The Science of Precision Prevention
Thomas A. Pearson, Debbie Vitalis, Charlotte Pratt, Rebecca Campo, Antonis A. Armoundas, David H. Au, Bettina M. Beech, Olga Brazhnik, Christopher G. Chute, Karina W. Davidson, Ana V. Diez–Roux, Lawrence J. Fine, Davera Gabriel, P. Groenveld, Jaclyn Hall, Alison Brown, Hui Hu, Heng Ji, Amy Kind, William E. Kraus, Harlan M. Krumholz, George A. Mensah, Raina M. Merchant, Dariush Mozaffarian, David M. Murray, Dianne Neumark‐Sztainer, Maya Petersen, David C. Goff
Abstract
Precision prevention embraces personalized prevention but includes broader factors such as social determinants of health to improve cardiovascular health. The quality, quantity, precision, and diversity of data relatable to individuals and communities continue to expand. New analytical methods can be applied to these data to create tools to attribute risk, which may allow a better understanding of cardiovascular health disparities. Interventions using these analytic tools should be evaluated to establish feasibility and efficacy for addressing cardiovascular disease disparities in diverse individuals and communities. Training in these approaches is important to create the next generation of scientists and practitioners in precision prevention. This state-of-the-art review is based on a workshop convened to identify current gaps in knowledge and methods used in precision prevention intervention research, discuss opportunities to expand trials of implementation science to close the health equity gaps, and expand the education and training of a diverse precision prevention workforce.