AI-Powered Telemedicine and Remote Patient Monitoring: Transforming Healthcare Accessibility

Abstract

The objective of this study is to investigate the application and potential impact of artificial intelligence (AI)-powered telemedicine and remote patient monitoring (RPM) in enhancing healthcare accessibility. The inherent nature of telemedicine, coupled with significant advancements in the field of AI, suggests that the widespread impact of such applications is imminent. Facilitated by progress in sensor technology, RPM can now measure various physiological parameters, including weight, glucose levels, hemoglobin levels, blood pressure, blood oxygen saturation, and heart rhythm, thereby enabling improved access to healthcare and population health management. Telemedicine and RPM demonstrate considerable potential to enhance healthcare accessibility, as discussed throughout this paper. This study commenced with an introduction to the theoretical foundations of telemedicine and AI, followed by an examination of telemedicine concepts, including its various forms and applications. There exists a pressing need for effective policies, training, infrastructure, and efficient utilization of data generated globally. AI must be employed to design and implement telecommunication systems and platforms that address ethical concerns. Consequently, collaboration, flexibility, and practical deployment, as well as empirical adoption and analysis of specific contexts, are essential. Each of the ordered variables responds to these developments in novel and more nuanced ways, excepting general progress as described in relation to the established framework. AI in global health is addressing sociocultural and political issues within the associated adjunct and research communities, critically summarizing whether we are producing a backdrop to the work presented, before assessing the challenges and considerations related to previous literature.