Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services
This addresses pharmacy service optimization in healthcare, particularly in resource-limited settings, but appears incremental as it applies existing reinforcement learning methods to a new domain.
The paper tackles the problem of enhancing pharmacy services in low- and middle-income countries by developing a reinforcement learning system to deliver personalized behavioral interventions via mobile apps, with initial experiments conducted using the SwipeRx app in Indonesia.
Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance their skills, public health awareness, and pharmacy inventory management, ensuring access to essential medicines that ultimately benefit their patients. We introduce a reinforcement learning operational system to deliver personalized behavioral interventions through mobile health applications. We illustrate its potential by discussing a series of initial experiments run with SwipeRx, an all-in-one app for pharmacists, including B2B e-commerce, in Indonesia. The proposed method has broader applications extending beyond pharmacy operations to optimize healthcare delivery.