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Participatory methods to support team science development for predictive analytics in health

  • Armen C. Arevian (a1), Doug Bell (a2), Mark Kretzman (a1), Connie Kasari (a1), Shrikanth Narayanan (a3), Carl Kesselman (a4), Shinyi Wu (a5), Paul Di Capua (a6), William Hsu (a7), Mathew Keener (a8), Joshua Pevnick (a9), Kenneth B. Wells (a1) and Bowen Chung (a1) (a10)...
Abstract

Predictive analytics in health is a complex, transdisciplinary field requiring collaboration across diverse scientific and stakeholder groups. Pilot implementation of participatory research to foster team science in predictive analytics through a partnered-symposium and funding competition. In total, 85 stakeholders were engaged across diverse translational domains, with a significant increase in perceived importance of early inclusion of patients and communities in research. Participatory research approaches may be an effective model for engaging broad stakeholders in predictive analytics.

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Copyright
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike licence (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the same Creative Commons licence is included and the original work is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use.
Corresponding author
*Address for correspondence: A. C. Arevian, MD, PhD, Semel Institute, University of California, Los Angeles, 10920 Wilshire Blvd Suite 300, Los Angeles, CA 90095, USA. (Email: aarevian@mednet.ucla.edu)
References
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