期刊
AMERICAN JOURNAL OF LIFESTYLE MEDICINE
卷 14, 期 3, 页码 289-293出版社
SAGE PUBLICATIONS INC
DOI: 10.1177/1559827619843489
关键词
precision medicine; digital therapeutics; behavior change; mobile health (mHealth); machine learning
资金
- Johns Hopkins School of Medicine Medical Scientist Training Program (National Institutes of Health: Institutional Predoctoral Training Grant T32)
- National Institutes of Health (Ruth L. Kirschstein Individual Predoctoral NRSA)
- Johns Hopkins Individualized Health (inHealth) Initiative
Chronic disease now affects approximately half of the US population, causes 7 in 10 deaths, and accounts for roughly 80% of US health care expenditure. Because the root causes of chronic diseases are largely behavioral, effective therapies require frequent, individualized interventions that extend beyond the hospital and clinic to reach patients in their day-to-day lives. However, a mismatch currently exists between what the health care system is equipped to provide and the interventions necessary to effectively address the chronic disease burden. To remedy this health crisis, we present an individualized, data-driven digital approach for chronic disease management and prevention through precision behavior change. The rapid growth of information, biological, and communication technologies makes this an opportune time to develop digital tools that deliver precision interventions for health behavior change to address the chronic disease crisis. Building on this rapid growth, we propose a framework that includes the precise targeting of risk-producing behaviors using real-time sensing technology, machine learning data analysis to identify the most effective intervention, and delivery of that intervention with health-reinforcing feedback to provide real-time, individualized support to empower sustainable health behavior change.
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