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A behavioral approach to personalizing public health

Published online by Cambridge University Press:  09 July 2020

KAI RUGGERI*
Affiliation:
Columbia University, Mailman School of Public Health, Department of Health Policy and Management, New York, NY, USA
AMEL BENZERGA
Affiliation:
Columbia University, Mailman School of Public Health, Department of Health Policy and Management, New York, NY, USA Sciences Po Paris, School of Public Affairs, Paris, France
SANNE VERRA
Affiliation:
Columbia University, Mailman School of Public Health, Department of Health Policy and Management, New York, NY, USA Department of Interdisciplinary Social Science, Utrecht University, Utrecht, The Netherlands
TOMAS FOLKE
Affiliation:
Columbia University, Mailman School of Public Health, Department of Health Policy and Management, New York, NY, USA
*
*Correspondence to: Columbia University, Mailman School of Public Health, Health Policy and Management Department,722 W 168th St., New York, NY 10032, USA. E-mail: dr2946@cumc.columbia.edu

Abstract

Behavioral policies are increasingly popular in a number of health care contexts. However, evidence of their effectiveness, specifically in low-income and highly disadvantaged populations, is limited. Some positive effects have been found for adaptive interventions, which merge more personalized approaches with advances in data collection and modern analytical methods. These approaches have only recently become feasible, as their implementation requires a confluence of large-scale datasets, contemporary machine learning, and validated behavioral insights. Such methods have considerable potential to improve outcomes without requiring substantial increases in effort on the part of individuals. Using examples from health insurance choice, clinical attendance rates, and prescription of medicines, we present an argument for how adaptive approaches, especially those considering disadvantaged populations explicitly, offer an opportunity to generate equity in public health.

Type
New Voices
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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