This research paper presents an integrated digital healthcare framework aimed at improving urban healthcare accessibility in metropolitan cities. The study addresses critical challenges such as traffic congestion, unequal resource distribution, and delays in accessing medicines after teleconsultation. The proposed system combines teleconsultation services with AI-optimized hyperlocal medicine delivery to create an end-to-end healthcare solution. It incorporates Mixed Integer Linear Programming (MILP) for efficient delivery routing and Explainable Artificial Intelligence (XAI) techniques such as SHAP and LIME to enhance transparency in clinical decision-making. A survey conducted across five major Indian metropolitan cities highlights significant disparities in telehealth adoption. The framework is validated through simulations and case studies, demonstrating a reduction of up to 78% in healthcare access time and approximately 25% cost optimization in delivery. The proposed model offers a scalable and efficient approach to building equitable digital healthcare ecosystems by bridging the gap between telemedicine and last-mile medicine access.
Sumit Sharma (2026) studied this question.