Nudge to Refill? Modeling Consumer Health Risk with Graph Convolutional Networks for Online Pharmaceutical Targeting
Wen Wang, Xueming Luo, Beibei Li, Haizhong Wang · Journal of the Association for Information Systems · 2021
Online pharmacy becomes a convenient and efficient channel these days with greater access and lower product costs. Notwithstanding the fastest growing trend, low conversion rates have been formidable challenge to the platforms. To date, little is known about how platforms can scientifically track the health risk of online pharmacy consumers using drug consumption and leverage the predicted risk in the targeting strategies to provide business values for platforms. This paper adopted a novel Attention-based Graph Convolutional Networks to model patient’s future health risks based on drug consumption data. We further leverage the predicted health risk in the pharmacy targeting strategy. We found the effectiveness of a drug-refilling reminder is closely related to the predicted health risk. Moreover, we found for patients who undergo the health status change, reminder facilitates their information learning towards the new disease. For patients with stability, reminder facilitates their adherence to existing disease management.