Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services

TL;DR

This paper presents a reinforcement learning system that personalizes behavioral interventions for pharmacists via mobile apps, aiming to improve healthcare delivery and pharmacy services in low-resource settings.

Contribution

It introduces a novel reinforcement learning approach for delivering personalized behavioral nudges to pharmacists through mobile health applications.

Findings

Initial experiments with SwipeRx demonstrate the system's potential.

The method can improve pharmacy inventory management and public health awareness.

Broader applications in healthcare delivery are feasible.

Abstract

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.