How Many Researchers, Revisited: A Look at Cumulative Investigator Funding Rates

In May 2016, we posted a blog on “How Many Researchers” NIH supports. We cited the findings of a University of Wisconsin workshop, which concluded that the biomedical research enterprise suffers from two core problems: too many scientists vying for too few dollars and too many post-docs seeking too few faculty positions. We also noted that NIH leadership and others were increasingly interested in describing the agency’s portfolio not only in terms of the numbers of awards and dollars (as we do each year in our “By the Numbers” reports), but also in terms of the numbers of researchers those awards support. Today we show updated figures on how many researchers are vying for NIH support and how many are successful. Continue reading

FY 2017 By the Numbers

We recently released our annual web reports, success rates and NIH Data Book with updated numbers for fiscal year 2017. Looking at data across both competing and non-competing awards, NIH supports approximately 2,500 organizations. In 2017 about 640 of these organizations received funding for competing Research Project Grants (RPGs) which involved over 11,000 principal investigators. Continue reading

Patents and the Relative Citation Ratio: Correlations to Assess NIH Impact

We previously referenced Ioannidis’ and Khoury’s “PQRST” mnemonic for describing research impact: “P” is productivity, “Q” is quality, “R” is reproducibility, “S” is sharing, and “T” is translation.  We wrote several blogs about “P,” productivity, focusing on publications, citations, and more recently the relative citation ratio.  Now we’ll focus on a different kind of “P” for productivity, namely patents (which arguably are also related to “T” for translation).  …. Do NIH-supported papers that are cited by patents have a higher Relative Citation Ratio than those that are not cited by patents? As a refresher, the Relative Citation Ratio uses citation rates to measure the influence of a publication at the article level…. We identified 119,674 unique NIH grants that were funded between 1995 and 2007 and that generated at least one publication…. Continue reading

Data On Trends According to Career Stage

By the 21st Century Cures Act, the Next Generation Researchers’ Initiative calls on the NIH to develop policies to increase funding opportunities for new researchers seeking to secure early independence. To put the Initiative in perspective and to extend on previous blogs we’ve posted on changing demographics in NIH-funded researchers, we thought it would be useful to explore trends according to career stage.

First, some definitions.  We define “Early Stage Investigators” (ESI) as those who are within 10 years of completing their terminal degree or post-graduate clinical training and who have not yet secured independence as a PI of a substantial NIH research award.  …. Continue reading

Applications, Resubmissions, and the Relative Citation Ratio

Measuring the impact of NIH grants is an important input in our stewardship of research funding. One metric we can use to look at impact, discussed previously on this blog, is the relative citation ratio (or RCR). This measure – which NIH has made freely available through the iCite tool – aims to go further than just raw numbers of published research findings or citations, by quantifying the impact and influence of a research article both within the context of its research field and benchmarked against publications resulting from NIH R01 awards.

In light of our more recent posts on applications and resubmissions, we’d like to go a step further by looking at long-term bibliometric outcomes as a function of submission number. In other words, are there any observable trends in the impact of publications resulting from an NIH grant funded as an A0, versus those funded as an A1 or A2? And does that answer change when we take into account how much funding each grant received? …. Continue reading

Mid-career Investigators and Shifting Demographics of NIH Grant Recipients

While NIH policies focus on early stage investigators, we also recognize that it is in our interest to make sure that we continue to support outstanding scientists at all stages of their career. Many of us have heard mid-career investigators express concerns about difficulties staying funded. In a 2016 blog post we looked at data to answer the frequent question, “Is it more difficult to renew a grant than to get one in the first place?” We found that new investigators going for their first competitive renewal had lower success rates than established investigators. More recently, my colleagues in OER’s Statistical Analysis and Reporting Branch and the National Heart Lung and Blood Institute approached the concerns of mid-career investigators in a different way – by looking at the association of funding with age. Today I’d like to highlight some of the NIH-wide findings, recently published in the PLOS ONE article, “Shifting Demographics among Research Project Grant Awardees at the National Heart, Lung, and Blood Institute (NHLBI)”. Using age as a proxy for career stage, the authors analyzed funding outcomes for three groups …. Continue reading

Resubmissions Revisited: Funded Resubmission Applications and Their Initial Peer Review Scores

“My first submission got an overall impact score of 30. Is that good enough? What’s the likelihood I’ll eventually get this funded?”, or, “My first submission was not even discussed. Now what? Does anyone with an undiscussed grant bother to … Continue reading

Following up on the Research Commitment Index as a Tool to Describe Grant Support

Many thanks for your terrific questions and comments to last month’s post, Research Commitment Index: A New Tool for Describing Grant Support. I’d like to use this opportunity to address a couple of key points brought up by a number of commenters; in later blogs, we’ll focus on other suggestions.

The two points I’d like to address here are: 1) why use log-transformed values when plotting output (annual weighted relative citation ratio, or annual RCR) against input (annual research commitment index, or annual RCI), and 2) what is meant by diminishing returns. …. Continue reading

Research Commitment Index: A New Tool for Describing Grant Support

On this blog we previously discussed ways to measure the value returned from research funding. Several of my colleagues and I, led by NIGMS director Jon Lorsch – chair of an NIH Working Group on Policies for Efficient and Stable Funding – conceived of a “Research Commitment Index,” or “RCI.” We focus on the grant activity code (R01, R21, P01, etc) and ask ourselves about the kind of personal commitment it entails for the investigator(s). We start with the most common type of award, the R01, and assign it an RCI value of 7 points. And then, in consultation with our NIH colleagues, we assigned RCI values to other activity codes: fewer points for R03 and R21 grants, more points P01 grants. Continue reading