Capturing Impact: A Method for Measuring Progress

NIH’s mission is to seek fundamental knowledge about the nature and behavior of living systems and the application of that knowledge to enhance health, lengthen life, and reduce illness and disability.

Let me pose a simple question – how do we know if NIH is achieving its mission?  It’s tricky enough to assess how effective we are at generating fundamental scientific knowledge, though we have decent grasp on that side of the equation.  We can link tens of thousands of biomedical research articles published each year to the NIH grants that supported them.  But can we take it a few sizeable steps further and systematically connect our research efforts to advances in human health?  And how can we use what we learn to design policies and strategies to speed innovation and biomedical progress?

The pathways from research to practice to changes in public health are typically non-linear and unpredictable.  For a scientific discovery to make that journey may take decades or more and involves a complex ecosystem – academic scientists, research funders, policymakers, health product developers, regulators, clinicians, and a receptive public, just to name a few. To better understand these intricate pathways, we conducted a handful of case studies that help illuminate the types of evidence and data that NIH can draw from in order to measure our progress towards our ultimate goal – improving human health.

Today we are publishing three case studies in a new section on the “Impact of NIH Research” website, titled “Our Stories.”  These studies, developed with our partners in the Institutes and Centers, trace the chain of evidence between scientific discoveries to longer-term health impact, reaching back into basic research findings that set the stage for progress and noting NIH’s role as well as that of others along the way.  Study topics range from a childhood vaccine that dramatically reduced the incidence of a deadly infection, to a paradigm-shifting approach for treating cancer, to a suite of neurotechnologies for profound impairments like deafness, paralysis, and Parkinson’s disease.  Focusing on these topics gave us a chance to examine the factors that led to their success and broadly map the data sources and strategies we should cultivate in order to improve our capacity for assessing impact (positive, negative, and null) across NIH’s portfolio.  In an era of big data, when the ability to link and analyze multiple streams of information has never been better, this seemed an opportune time to go on a data hunt.

The data we drew from were wide-ranging, including grants, research publications, press releases, patents, FDA approvals, clinical guidelines, policy and regulatory decisions, industry reports, economic analyses, medical expenditures, and public health statistics.  In piecing these disparate sources together, some clear needs emerged – it would be fantastic to link NIH’s grants data to structured data from other Federal sources, like FDA, CDC, AHRQ, USPTO, and CMS.  Citations in patents, FDA approval packages, clinical trials and guidelines, and regulations could help link such outputs to federal funding.  One of the biggest challenges is the need for strategies to connect research advances to long-term changes in health practice and outcomes, for example data on healthcare utilization, disease statistics, and quality of life measures.  We at NIH, and particularly our colleagues in the Office of Extramural Research and the Office of Portfolio Analysis, are pushing to develop and bring just these kinds of data into our own administrative data systems. We’re hopeful that emerging data tools may one day keep track of our impacts, and our influence on the health of the Nation, almost as thoroughly as we track our grants.

The studies we post today are just a few examples of the continuing work of NIH to measure our progress in improving the health of all Americans and those across the globe.  I invite you to take a look, not just at the story itself, but also the backbone of evidence behind it.  Hopefully, you’ll get a sense of the vibrant and diverse ways that NIH turns discovery into health, and how we’re grappling with making that process even better.

Posted by Dr. Carrie D. Wolinetz, June 1, 2016


    Dear Dr. Wolinetz – I really enjoyed reading “Capturing Impact: A Method for Measuring Progress.” The ideas that you presented, the opportunities for putting data together to facilitate the emergence of meaningful insight about the impact of research on advances on human health is thrilling, and frankly, ripe with challenge! I think about demonstrating impact in a relatively smaller frame – that of individual investigators and how to tie the impact and continuity of an individual’s research portfolio together; effectively making each investigator and their portfolio, big or small, a case study. I’m sure the NIH has thought about this and about how linking individual case studies together will show strengths and gaps and could possibly be predictive. I’m thinking about how to show research impact here at the University of South Alabama – an emerging research institution – where it is small enough, at the present moment, to get my arms around the NIH – funded portfolio and to practice some ideas that will show impact and that I hope will scale as the institution grows. I will subscribe to your blog and I look forward to following the discussion.

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