Bridging the Digital Divide: A Socio-Technical Framework for AI-Enabled Rural Healthcare Access in Developing Economies
Keywords:
Global digital divide in healthcare access, AI-enabled mHealth systems, Offline-first mobile app design, Federated learning in healthcare, AI triage and referral tools, Rural healthcare innovation, Edge computing for medical applications, Data privacy and health informatics, Implementation in Pakistan, Nigeria, and Peru, Cross-national policy and ethical guidelines, Public-private partnerships in health tech, Socio-technical systems for underserved regions.Abstract
This study introduces a federated, AI-enabled mobile health (mHealth) framework designed to improve healthcare accessibility in digitally underserved rural regions of developing economies. The framework is built upon an offline-first architecture that supports AI-driven clinical triage, referral guidance, and secure caching of medical records on edge devices, minimizing reliance on continuous internet connectivity. Field deployments in rural areas of Pakistan, Nigeria, and Peru provide empirical evidence of the system's viability and adaptability across varied socio-technical contexts. The study outlines key implementation challenges, including infrastructure limitations, healthcare worker training, and multilingual data processing. A comprehensive stakeholder analysis highlights the roles of public health ministries, NGOs, and telecom providers in supporting sustainable deployment. The paper also discusses ethical, regulatory, and data governance considerations essential for cross-national integration of federated learning systems in healthcare. This work contributes a scalable model for bridging the global digital divide in rural healthcare through inclusive, context-sensitive AI innovation.
