Authors - Saravana Kumari Shanmuga Sundaram, Shyam A V Abstract - e-Sanjeevani is India's national telemedicine system. It had its modest origin during the COVID lockdown and is now the biggest recorded platform worldwide for primary healthcare, especially for underprivileged communities. For the design, implementation, and assessment, this article investigates the two service models of the platform: e-Sanjeevani OPD (patient-to-doctor) and e-Sanjeevani HWC (doctor-to-doctor). This study assesses e-Sanjeevani's scalability, usage patterns, and integration with the more extensive health system, such as the Ayushman Bharat Health Accounts (ABHA), and National Digital Health Mission (NDHM) frameworks, based on research literature, secondary data from official sources, and policy documents. For those who do not have access to primary healthcare, the platform has provided several advantages. However, there have been difficulties reaching the system's maximum efficiency. By early 2025, the platform had helped over 342 million individuals throughout India, supporting several aspects of healthcare delivery like diabetic foot, caries in elderly persons, and so on. The research suggests a conceptual framework for incorporating Large Language Models (LLMs) into e-Sanjeevani, addressing the existing challenges and extending the solution’s possibilities. The framework includes LLM-driven features, including clinical decision support, real-time translation, automated documentation, and individualized patient education. It comprises a layered architecture effortlessly incorporated into telehealth, supporting artificial intelligence augmentation at pre-consultation, consultation, and post-consultation phases. This integration can significantly increase provider efficiency, lower workload, and raise the general quality of treatment. The results underline present achievements and the transforming opportunities of LLM-enabled fair telemedicine for India and other low- and middle-income nations.
Open Zoom
