Bibliometric Insights into the Evolution of Health Information Systems and Telemedicine Research

ABSTRACT


INTRODUCTION
The integration of technology into healthcare systems has revolutionized the way medical information is managed and utilized [1].Health Information Systems (HIS) utilize sophisticated information technology tools to efficiently collect, store, and disseminate healthcare data [2].This not only streamlines administrative processes but also facilitates seamless communication among healthcare professionals, enabling swift access to patient records and collaborative decisionmaking [3], [4].Moreover, HIS platforms are designed to enhance patient care by providing clinicians with comprehensive and up-to-date medical information, leading to more accurate diagnoses and personalized treatment plans [4].
Telemedicine represents a groundbreaking application of telecommunications technology in healthcare delivery [5].By leveraging digital communication channels, telemedicine enables healthcare providers to offer clinical services remotely, overcoming geographical barriers and improving healthcare accessibility, especially in underserved areas [6], [7].Through virtual consultations, remote monitoring, and telehealth platforms, patients can receive timely medical advice and intervention without the need for physical visits to healthcare facilities [8].This not only saves time and resources but also empowers patients to take a more proactive role in managing their health [9].
The synergy between Health Information Systems and Telemedicine holds immense potential for transforming healthcare delivery on a global scale [10].Integrated HIS platforms can seamlessly incorporate telemedicine functionalities, allowing for the efficient exchange of patient data and real-time communication between healthcare providers and patients [11].This integration enhances care coordination, reduces medical errors, and improves patient outcomes by ensuring continuity of care across different care settings [12], [13].Furthermore, the adoption of telemedicine within HIS frameworks enables healthcare organizations to optimize resource allocation, minimize healthcare disparities, and adapt to evolving patient needs and preferences [14].
The rapid evolution of technology and its applications in healthcare present a dynamic research landscape in Health Information Systems and Telemedicine.However, there is a lack of comprehensive analysis regarding the trajectory of research in this domain.Identifying the gaps, trends, and influential factors shaping HIS and Telemedicine research can facilitate a deeper understanding of the field's progression and inform strategic initiatives for future advancements.The primary objective of this research is to conduct a bibliometric analysis of the literature pertaining to Health Information Systems and Telemedicine.Specifically, the study aims to:

Health Information Systems
Health Information Systems (HIS) are complex entities that play a crucial role in guiding public health policies and programs.These systems consist of diverse components that interact and depend on each other.

Telemedicine
Telemedicine is an emerging healthcare delivery model that uses information and communication technologies (ICTs) to provide medical services remotely.It has the potential to improve healthcare outcomes, particularly in resourcelimited settings, by improving patient access to medical care, reducing healthcare costs, and increasing patient satisfaction [20].Telemedicine is the use of computers and automated data to deliver technologies and promote healthcare when patients are located far away from professionals [21]- [23].It cannot replace old-fashioned medicine everywhere, especially in emergency medicine, but it offers opportunities for medical education and training, remote consultations and diagnoses, and remote patient health status monitoring [24].The use of telemedicine, especially during crises like the Covid-19 pandemic, has the potential to deliver accessible, affordable, and effective healthcare services worldwide [24].It overcomes distance as a critical factor by using communication and information technologies, improving access to healthcare and complementing healthcare itself .Continued research and innovation are needed to ensure the success and sustainability of telemedicine as a healthcare delivery model .

METHODS
The research will involve systematic data collection from academic databases such as PubMed, Scopus, Web of Science, and Google Scholar.Keywords related to Health Information Systems, Telemedicine, and related terms will be used to retrieve relevant articles published within a specified time frame.Articles included in the analysis will be peer-reviewed research papers, conference proceedings, and review articles focusing on Health Information Systems, Telemedicine, or related topics.The inclusion criteria will encompass studies published in English and within a defined time period to capture recent trends in the field.A bibliometric analysis will be conducted to quantitatively assess the characteristics of the retrieved literature.Key bibliometric indicators such as publication counts, citation counts, collaboration patterns, and geographic distribution will be analyzed using bibliometric software tool such as VOSviewer.Systems and Telemedicine.The data covers publication years from 1976 to 2024, spanning a period of 48 citation years.A total of 980 papers were included in the analysis, accumulating a substantial number of citations totaling 34,699.On average, the research received approximately 722.90 citations per year, reflecting the impact and relevance of the literature in this field.Each paper garnered an average of 35.41 citations, highlighting the influence of individual contributions.Collaboration was common, with an average of 2.53 authors per paper.The h-index, a widely used metric to assess research impact, stood at 91, indicating that 91 papers in the dataset received at least 91 citations each.The g-index, a variation of the h-index, was calculated at 167, providing another measure of research productivity and impact.The hI,norm and hI,annual metrics offer normalized measures of the h-index, accounting for variations in citation practices over time.Additionally, the hA index, which accounts for author order, was calculated at 24, indicating the contribution of prolific authors to the field.Furthermore, the table provides insights into the distribution of highly cited papers, with 451 papers having an accumulated citation count of at least 1, 313 papers with a count of at least 2, and so forth, up to 32 papers with a count of at least 20, underscoring the presence of influential works in the literature.These metrics offer a comprehensive overview of the research landscape in Health Information Systems and Telemedicine, highlighting its impact, productivity, and collaborative nature.In the context of this visualization, the areas that are less bright likely represent keywords or topics that are currently less prominent or developed in the research literature but could be potential areas for future research.The less bright area contains keywords such as: "advanced health telematic", "knowledge", "security", "physician", "effectiveness", "nigeria", "future".This suggests a potential research topic in the future could focus on the development and effectiveness of advanced health telematic systems, with an emphasis on security and physician involvement.Furthermore, the mention of Nigeria implies that there is room for country-specific studies, examining the future of health telematics in the context of Nigeria or similar regions.Research could explore how these systems can be optimized to improve healthcare delivery, ensure data security, and be effectively used by healthcare professionals.The need for such research might be driven by ongoing technological advancements and the continuous evolution of healthcare needs, especially in developing countries or regions with unique challenges.The visualization uses different colors to potentially indicate different clusters or groups of researchers that are more closely associated with each other than with those in other clusters.The image shows three distinct clusters: blue, red, and green.The blue cluster, with authors "Puustjärvi, J" and "Puustjärvi, L", indicates that these authors are linked, possibly through co-authorship or subject matter.The red cluster with "Winter, A", "Ammenwerth, E", and "Haux, R", and the green cluster with "Blobel, B" and "Pharow, P", suggest these authors are similarly connected.The last one is the green cluster consist of "blobel,b" "pharow,p".

CONCLUSION
In conclusion, the bibliometric analysis of the literature on Health Information Systems (HIS) and Telemedicine provides valuable insights into the evolution and trends of research in this dynamic field.
The comprehensive metrics reveal a robust body of literature with a significant impact, as evidenced by the high citation counts and collaborative nature of the research.The thematic network analysis highlights key areas of focus, including telehealth, HIS implementation, advanced telemedicine technologies, and contextual factors influencing telemedicine adoption.Moreover, the temporal analysis underscores the evolution of research priorities over time, reflecting shifts in technological advancements and emerging healthcare challenges.The identification of highly cited papers and author collaboration networks further elucidates seminal contributions and key research clusters within the field.Overall, this analysis not only contributes to a deeper understanding of the current state of HIS and Telemedicine research but also informs future directions for advancing healthcare technology and delivery on a global scale.

( 1 )
Identify the key thematic areas and research trends within Health Information Systems and Telemedicine.(2) Analyze the publication output, citation patterns, and collaboration networks among researchers and institutions.(3) Investigate the influence of technological advancements, policy frameworks, and socioeconomic factors on the evolution of HIS and Telemedicine research.

Figure 1 .
Figure 1.Thematical Network Analysis Source: Data Analysis Result, 2024 In this network, each node (the colored rectangle) represents a key term or concept, and the lines between them indicate the strength of the relationship or association between these terms.The thickness of the lines might signify the frequency of association or the strength of the relationships in the underlying data (e.g., the number of times two terms appear together in literature).The visualization also seems to involve a color-coding scheme to group related terms into clusters, suggesting thematic clusterization.This is often done to show how different terms or concepts are grouped together in the literature, indicating different themes or focal areas of research.1. Red Cluster: This seems to focus on telehealth, particularly in the context of COVID.It includes terms like 'problem', 'lesson', 'experience', 'cloud', and 'China', suggesting a discussion of the challenges and

4 .
Turquoise Cluster: This cluster seems to be about the broader contextual factors influencing telemedicine, with 'context', 'future', and 'routine health information sys' highlighted.It may address the future prospects of telemedicine and the routine use of health information systems.

Figure 2 .
Figure 2. Overlay Visualization Source: Data Analysis Result, 2024 This network visualization includes a color gradient at the bottom, which typically represents the time dimension in bibliometric analyses, with colors transitioning from one hue to another over time.The gradient goes from purple (around 2010) to yellow (around 2016), suggesting that the colors of the nodes (terms) may correspond to the years in which they were most prominent in the literature.1. Purple Nodes (circa 2010): The terms with a purple tint are likely those that were more prominent or emerged around 2010.In the image, these might be terms at the edge of the network that are harder to read.However, if there were clear purple nodes, they would indicate the starting points or the early focus areas of the research captured by the dataset.2. Blue Nodes (circa 2012): The terms that are in shades of blue might represent the focal points of research around 2012.They could indicate a shift from the earlier themes or an