Abanibhusan Jena

Background: Telemedicine has emerged as a transformative solution in healthcare, offering improved accessibility and efficiency. However, its widespread adoption remains influenced by policy frameworks, digital infrastructure, and financial sustainability. This study examines the role of policy innovation in telemedicine adoption and implementation, assessing regulatory impact, technological readiness, and reimbursement structures. Methods: A cross-sectional survey design with a mixed-methods approach was employed, integrating quantitative surveys and qualitative interviews. Data were collected from healthcare policymakers, administrators, physicians, and technology developers across hospitals, clinics, and telemedicine service providers. Logistic regression and chi-square tests were conducted to analyze key predictors of telemedicine adoption, including regulatory support, digital infrastructure, and reimbursement policies. A total of 400 participants were surveyed, and 25 stakeholders were interviewed to analyze key predictors of telemedicine adoption. Results: The findings indicate that institutions with clear licensing regulations and policy support exhibited significantly higher telemedicine adoption rates (OR = 2.15, p = 0.004). Standardized reimbursement policies positively influenced adoption rates (χ² = 14.91, p = 0.008). Digital infrastructure readiness, including broadband connectivity and EHR interoperability, was strongly associated with increased telemedicine utilization (OR = 2.31, p = 0.005). Major barriers included regulatory fragmentation, financial constraints, and technological literacy gaps. Conclusion: Policy innovation, digital infrastructure investments, and structured reimbursement models are critical for telemedicine expansion. Addressing regulatory inconsistencies and financial limitations will enhance adoption. Future research should explore long-term policy impacts and AI integration in telemedicine.

Diabetes, hypertension, and cardiovascular diseases are some of the common diseases that are prevalent in the world and exert a lot of pressure on the health systems. The conventional management techniques do not provide immediate and personalized attention. The purpose of this research is to analyze the impact of AI based health monitoring systems for enhancing chronic diseases. Smartwatches and mobile applications in combination with artificial intelligence tools enable users to monitor, evaluate, and provide interventions on a daily basis. The study employs both quantitative and qualitative research to assess the effectiveness of AI tools on patients’ outcomes in a RCT trial. The results indicate the improvement of the patients’ health outcomes including HbA1c, blood pressure, and medication adherence. The AI systems are more efficient and among all the models the CNN model has the highest accuracy and prediction. The cost breakdown demonstrates that while the setup cost of AI-based monitoring systems is relatively higher than the standard care, the annual operating cost is relatively lower and the QALYs per patient is also higher. There are limitations such as data privacy and technological implementation and thus it is suggested that subsequent research take them into consideration. The study finds that AI in health monitoring is capable of revolutionizing chronic disease management through efficiency, cost and patient centeredness.The cost breakdown demonstrates that while the setup cost of AI-based monitoring systems is relatively higher than the standard care, the annual operating cost is relatively lower and the QALYs per patient is also higher. There are limitations such as data privacy and technological implementation and thus it is suggested that subsequent research take them into consideration. The study finds that AI in health monitoring is capable of revolutionizing chronic disease management through efficiency, cost and patient centeredness.

Cancer therapy is an intricate and constantly evolving field, marked by a multitude of challenges in achieving optimal drug therapies. This abstract presents a comprehensive exploration of innovative strategies designed to master the intricate realm of medicine management in the context of cancer treatment. Leveraging precision medicine techniques, pharmacogenomics, targeted therapies, and immunotherapies, This paper as it is one of the