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Estimating the NIH Efficient Frontier

Author

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  • Dimitrios Bisias
  • Andrew W Lo
  • James F Watkins

Abstract

Background: The National Institutes of Health (NIH) is among the world’s largest investors in biomedical research, with a mandate to: “…lengthen life, and reduce the burdens of illness and disability.” Its funding decisions have been criticized as insufficiently focused on disease burden. We hypothesize that modern portfolio theory can create a closer link between basic research and outcome, and offer insight into basic-science related improvements in public health. We propose portfolio theory as a systematic framework for making biomedical funding allocation decisions–one that is directly tied to the risk/reward trade-off of burden-of-disease outcomes. Methods and Findings: Using data from 1965 to 2007, we provide estimates of the NIH “efficient frontier”, the set of funding allocations across 7 groups of disease-oriented NIH institutes that yield the greatest expected return on investment for a given level of risk, where return on investment is measured by subsequent impact on U.S. years of life lost (YLL). The results suggest that NIH may be actively managing its research risk, given that the volatility of its current allocation is 17% less than that of an equal-allocation portfolio with similar expected returns. The estimated efficient frontier suggests that further improvements in expected return (89% to 119% vs. current) or reduction in risk (22% to 35% vs. current) are available holding risk or expected return, respectively, constant, and that 28% to 89% greater decrease in average years-of-life-lost per unit risk may be achievable. However, these results also reflect the imprecision of YLL as a measure of disease burden, the noisy statistical link between basic research and YLL, and other known limitations of portfolio theory itself. Conclusions: Our analysis is intended to serve as a proof-of-concept and starting point for applying quantitative methods to allocating biomedical research funding that are objective, systematic, transparent, repeatable, and expressly designed to reduce the burden of disease. By approaching funding decisions in a more analytical fashion, it may be possible to improve their ultimate outcomes while reducing unintended consequences.

Suggested Citation

  • Dimitrios Bisias & Andrew W Lo & James F Watkins, 2012. "Estimating the NIH Efficient Frontier," PLOS ONE, Public Library of Science, vol. 7(5), pages 1-10, May.
  • Handle: RePEc:plo:pone00:0034569
    DOI: 10.1371/journal.pone.0034569
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    References listed on IDEAS

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    Cited by:

    1. Supradeep Dutta & Jenna Rodrigues & Timothy B. Folta, 2023. "Does NIH select the right healthcare ventures through the SBIR grant program?," The Journal of Technology Transfer, Springer, vol. 48(4), pages 1206-1220, August.
    2. Samson John Mgaiwa, 2018. "The Paradox of Financing Public Higher Education in Tanzania and the Fate of Quality Education: The Experience of Selected Universities," SAGE Open, , vol. 8(2), pages 21582440187, April.
    3. Luba Katz & Rebecca V Fink & Samuel R Bozeman & Barbara J McNeil, 2014. "Using Health Care Utilization and Publication Patterns to Characterize the Research Portfolio and to Plan Future Research Investments," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-12, December.
    4. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2012. "On the Efficiency-Fairness Trade-off," Management Science, INFORMS, vol. 58(12), pages 2234-2250, December.
    5. Park, Hyunwoo & Lee, Jeongsik (Jay) & Kim, Byung-Cheol, 2015. "Project selection in NIH: A natural experiment from ARRA," Research Policy, Elsevier, vol. 44(6), pages 1145-1159.

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