2024/08/15 by Ana Fernández del Río, del Río, Ana Fernández, Michael Brennan Leong +13
Business, Management and Accounting · Computer Science · #Artificial Intelligence (cs.AI) #Big Data and Business Intelligence #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Online Learning and Analytics #Open Source Software Innovations
paper · pdf · doi:10.48550/arxiv.2408.08024
openalex publication_date 2024/08/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper introduces a reinforcement learning (RL) platform that enhances end-to-end user journeys in healthcare digital tools through personalization. We explore a case study with SwipeRx, the most popular all-in-one app for pharmacists in Southeast Asia, demonstrating how the platform can be used to personalize and adapt user experiences. Our RL framework is tested through a series of experiments with product recommendations tailored to each pharmacy based on real-time information on their purchasing history and in-app engagement, showing a significant increase in basket size. By integrating adaptive interventions into existing mobile health solutions and enriching user journeys, our platform offers a scalable solution to improve pharmaceutical supply chain management, health worker capacity building, and clinical decision and patient care, ultimately contributing to better healthcare outcomes.