3.2.2 Visualization of hot topics evolution

To explore the degree of concern of the international E-health research, we divided it into three periods: from 2001 to 2005, 2006 to 2010, and 2011 to 2016. The frequency of keywords has been counted as shown in Table 5. Similar to the above method, we get the visualization maps of keywords in different times, as shown in Figures 6–8.

In Atlas of visualization, the three stages of topics evolution show a gradual trend of convergence. In 2001–2005, the link intensity among high-frequency keywords was low. The study of E-health was at an exploratory stage, and research direction is scattered as scholars had not yet formed a complete theoretical system. With the emergence of E-health concepts raising academic great interest, scholars considered using network communication technology can greatly improve the quality of medical service and reduce healthcare costs. However, they also doubted whether it determined the actual role, which focused them on the theoretical exploration and the possibility of assessment of E-health [45, 52–54]. In 2006–2010, with the Internet explosively developing and governments attaching more importance to E-health gradually, some medical items based on network technology entered the implementation phase. Scholars tried to evaluate implementation of these projects from visual map aspects. The formation of E-health research prototype has an important connection with the Internet, telemedicine, and care.


### Table 5.

Frequency of keywords in different periods.

### Figure 6. Visualization of hot topics in 2001–2005.

Scholars thought that the core was the Internet, telemedicine, and care. This provided a point of reference standard for future research directions and reduced misuse and abuse of the concept [44, 55–58]. In 2011–2016, visual maps showed that the core keywords were still the Internet, telemedicine, and care. The map of central tendency is obvious but there had been significant changes. M-health, system management, and randomized controlled trial suddenly broke out, which respectively reflected three characteristics of E-health research: mobile, systematic, and precision. The popularity of mobile and wearable devices greatly accelerated the development process of E-health. Systematic management of the healthcare system can effectively improve the quality of medical services. Precision means

researchers used random control experiments and other scientific methods to assess E-health to obtain scientific outputs [59, 60]. In addition, the keyword "big data" began to appear in the knowledge map, indicating that scholars began to study the application of health data technology to promote E-health-related research projects. Application of big data technology can help solve the problem that medical field

Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016)

DOI: http://dx.doi.org/10.5772/intechopen.88610

data volume, various, and grows rapidly to deal with.

Figure 7.

Figure 8.

77

Visualization of hot topics in 2011–2016.

Visualization of hot topics in 2006–2010.

Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016) DOI: http://dx.doi.org/10.5772/intechopen.88610

Figure 7. Visualization of hot topics in 2006–2010.

### Figure 8. Visualization of hot topics in 2011–2016.

researchers used random control experiments and other scientific methods to assess E-health to obtain scientific outputs [59, 60]. In addition, the keyword "big data" began to appear in the knowledge map, indicating that scholars began to study the application of health data technology to promote E-health-related research projects. Application of big data technology can help solve the problem that medical field data volume, various, and grows rapidly to deal with.

Scholars thought that the core was the Internet, telemedicine, and care. This provided a point of reference standard for future research directions and reduced misuse and abuse of the concept [44, 55–58]. In 2011–2016, visual maps showed that the core keywords were still the Internet, telemedicine, and care. The map of central tendency is obvious but there had been significant changes. M-health, system management, and randomized controlled trial suddenly broke out, which respectively reflected three characteristics of E-health research: mobile, systematic, and precision. The popularity of mobile and wearable devices greatly accelerated the development process of E-health. Systematic management of the healthcare system can effectively improve the quality of medical services. Precision means

2001–2005 2006–2010 2011–2016

System 18 Information 73 Randomized controlled

Information technology

Scientometrics Recent Advances

Frequency of keywords in different periods.

Table 5.

Figure 6.

76

Visualization of hot topics in 2001–2005.

Care 16 System 71 Intervention 281 Health information 10 Telehealth 59 Technology 278 Quality 10 Quality 51 M-health 251 Education 9 Technology 48 System 247

Management 7 Healthcare 47 Health 204

8 Health 47 Telehealth 213

Keywords Frequency Keywords Frequency Keywords Frequency Telemedicine 39 Telemedicine 163 Internet 440 Internet 37 Internet 151 Care 416 Information 20 Care 92 Telemedicine 416

trial

323

The evolution of topics in Figures 6–8 and Table 5 can be divided into several classes: continuous topics, emerging topics, and disappearing topics.

computers working upon distributed systems that provide service in real time over a network. Cloud computing is massively scalable which provides a superior user experience and is characterized by new Internet-driven economics [65]. Once established a unified exchange standard is used to do real-time exchange; the amount of data analyzer will face is enormous, so using cloud computing technolo-

Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016)

Nonetheless, studies regarding information security, privacy, and IT policies had

The concept of research frontier was introduced by Price. It is used to describe a trend in the field of research. Price uses his own definition of indicators and watches the trends of the article citations according to these indicators [66]. Research frontier is a dynamic concept. The cited articles containing the contents of research front are the knowledge base, and research front is based on these articles. Emergence refers to the rate of change of cited frequency, which can be considered that the content of some emergent literature is discussed form research frontiers. To detect research frontier, we need to analyze the content of citing articles, burst words, and burst literature. CiteSpace provide us a method—Citing articles Cluster, which is the base of identifying clustering-edge [67]. By doing content analysis and clustering, according to Visual analysis results CiteSpace outputted, we can deter-

We do co-citation network process, get burst information of literature, and use the burstness at the right of the software to view the strength of emergent literature

The first column in Figure 6 indicates cited emergent literature and strength, representing emergent index. The higher the index is, the more focused cited literature is. The right place in the figure indicates the time literature emergence.

gies to process these data would be a satisfactory solution.

mine the forefront of research in the field of E-health research.

decreased gradually in these three periods.

DOI: http://dx.doi.org/10.5772/intechopen.88610

and emergent time distribution (Figure 9).

Figure 9.

79

Document co-citation bursting statistical chart.

3.3 Research frontier analysis

Continuous topics: telemedicine, Internet technology, and care are continuous academic focus of research topics. From the point of view of clusters each year, telemedicine, Internet technology, and care focus on different research topics in the last decade. The main direction of telemedicine research is to determine the initial authoritative definition and unify communication standard [61].The aim of midterm is to assess the effect of the recent literature, and the aim of recent time is to review telemedicine research from the perspective of human society. Internet technology which functioned as support of the development of E-health technology in recent years has undergone tremendous changes. Scholars began to explore the possibility of using a network to pass health information, using network storage to transfer data, and analyzing the advantages and disadvantages of doing so. Then, they gradually changed to focus on the user network information literacy and healthy relationship, which pointed out that information literacy is to enhance users' ability to understand E-health for further development [62]. Electronic health records are the most direct and most important solutions for problems such as how to build a unified specification and how to help different medical workers when they cannot communicate directly. Research focus gradually changed the use of electronic health record information, medical research, and health information so that they maximize the effectiveness of change.

Emerging topics, including health technology, information literacy, and cloud computing, have developed rapidly in a few years. Relatively speaking, mobile health technology and information literacy were at the heart of co-occurrence analysis in recent years. Improvements of the Internet and other information technologies and increasing researchers' knowledge promote the application of Ehealth. Earlier E-health applications and services are based on computer terminals, but portable monitor cannot do that with the advances in mobile technology in recent years. Thus, the use of mobile devices in health and disease management or monitoring the user's health condition has attracted great concern [63]. In previous studies, researchers found that different users get different abilities to accept the electronic health information, which has significant impact on the development of E-health. Therefore, some scholars have done some research in information literacy [64].

Cloud computing is an emerging technology based on Internet computing in which shared resources are provided on the Internet to other users on demand. Basically, cloud is a synonym for the Internet and composed of clusters of


Table 6. Document bursting information. Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016) DOI: http://dx.doi.org/10.5772/intechopen.88610

computers working upon distributed systems that provide service in real time over a network. Cloud computing is massively scalable which provides a superior user experience and is characterized by new Internet-driven economics [65]. Once established a unified exchange standard is used to do real-time exchange; the amount of data analyzer will face is enormous, so using cloud computing technologies to process these data would be a satisfactory solution.

Nonetheless, studies regarding information security, privacy, and IT policies had decreased gradually in these three periods.

### 3.3 Research frontier analysis

The evolution of topics in Figures 6–8 and Table 5 can be divided into several

Continuous topics: telemedicine, Internet technology, and care are continuous academic focus of research topics. From the point of view of clusters each year, telemedicine, Internet technology, and care focus on different research topics in the last decade. The main direction of telemedicine research is to determine the initial authoritative definition and unify communication standard [61].The aim of midterm is to assess the effect of the recent literature, and the aim of recent time is to review telemedicine research from the perspective of human society. Internet technology which functioned as support of the development of E-health technology in recent years has undergone tremendous changes. Scholars began to explore the possibility of using a network to pass health information, using network storage to transfer data, and analyzing the advantages and disadvantages of doing so. Then, they gradually changed to focus on the user network information literacy and healthy relationship, which pointed out that information literacy is to enhance users' ability to understand E-health for further development [62]. Electronic health records are the most direct and most important solutions for problems such as how to build a unified specification and how to help different medical workers when they cannot communicate directly. Research focus gradually changed the use of electronic health record information, medical research, and health information so

Emerging topics, including health technology, information literacy, and cloud computing, have developed rapidly in a few years. Relatively speaking, mobile health technology and information literacy were at the heart of co-occurrence analysis in recent years. Improvements of the Internet and other information technologies and increasing researchers' knowledge promote the application of Ehealth. Earlier E-health applications and services are based on computer terminals, but portable monitor cannot do that with the advances in mobile technology in recent years. Thus, the use of mobile devices in health and disease management or monitoring the user's health condition has attracted great concern [63]. In previous studies, researchers found that different users get different abilities to accept the electronic health information, which has significant impact on the development of E-health. Therefore, some scholars have done some research in information

Cloud computing is an emerging technology based on Internet computing in which shared resources are provided on the Internet to other users on demand. Basically, cloud is a synonym for the Internet and composed of clusters of

Frequency Burst Author Year Title Journal source

15 9.40 Donkin L 2011 "A systematic review of the impact of

20 8.42 Mair FS 2012 "Factors that promote or inhibit the

2011 "A holistic framework to improve the uptake and impact of eHealth technologies"

> adherence on the effectiveness of etherapies"

implementation of E-health system: an explanatory systematic review"

Journal of Medical Internet Research

Journal of Medical Internet Research

Patient Education and Counseling

classes: continuous topics, emerging topics, and disappearing topics.

Scientometrics Recent Advances

that they maximize the effectiveness of change.

literacy [64].

Table 6.

78

17 9.52 van

Document bursting information.

Gemert-Pijnen JEWC

The concept of research frontier was introduced by Price. It is used to describe a trend in the field of research. Price uses his own definition of indicators and watches the trends of the article citations according to these indicators [66]. Research frontier is a dynamic concept. The cited articles containing the contents of research front are the knowledge base, and research front is based on these articles. Emergence refers to the rate of change of cited frequency, which can be considered that the content of some emergent literature is discussed form research frontiers. To detect research frontier, we need to analyze the content of citing articles, burst words, and burst literature. CiteSpace provide us a method—Citing articles Cluster, which is the base of identifying clustering-edge [67]. By doing content analysis and clustering, according to Visual analysis results CiteSpace outputted, we can determine the forefront of research in the field of E-health research.

We do co-citation network process, get burst information of literature, and use the burstness at the right of the software to view the strength of emergent literature and emergent time distribution (Figure 9).

The first column in Figure 6 indicates cited emergent literature and strength, representing emergent index. The higher the index is, the more focused cited literature is. The right place in the figure indicates the time literature emergence.


### Figure 9.

Document co-citation bursting statistical chart.

## Scientometrics Recent Advances

The red part of the document is the period when cited rate raised most rapidly. At this stage, literature based on these knowledge bases is a research frontier. Drawing keywords co-occurrence network map combined with these citing articles can help identify research frontier.

framework to study the cost–benefit of Internet technology in the medical field has

According to the high-frequency keywords and keyword co-occurrence clustering results (Figure 11), we can find high-frequency keywords named "randomized controlled trial," "adherence," "Internet," "depression," "intervention," "mental health," and "stress management." Scholars have studied methods to enhance patient attachment and loyalty to E-health technologies, including the use of network health technologies and mobile technology to manage the patient's physical and mental health, by increasing the degree of interaction between patients and electronic health technology to improve the patient's sense of e-therapy. In other words, making patients trust in e-therapy is a problem that needed to be solved. "Factors that promote or inhibit the implementation of E-health system: an explanatory systematic review" is an article aimed to review the literature on the implementation of E-health to identify barriers and facilitators to E-health implementation and outstanding gaps in research on the subject. Mair published this review, and he found some interesting results: (1) work directed at making sense of E-health systems, specifying their purposes and benefits, establishing their value to users, and planning their implementation, (2) factors promoting or inhibiting engagement and participation, (3) effects on roles and responsibilities, (4) risk management, and (5) ways in which implementation processes might be

reconfigured by user-produced knowledge [68]. He thought the published literature

Emergent literature of the cluster is "A systematic review of the impact of adherence on the effectiveness of e-therapies." This article reviewed the development of electronic treatment and the impact patient compliance has on treatment effect. It assessed factors that affect patient compliance and listed ways to improve electronic treatment and then concluded that electronic treatment was lacking in effective treatment of electronic protocols. Due to remote treatment, the patient was easier to be influenced by external factors. Further studies are needed to establish consensus compliance measurement program and understand the factors

Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016)

become a trend in the future.

DOI: http://dx.doi.org/10.5772/intechopen.88610

affected by compliance.

Figure 11.

81

Keyword-based clustering co-occurrence patterns.

Figure 8 shows the results of literature whose mutation time has been covered at least in the past 3 years and three documents were chosen which have the highest intensity of mutation (Table 6). Then we retrieved Web of Science for citing articles and conducted keyword cluster analysis and word frequency statistics. Combined with automatic identification function, we drew a cluster map of article citations, interpreted three key documents' citing document clustering and word frequency comprehensively, and did qualitative analysis of E-health academic field frontier research.

"A holistic framework to improve the uptake and impact of E-health technologies" is an article published by van Gemert-Pijinen Pewc in 2011. He found that a lot of E-health technologies were not appropriate for health services, the effect of which did not match people's expectation. After careful study, he believed that it was because developers ignored the dependencies among technologies, human characteristics, and environmental impact. Thus, he proposed a frame based on many scholars'studies to improve the quality of health services. Under such unity frame's guidance, E-health technology can be combined with the health sector better, but it needs more empirical support [18].

Based on high-frequency statistics and keyword co-occurrence cluster time-zone views (Figure 10), we can find high-frequency keywords including "intervention," "randomized controlled trial," "technology," "framework," "physical activity," and "self-management." Researchers use different research methods to compare the actual effects of E-health and then make reasonable predictions about the future of these applications, such as Van's framework [8]. Then the cost of applying emerging technologies in the medical field is reduced. Using a reasonable evaluation

Figure 10. Keyword-based clustering co-occurrence patterns.

## Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016) DOI: http://dx.doi.org/10.5772/intechopen.88610

framework to study the cost–benefit of Internet technology in the medical field has become a trend in the future.

Emergent literature of the cluster is "A systematic review of the impact of adherence on the effectiveness of e-therapies." This article reviewed the development of electronic treatment and the impact patient compliance has on treatment effect. It assessed factors that affect patient compliance and listed ways to improve electronic treatment and then concluded that electronic treatment was lacking in effective treatment of electronic protocols. Due to remote treatment, the patient was easier to be influenced by external factors. Further studies are needed to establish consensus compliance measurement program and understand the factors affected by compliance.

According to the high-frequency keywords and keyword co-occurrence clustering results (Figure 11), we can find high-frequency keywords named "randomized controlled trial," "adherence," "Internet," "depression," "intervention," "mental health," and "stress management." Scholars have studied methods to enhance patient attachment and loyalty to E-health technologies, including the use of network health technologies and mobile technology to manage the patient's physical and mental health, by increasing the degree of interaction between patients and electronic health technology to improve the patient's sense of e-therapy. In other words, making patients trust in e-therapy is a problem that needed to be solved.

"Factors that promote or inhibit the implementation of E-health system: an explanatory systematic review" is an article aimed to review the literature on the implementation of E-health to identify barriers and facilitators to E-health implementation and outstanding gaps in research on the subject. Mair published this review, and he found some interesting results: (1) work directed at making sense of E-health systems, specifying their purposes and benefits, establishing their value to users, and planning their implementation, (2) factors promoting or inhibiting engagement and participation, (3) effects on roles and responsibilities, (4) risk management, and (5) ways in which implementation processes might be reconfigured by user-produced knowledge [68]. He thought the published literature

Figure 11. Keyword-based clustering co-occurrence patterns.

The red part of the document is the period when cited rate raised most rapidly. At this stage, literature based on these knowledge bases is a research frontier. Drawing keywords co-occurrence network map combined with these citing articles can help

Figure 8 shows the results of literature whose mutation time has been covered at least in the past 3 years and three documents were chosen which have the highest intensity of mutation (Table 6). Then we retrieved Web of Science for citing articles and conducted keyword cluster analysis and word frequency statistics. Combined with automatic identification function, we drew a cluster map of article citations, interpreted three key documents' citing document clustering and word frequency comprehensively, and did qualitative analysis of E-health academic field

"A holistic framework to improve the uptake and impact of E-health technologies" is an article published by van Gemert-Pijinen Pewc in 2011. He found that a lot of E-health technologies were not appropriate for health services, the effect of which did not match people's expectation. After careful study, he believed that it was because developers ignored the dependencies among technologies, human characteristics, and environmental impact. Thus, he proposed a frame based on many scholars'studies to improve the quality of health services. Under such unity frame's guidance, E-health technology can be combined with the health sector

Based on high-frequency statistics and keyword co-occurrence cluster time-zone views (Figure 10), we can find high-frequency keywords including "intervention," "randomized controlled trial," "technology," "framework," "physical activity," and "self-management." Researchers use different research methods to compare the actual effects of E-health and then make reasonable predictions about the future of these applications, such as Van's framework [8]. Then the cost of applying emerging technologies in the medical field is reduced. Using a reasonable evaluation

identify research frontier.

Scientometrics Recent Advances

frontier research.

Figure 10.

80

Keyword-based clustering co-occurrence patterns.

better, but it needs more empirical support [18].

although many of us think E-health is better than traditional treatment methods, governments operating E-health system decreased in number [75]. In view of that, we seek evidence that could help us find the reason. Since research about E-health has come into a new stage, technologies have already reached the demand, and governments are also positive that designing a complete E-health system is a top priority. Unfortunately, no one has satisfied the requirement [76]. A sustainable system need to be operated for a long time, so we need to take cost and profit into consideration. But we found that most of the research or surveys neglected these and they just concentrated on realizing E-health system [77–79]. On this occasion,

Detection and Characterization of E-Health Research: A Bibliometrics (2001–2016)

how to reduce cost and profit will be the center of most scholars'study.

The E-health has been one of continued research focuses on the study of many academics, and the majority of scholars tended to publish papers to show their achievements. Annually published papers have reached 900 in 2015 and 2016,

There was a gap between China and some developed countries in the researches

There were many institutions and authors working on this field. Among them, the number of authors who published at least one paper was 3770. On the one hand, it indicated that many scholars paid attention to E-health research from 2001 to 2016. On the other hand, there was great potential to improve the cooperation of authors, because the present relationships were not close which was revealed from the visualization map. Therefore, it is important to improve the allocation ability of resources and form cooperation network, so that we can deepen and improve the

Global E-health research focused on five topics ("Internet technology," "telemedicine," "E-health intervention on healthcare," "health system," and "personal health management"). With the development of information technology, E-health has been absorbing and applying emerging information technologies and applications. Among them, the application of the sophisticated cloud computing technology and big data are typical examples. Cloud computing is an emerging technology for Internet and composed of cluster of computers working upon distributed system that provide service in real time over a network. According to the definition by NIST, cloud computing is "a model that can provide distributed, rapidly provisioned and configurable computing resources" [78, 79]. Big Data in healthcare is concerned with meaningful datasets that are too large, too fast, and too complex for healthcare providers to process and interpret with existing tools. The application of big data technology can help solve the problem that medical field data is volume,

In addition, E-health has been a research focus of many counties over the world early in the twenty-first century. In detail, Internet, telemedicine, and health care became the focus in 2006. However, m-health, system management, and experimental intervention began to form the new study hot-spots, especially the commercialization of E-health from 2011. Therefore, scholars tended to set up a new E-health system so that we can improve the efficiency of health care and monitor people's health level in the distance and profit by developing E-health business.

of E-health. For instance, the USA, the UK, and Australia were the top three countries that published many articles. The impact of the UK was bigger than the USA according to the centrality index. The published quantity of references in China was not up to 1/6 of the USA and 1/3 of the UK. The time when China became

to have centrality was 2004 which was later than most developed countries.

4. Discussion and conclusion

DOI: http://dx.doi.org/10.5772/intechopen.88610

which is a pretty substantial number.

development of E-health.

83

various, and it grows too rapidly to deal with.

Figure 12. Keyword-based clustering co-occurrence patterns.

focused on organizational issues and neglected the wider social framework which must be considered when introducing modern technologies.

Implementation, system, healthcare, normalization process theory, qualitative research, meaningful use, and impact are high-frequency keywords. The scholars who cite the article are concerned about the role and responsibility of electronic health in the medical process, risk management, ways to engage with professions, and how to ensure the potential benefits of new technologies (Figure 12). Mcevoy Rachel studies using the normalization process theory to research implementation process [69]. Deborah studies the role of digital technologies in self-management [70]. Jane does an organizational analysis of the implementation of telehealth in view of whole systems [71]. Scholars are also concerned about factors having impact on E-health applications, whether they are positive factors or obstacles [72–74]. With the increase of E-health project numbers, these areas deserved more empirical investigation and have been research frontiers, such as the ways to identify and anticipate how E-health services will impact everyday clinical practice, how new Ehealth services will affect clinical interactions and performance of clinical work, and the effects of different methods of engaging with professionals before and during the implementation of E-health.
