Analysis of the health economics portfolio funded by the National Institutes of Health in response to published guidance
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ABSTRACT:
SUBMITTER: Burgdorf C
PROVIDER: S-EPMC10866517 | biostudies-literature | 2024 Jan
REPOSITORIES: biostudies-literature
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Project description:PurposeTo measure diversity within the National Institutes of Health (NIH)-funded workforce. The authors use a relevant labor market perspective to more directly understand what the NIH can influence in terms of enhancing diversity through NIH policies.MethodUsing the relevant labor market (defined as persons with advanced degrees working as biomedical scientists in the United States) as the conceptual framework, and informed by accepted economic principles, the authors used the American Community Survey and NIH administrative data to calculate representation ratios of the NIH-funded biomedical workforce from 2008 to 2012 by race, ethnicity, sex, and citizenship status, and compared this against the pool of characteristic individuals in the potential labor market.ResultsIn general, the U.S. population during this time period was an inaccurate comparison group for measuring diversity of the NIH-funded scientific workforce. Measuring accurately, we found the representation of women and traditionally underrepresented groups in NIH-supported postdoc fellowships and traineeships and mentored career development programs was greater than their representation in the relevant labor market. The same analysis found these demographic groups are less represented in the NIH-funded independent investigator pool.ConclusionsAlthough these findings provided a picture of the current NIH-funded workforce and a foundation for understanding the federal role in developing, maintaining, and renewing diverse scientific human resources, further study is needed to identify whether junior- and early-stage investigators who are part of more diverse cohorts will naturally transition into independent NIH-funded investigators, or whether they will leave the workforce before achieving independent researcher status.
| S-EPMC5502106 | 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: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
Project description:ObjectivesObtaining National Institutes of Health funding for heart transplant research is becoming increasingly difficult, especially for surgeons. We sought to determine the impact of National Institutes of Health-funded cardiac transplantation research over the past 30 years.MethodsNational Institutes of Health Research Portfolio Online Reporting Tools Expenditures and Results was queried for R01s using 10 heart transplant-related terms. Principal Investigator, total grant funding amount, number of publications, and citations of manuscripts were collected. A citation-based Grant Impact Metric was assigned to each grant: sum of citations for each manuscript normalized by the funding of the respective grant (per $100K). The department and background degree(s) (MD, PhD, MD/PhD) for each funded Principal Investigator were identified from institutional faculty profiles.ResultsA total of 321 cardiac transplantation R01s totaling $723 million and resulting in 6513 publications were analyzed. Surgery departments received more grants and more funding dollars to study cardiac transplantation than any other department (n = 115, $249 million; Medicine: n = 93, $208 million; Pathology: 26, $55 million). Surgeons performed equally well compared with all other Principal Investigators with respect to Grant Impact Metric (15.1 vs 20.6; P = .19) and publications per $1 million (7.5 vs 6.8; P = .75). Finally, all physician-scientists (MDs) have a significantly higher Grant Impact Metric compared with nonclinician researchers (non-MDs) (22.3 vs 16.3; P = .028).ConclusionsSurgeon-scientists are equally productive and impactful compared with nonsurgeons despite decreasing funding rates at the National Institutes of Health and greater pressure from administrators to increase clinical productivity.
| S-EPMC7782209 | biostudies-literature
Project description: Not available
| S-EPMC10370255 | biostudies-literature
Project description:The clinical trials community has a never-ending search for dependable and reliable ways to improve clinical research. This exploration has led to considerable interest in adaptive clinical trial designs, which provide the flexibility to adjust trial characteristics on the basis of data reviewed at interim stages. Statisticians and clinical investigators have proposed or implemented a wide variety of adaptations in clinical trials, but specific approaches have met with differing levels of support. Within industry, investigators are actively exploring the benefits and pitfalls associated with adaptive designs (ADs). For example, a Drug Information Association (DIA) working group on ADs has engaged regulatory agencies in discussions. Many researchers working on publicly funded clinical trials, however, are not yet fully engaged in this discussion. We organized the Scientific Advances in Adaptive Clinical Trial Designs Workshop to begin a conversation about using ADs in publicly funded research. Held in November of 2009, the 1½-day workshop brought together representatives from the National Institutes of Health (NIH), the Food and Drug Administration (FDA), the European Medicines Agency (EMA), the pharmaceutical industry, nonprofit foundations, the patient advocacy community, and academia. The workshop offered a forum for participants to address issues of ADs that arise at the planning, designing, and execution stages of clinical trials, and to hear the perspectives of influential members of the clinical trials community. The participants also set forth recommendations for guiding action to promote the appropriate use of ADs. These recommendations have since been presented, discussed, and vetted in a number of venues including the University of Pennsylvania Conference on Statistical Issues in Clinical Trials and the Society for Clinical Trials annual meeting.To provide a brief overview of ADs, describe the rationale behind conducting the workshop, and summarize the main recommendations that were produced as a result of this workshop.There is a growing interest in the use of adaptive clinical trial designs. However, a number of logistical barriers need to be addressed in order to obtain the potential advantages of an AD. Currently, the pharmaceutical industry is well ahead of academic trialists with respect to addressing these barriers. Academic trialists will need to address important issues such as education, infrastructure, modifications to existing funding models, and the impact on Data and Safety Monitoring Boards (DSMB) in order to achieve the possible benefits of adaptive clinical trial designs.
| S-EPMC5570450 | biostudies-other
Project description:Policy has a tremendous potential to improve population health when informed by research evidence. Such evidence, however, typically plays a suboptimal role in policymaking processes. The field of policy dissemination and implementation research (policy D&I) exists to address this challenge. The purpose of this study was to: (1) determine the extent to which policy D&I was funded by the National Institutes of Health (NIH), (2) identify trends in NIH-funded policy D&I, and (3) describe characteristics of NIH-funded policy D&I projects.The NIH Research Portfolio Online Reporting Tool was used to identify all projects funded through D&I-focused funding announcements. We screened for policy D&I projects by searching project title, abstract, and term fields for mentions of "policy," "policies," "law," "legal," "legislation," "ordinance," "statute," "regulation," "regulatory," "code," or "rule." A project was classified as policy D&I if it explicitly proposed to conduct research about the content of a policy, the process through which it was developed, or outcomes it produced. A coding guide was iteratively developed, and all projects were independently coded by two researchers. ClinicalTrials.gov and PubMed were used to obtain additional project information and validate coding decisions. Descriptive statistics--stratified by funding mechanism, Institute, and project characteristics--were produced.Between 2007 and 2014, 146 projects were funded through the D&I funding announcements, 12 (8.2 %) of which were policy D&I. Policy D&I funding totaled $16,177,250, equivalent to 10.5 % of all funding through the D&I funding announcements. The proportion of funding for policy D&I projects ranged from 14.6 % in 2007 to 8.0 % in 2012. Policy D&I projects were primarily focused on policy outcomes (66.7 %), implementation (41.7 %), state-level policies (41.7 %), and policies within the USA (83.3 %). Tobacco (33.3 %) and cancer (25.0 %) control were the primary topics of focus. Many projects combined survey (58.3 %) and interview (33.3 %) methods with analysis of archival data sources.NIH has made an initial investment in policy D&I research, but the level of support has varied between Institutes. Policy D&I researchers have utilized a variety of designs, methods, and data sources to investigate the development processes, content, and outcomes of public and private policies.
| S-EPMC4700744 | biostudies-other
Project description:BackgroundTelehealth use increased during the COVID-19 pandemic and remains a complementary source of cancer care delivery. Understanding research funding trends in cancer-related telehealth can highlight developments in this area of science and identify future opportunities.MethodsApplications funded by the US National Cancer Institute (NCI) between fiscal years 2016 and 2022 and focused on synchronous patient-provider telehealth were analyzed for grant characteristics (eg, funding mechanism), cancer focus (eg, cancer type), and study features (eg, type of telehealth service). Of 106 grants identified initially, 60 were retained for coding after applying exclusion criteria.ResultsAlmost three-quarters (73%) of telehealth grants were funded during fiscal years 2020-2022. Approximately 67% were funded through R01 or R37 mechanism and implemented as randomized controlled trials (63%). Overall, telehealth grants commonly focused on treatment (30%) and survivorship (43%); breast cancer (12%), hematologic malignancies (10%), and multiple cancer sites (27%); and health disparity populations (ie, minorities, rural residents) (73%). Both audio and video telehealth were common (65%), as well as accompanying mHealth apps (20%). Telehealth services centered on psychosocial care, self-management, and supportive care (88%); interventions were commonly delivered by mental health professionals (30%).ConclusionNCI has observed an increase in funded synchronous patient-provider telehealth grants. Trends indicate an evolution of awards that have expanded across the cancer control continuum, applied rigorous study designs, incorporated additional digital technologies, and focused on populations recognized for disparate cancer outcomes. As telehealth is integrated into routine cancer care delivery, additional research evidence will be needed to inform clinical practice.
| S-EPMC11207831 | biostudies-literature
Project description: Not available
| S-EPMC9945062 | biostudies-literature
Project description:ImportanceInvestigators applying for National Institutes of Health (NIH) funding increasingly use promotional language (or hype) that has the potential to undermine objective evaluation. Whether or not the same investigators use hype in subsequent research reports has yet to be investigated.ObjectiveTo assess changes in the use of hype in journal abstracts reporting research funded by the NIH and to compare those trends with previously reported trends in the associated NIH funding applications.Design, setting, and participantsThis cross-sectional study assessed trends (from 1985 to 2020) in the use of promotional adjectives in abstracts of journal articles reporting NIH-funded research, and then compared those trends with previously reported trends for the associated NIH funding applications. Articles included in analyses had abstracts available in PubMed.Main outcomes and measuresAbsolute change for the 139 adjective forms that have previously been identified as representing hype in NIH funding applications was measured as the difference in frequency between 1985 and 2020. Relative change was measured as the percentage change in frequency in 2020 relative to 1985, or the first year of occurrence. Consistency of change was measured by the rank order correlation (Kendall τ). Concordance between longitudinal trends in the journal abstracts and NIH funding applications was measured by the rank-order cross-correlation.ResultsIn a total of 2 394 480 journal abstracts, all 139 adjective forms were identified in 2 793 592 total occurrences. Among these adjectives, 133 increased in absolute frequency by 5335 words per million (wpm), with a mean (SD) relative increase of 1404% (2371%). The largest absolute increases were for novel (524 wpm), important (414 wpm), and key (378 wpm). The largest relative increases were for scalable (22 wpm [19 964%]), unmet (23 wpm [12 126%]), and tailored (40 wpm [8169%]). The mean (SD) correlation for all adjectives was 0.70 (0.30) with 95 adjectives showing a strong positive correlation (τ > 0.7; P < .001), 24 a moderate positive correlation (0.5 < τ < 0.7; P < .001), and 3 a moderate negative correlation (-0.5 < τ < -0.7; P < .001). The mean (SD) cross-correlation was 0.64 (0.19) with 61 of the 139 adjectives showing a strong positive cross-correlations (τ > 0.7; P < .001), 53 a moderate positive cross-correlations (0.5 < τ < 0.7; P < .001), and 3 a moderate negative cross-correlation (-0.7 < τ < -0.5; P < .001).Conclusions and relevanceIn this analysis of journal abstracts reporting NIH-funded research from 1985 to 2020, levels of promotional language were found to be increasing and trends were closely associated with previously reported trends in the related NIH funding applications. This suggests that increasing levels of salesmanship may in part be a downstream effect of salesmanship infused during earlier stages of the research cascade.
| S-EPMC10739072 | biostudies-literature