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arXiv · 2407.20241

NudgeRank: Digital Algorithmic Nudging for Personalized Health

Jodi Chiam·Aloysius Lim·Ankur Teredesai
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Abstract

In this paper we describe NudgeRank, an innovative digital algorithmic nudging system designed to foster positive health behaviors on a population-wide scale. Utilizing a novel combination of Graph Neural Networks augmented with an extensible Knowledge Graph, this Recommender System is operational in production, delivering personalized and context-aware nudges to over 1.1 million care recipients daily. This enterprise deployment marks one of the largest AI-driven health behavior change initiatives, accommodating diverse health conditions and wearable devices. Rigorous evaluation reveals statistically significant improvements in health outcomes, including a 6.17% increase in daily steps and 7.61% more exercise minutes. Moreover, user engagement and program enrollment surged, with a 13.1% open rate compared to baseline systems' 4%. Demonstrating scalability and reliability, NudgeRank operates efficiently on commodity compute resources while maintaining automation and observability standards essential for production systems.

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Jodi Chiam, Aloysius Lim, Ankur Teredesai. 2024-07-16. NudgeRank: Digital Algorithmic Nudging for Personalized Health. https://doi.org/10.1145/3637528.3671562

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