<![CDATA[The global healthcare landscape is undergoing a digital transformation, driven by the integration of Artificial Intelligence (AI), Big Data, and Telemedicine. These technologies have become essential not only in addressing immediate clinical demands but also in shaping long-term system-wide reforms. However, digital health adoption remains uneven across countries, influenced by variations in infrastructure, policy frameworks, and socioeconomic conditions. This study aims to explore how the integration of AI, Big Data, and Telemedicine contributes to healthcare system transformation through a comparative qualitative-descriptive analysis of four countries: the United States, India, Indonesia, and Rwanda. Secondary data were collected from peer-reviewed journals, government reports, and institutional publications from 2019 to 2024. Thematic analysis focused on policy direction, infrastructure readiness, implementation models, and observed outcomes. Findings reveal that while the U.S. leads with private-sector-driven innovation, India emphasizes national-scale integration, Indonesia navigates digital transformation in a geographically dispersed setting, and Rwanda demonstrates scalable solutions in low-resource environments. Despite different contexts, common challenges include interoperability gaps, ethical data governance, and disparities in digital literacy. The study synthesizes strategic insights and highlights the importance of inclusive, adaptable, and well-regulated digital ecosystems. It concludes that successful digital health implementation depends not only on technology, but also on governance, investment, and equity-focused design.]]>
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