Journal of Clinical and Translational Science (Jan 2021)

Encouraging the scale-up of proven interventions: Infrastructure development for the “Evidence-to-Implementation” award

  • Andrew Quanbeck,
  • Roberta A. Johnson,
  • Mondira Saha-Muldowney,
  • Felice Resnik,
  • Sheena Hirschfield,
  • Rachael R. Meline,
  • Jane E. Mahoney

DOI
https://doi.org/10.1017/cts.2021.828
Journal volume & issue
Vol. 5

Abstract

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Abstract Background/Objective: Although most research universities offer investigators help in obtaining patents for inventions, investigators generally have few resources for scaling up non-patentable innovations, such as health behavior change interventions. In 2017, the dissemination and implementation (D & I) team at the University of Wisconsin’s Clinical and Translational Science Award (CTSA) created the Evidence-to-Implementation (E2I) award to encourage the scale-up of proven, non-patentable health interventions. The award was intended to give investigators financial support and business expertise to prepare evidence-based interventions for scale-up. Methods: The D & I team adapted a set of criteria named Critical Factors Assessment, which has proven effective in predicting the success of entrepreneurial ventures outside the health care environment, to use as review criteria for the program. In March 2018 and February 2020, multidisciplinary panels assessed proposals using a review process loosely based on the one used by the NIH for grant proposals, replacing the traditional NIH scoring criteria with the eight predictive factors included in Critical Factors Assessment. Results: two applications in 2018 and three applications in 2020 earned awards. Funding has ended for the first two awardees, and both innovations have advanced successfully. Conclusion: Late-stage translation, though often overlooked by the academic community, is essential to maximizing the overall impact of the science generated by CTSAs. The Evidence-to-implementation award provides a working model for supporting late-stage translation within a CTSA environment.

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