During Covid-19, organizations, particularly hospitals, encountered difficulties in providing services. Telemedicine has shown to be an alternative in service provision during these times. Based on this, acceptance of telemedicine in Jordanian public hospitals has become a very important issue to increase the attention of the health care organization toward it. A conceptual model was constructed based on previous literature. The model includes government policy, the capacity of external suppliers, and the capacity of the project team, top management support, as independent variables where their influence on the acceptance of telemedicine in Jordanian public hospitals as a dependent variable is examined. Respondents were chosen using a Purposive sampling technique. Questionnaires were delivered to 320 respondents using Google Forms. SEM was used for statistical analysis. The findings revealed that all the proposed factors including government policy, external supplier capacity, project team capacity, and top management support have a significant influence toward accepting telemedicine. The results of this study may aid Jordanian public hospitals in making the best use of the proposed factors to increase the acceptance of telemedicine in Jordanian public hospitals.

This analysis delves into the evolving telemedicine landscape in India. It dissects the service models employed by both government and private healthcare providers, highlighting their distinct approaches in delivering telemedicine services. The study unveils how government initiatives strive to bridge geographical gaps and widen accessibility, while private players leverage technology for a more patient-centric experience. Furthermore, the research investigates patient perceptions of the impact of 5G technology on telemedicine services. It evaluates aspects crucial for effective consultations, such as connected devices, connection stability, video quality, speed of data transfer, and overall user satisfaction. This analysis reviews patient experiences with 5G and its potential advancements in transforming telemedicine delivery. The exploration then extends to the potential advantages and growth prospects for telemedicine service providers in India's healthcare sector. The analysis highlights key benefits like increased geographical reach, improved cost-effectiveness for both patients and providers and enhanced scalability to cater to a wider population. Additionally, it explores the possibilities of deeper technological integration within healthcare systems, market expansion into underserved regions, and the role of supportive regulations in fostering innovation. By examining potential investment opportunities and strategic partnerships, the research offers valuable insights for stakeholders interested in capitalizing on the burgeoning telemedicine market in India. This comprehensive examination provides critical insights into the current state and future prospects of telemedicine in India. It sheds light on the evolving landscape, the impact of technological advancements, and the potential for this innovative approach to revolutionize healthcare delivery across the nation.

In contemporary medicine, two trends are of particular significance: the establishment of Telehealth as a fundamental component of healthcare delivery, and the emergence of Large Language Models (LLMs) as a transformative category of artificial intelligence. The convergence of these domains has created a new, dynamic, and rapidly expanding research frontier. Despite this escalating interest, a comprehensive map of the field's intellectual foundations, key contributors, and thematic progression has yet to be established. This study addresses this critical knowledge gap by employing a quantitative scientometric methodology to systematically map the intellectual structure and evolutionary trajectory of research at the intersection of Telehealth and LLMs. We conducted a comprehensive bibliometric analysis of 670 scientific documents extracted from the Web of Science (WoS) Core Collection database, spanning the period from 1997 to Oct 2025. The analysis utilized performance metrics and network mapping tools to identify publication dynamics, influential actors, and core conceptual themes. The findings reveal a field in a state of “Hypergrowth“, characterized by an exponential increase in scientific production, particularly after 2021. The United States and China are identified as the dominant leaders in research output. Thematic analysis demonstrates a clear paradigm shift within the literature: an evolution from a broad focus on general artificial intelligence and machine learning applications toward a more specialized and intense concentration on the capabilities and implications of LLMs and Generative AI. This research provides the first large-scale quantitative map of the Telehealth and LLM landscape. It documents a field that is maturing at an accelerated rate, creating an urgent need for scholarly and practical frameworks that bridge the gap between rapid technological innovation and the slower-moving, yet critical, domains of clinical validation, regulatory oversight, and ethical considerations. The insights provided herein offer a data-driven foundation for researchers, policymakers, and practitioners to navigate and contribute to this critical and rapidly evolving field.

In this study, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was applied to rank the telemedicine performance of seven major Japanese cities: Fukuoka, Sapporo, Yokohama, Kyoto, Osaka, Nagoya, and Tokyo. The ranking was consistent throughout the analysis based on the five criteria—Infrastructure, Healthcare System Integration, Accessibility & Equity, Service Breadth & Quality, and Regulatory Environment. Fukuoka was the best performer, followed by Sapporo, and Tokyo, even with its high medical resources, ranked last. The same ranking was observed even when the cost criterion was given a 50% weight, which means that structural and governance factors have more influence than affordability in determining performance. The findings question the view that telemedicine success relies exclusively on economic and medical scale. Rather, they point to the effectiveness of Japan's regional innovation policies; for example, proactive local governance, as in the case of Fukuoka's Special Zone status, and a clear demographic mandate for rural healthcare access, as in Hokkaido, are considered more important drivers of a robust and equitable telemedicine ecosystem.

This study evaluates the relative efficiency of digital health adoption across ten major German cities and regions. In a landscape where digital transformation is critical, this research moves beyond mere technological assessment to determine which locales most effectively convert inputs into outputs. A multi-criteria decision-making framework is employed, integrating Data Envelopment Analysis (DEA) under both constant and variable returns-to-scale assumptions and the TOPSIS method. Key metrics include Infrastructure, Healthcare System Integration, Service Breadth, Regulatory Environment, and a critical cost factor, Accessibility & Equity. Results from DEA models highlight a system-wide scale inefficiency, yet identify specific efficient units under variable returns, including Berlin, Rhineland-Pfalz, Leipzig, and Aachen. The TOPSIS analysis, particularly when prioritizing cost-equity, reveals a distinct ranking: Rhineland-Pfalz, Leipzig, and Aachen emerge as top performers, while major economic hubs like Munich, Frankfurt, and Stuttgart demonstrate lower efficiency due to high costs and systemic fragmentation. The findings challenge the presumption that economic scale guarantees digital health efficiency, instead underscoring the superior performance of strategically coordinated and equity-focused models. This study provides policymakers with a robust framework for benchmarking and highlights governance and integration, not just investment, as the key levers for enhancing digital health system performance.

This research applies TOPSIS, which stands for Technique for Order of Preference by Similarity to Ideal Solution, to evaluate and rank the performance of telemedicine in the seven Chinese cities—Hangzhou, Wuhan, Chengdu, Shanghai, Beijing, Guangzhou, and Shenzhen. The evaluation was based on five major criteria: Infrastructure, Healthcare System Integration, Accessibility & Equity, Service Breadth & Quality and Regulatory Environment. In a noteworthy finding, Hangzhou was at the top all the time, while Shenzhen was at the bottom despite its technological might. The result was very strong, being the same even when the cost criterion was given 50% weight which showed that the price factor alone does not overpower other performance disparities. The outcomes are a surprise to the common understanding that very high-quality medical institutions in a city and very good technology infrastructure are the only factors that determine the success of telemedicine. Rather, a city’s ability to build an integrated, user-centered digital ecosystem determines the leadership in telemedicine. The first position of Hangzhou indicates the benefit of unrestricted healthcare accessibility through a platform-based system whereas the last position of Shenzhen points out the drawbacks of an expensive and inequitable system. This study shifts the paradigm for future telemedicine cities from "Medical Resource" to "Integrated Ecosystem" model, thus, posing significant implications for the decision makers who strive to ensure effective and equal access to digital health services.