through the National Institutes of Health (NIH) peer review system, where peer reviewers are asked to evaluate and assign scores to five research criteria when assessing an application's scientific and technical merit. This study examined the relationship of the five research criterion scores to the Overall Impact score and the likelihood of being funded for over 123,700 competing R01 applications for fiscal years 2010 through 2013. The relationships of other application and applicant characteristics, including demographics, to scoring and funding outcomes were studied as well. The analyses showed that the Approach and, to a lesser extent, the Significance criterion scores were the main predictors of an R01 application's Overall Impact score and its likelihood of being funded. Applicants might consider these findings when submitting future R01 applications to NIH.
| S-EPMC4889138 | biostudies-literature
Project description:BackgroundEvaluating the National Institute's Health's (NIH's) response to the coronavirus disease 2019 (COVID-19) pandemic via grants and clinical trials is crucial to determining the impact they had on aiding US citizens. We determined how the NIH's funding for COVID-19 research was disbursed and used by various institutions across the United States.MethodsWe queried NIH RePORTER and isolated COVID-19-related grants from January 2020 to December 2021. We analyzed grant type, geographical location, and awardee institution. Manuscripts published from these grants were quantitatively analyzed. COVID-19 clinical trials were mapped and distances from counties to clinical trial sites were calculated using ArcGis.ResultsA total of 2401 COVID-19 NIH grants resulted in 14 654 manuscripts from $4.2 billion and generated more than 150 000 citations. R01s make up 32% of grants (763/2401) and 8% of funding ($329 million). UM1 grants account for the majority of funding (30.8%; $1.3 Billion). Five states received 50.6% of funding: North Carolina, Washington, New York, California, and Massachusetts. Finally, of the 1806 clinical trials across 1266 sites in the United States, the majority were in metropolitan areas in close proximity to areas of high COVID-19 disease burden.Conclusions and relevanceEvaluating the outcome of the NIH's response to the COVID-19 pandemic is of interest to the general public. The present study finds that the NIH disbursed more than $4 billion in funding to large consortiums and clinical trials to develop diagnostics, therapeutics, and vaccines. Approximately 8% of funding was used for R01 grants. Clinical trial sites were generally located in areas of high COVID-19 burden.
| S-EPMC10965119 | biostudies-literature
Project description:One in 5 Americans experiences disability that affects daily function because of impairments in mobility, impairments in cognitive function, sensory impairment, or communication impairment. The need for rehabilitation strategies to optimize function and reduce disability is a clear priority for research to address this public health challenge. The National Institutes of Health (NIH) recently published a Research Plan on Rehabilitation that provides a set of priorities to guide the field over the next 5 years. The plan was developed with input from multiple institutes and centers within the NIH, the National Advisory Board for Medical Rehabilitation Research, and the public. This article provides an overview of the need for this research plan, an outline of its development, and a listing of six priority areas for research.
| S-EPMC5397097 | biostudies-literature
Project description:To help explain the diversity of COVID-19 outcomes by country, research teams worldwide are studying national government response efforts. However, these attempts have not focused on a critical national authority that exists in half of the countries in the world: national public health institutes (NPHIs). NPHIs serve as an institutional home for public health systems and expertise and play a leading role in epidemic responses. To characterize the role of NPHIs in the COVID-19 response, we conducted a descriptive literature review that explored the research documented during March 2020-May 2021. We conducted a name-based search of 61 NPHIs in the literature, representing over half of the world's NPHIs. We identified 33 peer-reviewed and 300 gray articles for inclusion. We describe the most common NPHI-led COVID-19 activities that are documented and identify gaps in the literature. Our findings underscore the value of NPHIs for epidemic control and establish a foundation for primary research.
| S-EPMC9745230 | biostudies-literature
Project description:BackgroundAccording to a wide variety of analyses and projections, the potential effects of global climate change on human health are large and diverse. The U.S. National Institutes of Health (NIH), through its basic, clinical, and population research portfolio of grants, has been increasing efforts to understand how the complex interrelationships among humans, ecosystems, climate, climate variability, and climate change affect domestic and global health.ObjectivesIn this commentary we present a systematic review and categorization of the fiscal year (FY) 2008 NIH climate and health research portfolio.MethodsA list of candidate climate and health projects funded from FY 2008 budget appropriations were identified and characterized based on their relevance to climate change and health and based on climate pathway, health impact, study type, and objective.ResultsThis analysis identified seven FY 2008 projects focused on climate change, 85 climate-related projects, and 706 projects that focused on disease areas associated with climate change but did not study those associations. Of the nearly 53,000 awards that NIH made in 2008, approximately 0.17% focused on or were related to climate.ConclusionsGiven the nature and scale of the potential effects of climate change on human health and the degree of uncertainty that we have about these effects, we think that it is helpful for the NIH to engage in open discussions with science and policy communities about government-wide needs and opportunities in climate and health, and about how NIH's strengths in human health research can contribute to understanding the health implications of global climate change. This internal review has been used to inform more recent initiatives by the NIH in climate and health.
| S-EPMC3620768 | biostudies-literature
Project description:National Institutes of Health Clinical Center Klebsiella Outbreak 2011 Study
| PRJNA188534 | ENA
Project description:ImportanceDespite the rapid growth of interest and diversity in applications of artificial intelligence (AI) to biomedical research, there are limited objective ways to characterize the potential for use of AI in clinical practice.ObjectiveTo examine what types of medical AI have the greatest estimated translational impact (ie, ability to lead to development that has measurable value for human health) potential.Design, setting, and participantsIn this cohort study, research grants related to AI awarded between January 1, 1985, and December 31, 2020, were identified from a National Institutes of Health (NIH) award database. The text content for each award was entered into a Natural Language Processing (NLP) clustering algorithm. An NIH database was also used to extract citation data, including the number of citations and approximate potential to translate (APT) score for published articles associated with the granted awards to create proxies for translatability.ExposuresUnsupervised assignment of AI-related research awards to application topics using NLP.Main outcomes and measuresAnnualized citations per $1 million funding (ACOF) and average APT score for award-associated articles, grouped by application topic. The APT score is a machine-learning based metric created by the NIH Office of Portfolio Analysis that quantifies the likelihood of future citation by a clinical article.ResultsA total of 16 629 NIH awards related to AI were included in the analysis, and 75 applications of AI were identified. Total annual funding for AI grew from $17.4 million in 1985 to $1.43 billion in 2020. By average APT, interpersonal communication technologies (0.488; 95% CI, 0.472-0.504) and population genetics (0.463; 95% CI, 0.453-0.472) had the highest translatability; environmental health (ACOF, 1038) and applications focused on the electronic health record (ACOF, 489) also had high translatability. The category of applications related to biochemical analysis was found to have low translatability by both metrics (average APT, 0.393; 95% CI, 0.388-0.398; ACOF, 246).Conclusions and relevanceBased on this study's findings, data on grants from the NIH can apparently be used to identify and characterize medical applications of AI to understand changes in academic productivity, funding support, and potential for translational impact. This method may be extended to characterize other research domains.
| S-EPMC8787619 | biostudies-literature