Telemedicine has emerged as a transformative tool for reducing health disparities globally, particularly in low- and middle-income countries (LMICs). However, existing models, such as the Technology Acceptance Model (TAM), often overlook critical cultural, infrastructural, and usability challenges unique to LMICs. This study introduces a hybrid framework integrating TAM with regional adaptations, emphasizing adaptive interfaces to enhance usability, accessibility, and equity in telemedicine systems.

A systematic review adhering to PRISMA guidelines was conducted, encompassing 365 records sourced from SCOPUS, Web of Science (WoS), and PubMed. After screening 364 unique records, 29 studies were shortlisted for qualitative and quantitative synthesis. From these, 10 studies were selected for thematic analysis, focusing on adaptive interface design and its effects on usability, accessibility, and equity metrics.

Adaptive interfaces reduced wait times by 30% and improved patient compliance with chronic care plans by 25%. Features such as AI-driven language translation significantly improved usability for underserved populations. Persistent barriers, including digital literacy gaps and gender disparities, were also identified.

The proposed hybrid framework illustrates the potential of adaptive interfaces to bridge healthcare gaps in LMICs. Future research should explore the scalability of this framework and further investigate AI-driven solutions to address disparities in telemedicine adoption.