1. Introduction
Digital change has been particularly challenging in healthcare, as there is growing demand for services due to the aging population and the emergence of new diseases. Thus, investment in new treatments is necessary so that everyone has equal access to the healthcare system [1,2,3]. E-health involves practices such as mhealth and telehealth that employ electronic technologies to provide healthcare resources, services, and information [4].
Mobile health or mhealth consists of the use of mobile devices so that patients can solicit services electronically, use apps to verify information, and manage or monitor treatment or problems or other health-related issues [5]. Telehealth can be defined as the use of telecommunication technologies to promote the care and education of patients and professionals working in the area [6].
E-health has become an integral part of the healthcare system as it addresses a range of difficulties in medicine, including reducing errors and providing more efficient services with more accurate results [7]. Such is the case with the use of electronic medical records, in which all information about a patient is stored, thus preventing inappropriate administration of medication during medical care and ensuring that the patient is treated quickly and comfortably [8]. However, its implementation depends on adequate planning and strategies so that virtual medical care can be performed [3].
The success of e-health in a country is related to several factors, including user acceptance and the types of infrastructure, systems, and management used [6,9]. Meanwhile, there are four stakeholders involved in the outcomes: entrepreneurs, healthcare professionals, patients, and those responsible for health insurance and assistance policies [10]. To effectively implement the use of information technologies in healthcare, e-health strategies must occur in an integrated manner, including the development of norms, laws, or regulations. This situation is valid whether in the fields of telehealth and mhealth, or specific categories such as electronic medical records or health literacy—eLearning (learning in health) [5,11,12].
The e-health strategy has three main components: (i) knowledge management; (ii) tools and methods; and (iii) policies. These components work to consolidate healthcare systems with support networks and scientific and technological production, manage infrastructure and human resources, reduce barriers to accessing health services, and promote community inclusion [13]. Some barriers to e-health include the difficulties faced when using systems and applications, both by healthcare professionals and patients, as well as ensuring the security and privacy of user data transmitted throughout these systems [12].
Another challenge in e-health is interoperability across systems. That is, new e-health systems must interact with existing ones, and there should be a standard electronic language between hospitals (or clinics) to facilitate communication and data exchange, as well as formal agreements on how the system should work in a standardized way [14,15]. Further, the cost of implementing e-health also presents challenges, which may make the implementation of such systems unfeasible. This is related to the high levels of investment required to purchase equipment to implement more sustainable practices [3,16] than traditional systems that store paper records, alongside the costs of hiring specialized support personnel in information technology (IT) to keep the systems running and software acquisition [8,17].
There are several studies on the topic of e-health, but they generally address a specific practice. One example is [18], in which the authors analyze studies of interventions via e-health using websites and social media in the treatment of patients with mood disorders. Two e-health-related studies with a general approach were found [19,20]. However, such studies do not fully address all e-health practices, which differentiates the present study from previous work on the topic. Although scientific publication databases have a vast range of studies on e-health [21], there are gaps in knowledge related to this topic, which justifies the need for the present review. Herein, we update data related to practices in the field of e-health and provide an overview of the information present in selected articles within a five-year time frame (2014 to 2019), demonstrating what has been published on the topic both in practical studies and literature reviews.
Therefore, the objective of this analysis is to identify, through a systematic literature review, the most commonly used e-health practices worldwide, as well as the key services provided, diseases treated, and the associated technologies that assist in providing e-health practices. This study aims to answer the following questions:
In which countries and journals are studies published on e-health practices?
What are the main e-health practices used worldwide?
What are the main service delivery types and medical fields addressed using e-health?
What are the main barriers to e-health service delivery?
What are the most common diseases treated, and in which countries have e-health practices been applied?
What are the most common technologies used in e-health?
2. Materials and Methods
The identification of the study portfolio was carried out using the Methodi Ordinatio process developed [22] and based on the Cochrane model and ProKnow-C for research studies that use Information and Communication Technologies—ICTs, such as spreadsheets, word processors, and reference managers. The following software programs were employed to conduct the analyses: Mendeley version 1.19.3; JabRef version 3.3; Microsoft Office 365 (Excel and Word); and NVivo trial version 11 for initial article analysis. The Methodi Ordinatio includes nine steps and is used to conduct systematic literature reviews, build bibliographic portfolios, and map the literature on a specific topic. One advantage of the methodology is its multi-criteria decision-making model that considers the impact factor of the journal, the number of citations, and the year of publication. From this, the InOrdinatio index is calculated, and the researcher obtains a bibliographic portfolio [23]. This methodology has been used by authors such as [24,25,26].
The Methodi Ordinatio is shown in Figure 1 and is composed of the following steps:
Step 1—Establish the research objective;
Step 2—Define the keywords;
Step 3—Select the databases to be searched;
Step 4—Search for and register the results obtained;
Step 5—Define search filters such as publication period and type of study (articles, books, etc.), excluding duplicate articles and those unrelated to the selected research topic;
Step 6—Identify the impact factor, year of publication, and number of citations of the articles from Google Scholar for the selected portfolio;
Step 7—Apply the InOrdinatio equation [22] in a spreadsheet to classify the identified articles;
(1)
The equation is composed of the following variables: IF is the impact factor; α is the value defined by the researchers considering the current relevance of the articles, which may vary from 1 to 10 (for this study, we defined α as 10); ResearchYear is the year the research was conducted; PublishYear is the year the article was published; and ∑Ci is the number of citations of the article according to data from Google Scholar.Step 8—Select the articles for the final portfolio considering the highest InOrdinatio classification; and
Step 9—Read and analyze the final portfolio articles.
First, the search objective was defined, and the keywords were searched using Boolean operators (“E-Health” OR “EHealth” AND “Practice *”). The keyword “Technology” was not used to search the databases so as not to excessively limit the search. The analysis of e-health-related technologies took place after the portfolio was defined.
The search was carried out using seven electronic databases: Lilacs, MedLine, PubMed, SciELO, Scopus, Science Direct, and Web of Science. These databases were chosen due to the multidisciplinary character of this study and the fact that the information concerning medicine and health is vast. Thus, to conduct a careful analysis, well-known and key sources in the field should be used, such as MedLine, PubMed, Lilacs, SciELO, the Cochrane Library, and the Virtual Health Library (VHL).
MedLine is a database containing supplementary materials and offers a good basis for research as it indexes other databases and aggregates complementary materials. It has been employed in research on e-health, health, and medical technology [6].
Scopus is the largest research database for the fields of technology, medicine, science, social sciences, and the arts and humanities, while Science Direct contains technical publications in the fields of science and health [27]. The Web of Science is an independent global citation database that offers reliable multidisciplinary data for academic research [28].
The time frame for the published research was five years, from 2014 to 2019. According to [29], a five-year period is the half-life for article citations. In addition, the following filtering procedures were applied to the databases to obtain the results: selection of types of articles published (review, research, and journal-published), exclusion of duplicate articles. Thus, 3136 articles were obtained, whose titles, abstracts and keywords were read to exclude studies that dealt with areas unrelated to e-health practices and are beyond the scope of this analysis.
Finally, the Methodi Ordinatio equation was applied to obtain the most currently relevant articles. Articles with an index greater than 100 were considered, and one study was excluded as it was not found, resulting in a final portfolio of 446 articles, as listed in Appendix A—Table A1. Final portfolio.
The database search did not exclude any publication language, aiming to obtain a broad range of results and not limit the present analyses. Table 1 shows how the studies were analyzed to answer the research questions.
The questions referring to countries that are publishing studies on e-health and countries that use these practices were answered, respectively, by identifying the country of the first author and where the studies took place. Thus, the results and discussions of the research were organized in a bibliometric and content analysis carried out on the 446 articles from the final portfolio. For the content analysis of the technologies associated with e-health, 57 articles from the final portfolio (446 articles) were analyzed as they specifically address this topic.
3. Results and Discussion
3.1. Bibliometric Analysis
Figure 2 shows the number of publications per year from 2014 to 2019.
We can see that 2014 had the lowest number of publications on the topic and 2019 the highest. There was fluctuation in the number of publications, particularly between 2018 and 2019, when a marked increase in the number of studies related to the theme of e-health occurred. This increase is related to several factors. The area of mhealth has been growing, as has the number of chronic diseases and other health problems, while the advance of mobile technology has enabled greater access to e-health through devices, enabling an increase in research [30]. An increase in publication on the topic is also due to researcher interest, as it is current and still novel, allowing for greater numbers of studies on topics within the field, as is the case with reports published about e-health indicators, such as those from the Global Health Observatory of the World Health Organization (WHO) and the Nordic e-Health Research Network [31].
Although authors from 58 countries contributed to studies, the geographical distribution was uneven, as shown in Figure 3.
The leading countries in developing research related to e-health are United States (109), Australia (41), United Kingdom (32), China (23), Italy (19), Germany (18), Norway (14), and France (10). The countries with the fewest publication include Egypt (1), Mexico (2), and Brazil (3). In the study by [32] on e-health and health informatics skills, the authors found that the countries with the most authors who published on the topic were United States, Canada, United Kingdom, and Australia, and those with the least were Denmark and Norway.
Norway, Australia, Germany, the United Kingdom, United States, France, and Italy are countries with a remarkably high Human Development Index—HDI (which is based on the health, life expectancy, education, and income of a country’s population), while Egypt, Brazil, Mexico, and China are countries with high HDI. The wealthier a country is, the better its economic, political, and healthcare infrastructure, enabling more initiatives for e-health development, as has occurred in many European countries [33,34]. Each country has a different level of e-health development, and consequently, countries with more advanced e-health systems have a higher incidence of scientific production on the topic, such as European countries and the United States, as verified by [35]. Moreover, [36] state that although countries on the African continent and Latin America are publishing on the topic, the number of studies is still low as the countries have less developed e-health systems. Such is the case with Brazil and Mexico, which are still at the stage of telehealth improvement and consolidation.
The 446 articles in the portfolio were published across 253 academic journals. However, some journals among those identified stand out for having very few publications on the topic but a high impact factor, such as The Lancet (1 publication—60.392 JCR); British Medical Journal—BMJ (1 publication—30.223 JCR); IEEE Communications Surveys & Tutorials (1 publication—23.700 JCR); IEEE Internet of Things Journal (2 publications—9.936 JCR); Schizophrenia Bulletin (2 publications—7.958 JCR); Information Sciences (2 publications—5.910 JCR); AIDS and Behavior (3 publications—3.147 JCR); Social Science & Medicine (3 publications—3.616 JCR); International Journal of Environmental Research and Public Health (3 publications—2.849 JCR); Journal of the American Medical Informatics Association—JAMIA (4 publications—4.112 JCR); Frontiers in Psychiatry (4 publications—2.849 JCR); PLoS One (4 publications—2.740 JCR).
In the analysis by [19], who conducted a literature review on e-health, and [32], who did a bibliometric study, the journals that had the most publications were Journal of Medical Internet Research and Telemedicine and e-Health.
Therefore, for the research question “In which country and journals are studies on e-health practices published worldwide?” we can see that the United States stands out as it has the greatest number of authors who published on this topic, with 109 studies. Moreover, the Journal of Medical Internet Research is the most prominent scientific outlet for research on e-health, with 47 publications.
3.2. Content Analysis
3.2.1. Main E-Health Service Delivery Types and Fields
Based on the survey of studies from the final portfolio, Table 2 presents the categories of practices and services provided in e-health as described in the analyzed studies.
When answering the research question “What are the most common e-health practices used around the world?” four categories of e-health practices became evident: (i) mhealth or mobile health; (ii) telehealth or telemedicine; (iii) technology; and (iv) others, which include combinations of different practices.
E-health can be defined as healthcare services and health information provided and/or obtained using the internet, mobile devices, computers, and information technology [64]. It involves the application of digital solutions for healthcare, thus facilitating patient care in a more comfortable way [62]. The practice areas are described below.
Mhealth or mobile health enables persons who use mobile devices, such as smartphones, to access systems, data, and apps to monitor and manage their health status [38]. Telehealth or telemedicine includes remote consultations via videoconference/call using desktop computers, smartphones, or tablets with internet access [44,67,68].
The technology applied in e-health helps healthcare professionals, patients, and the lay population to obtain information or access learning, treatment, and resources that are available online [69].
Through e-health, digital health interventions (DHIs), such as assisted therapy, have been shown as effective among children and young people undergoing mental health treatment, as discussed in the systematic review by [64] on randomized clinical trials of DHIs performed with children and young people up to 25 years of age. However, further data are required to offer satisfactory conclusions about the benefits; despite the potential that the intervention can offer, few studies have been carried out on the subject and with small sample sizes, making this assessment difficult.
In an analysis by [62], the authors evaluated the effectiveness of an electronic health project model for people with severe mental illness (SMI), called the Flat Explicit Design Model (FEDM). The study was carried out via a website with 38 people aged 31 to 59 years who have some degree of severe mental illness and involved online tests.
We also identified a study that sought to conduct a theoretical review on the services and applications offered in the practice of mhealth and their use for therapy in the areas of mental health and behavioral disorders, musculoskeletal and connective tissue systems, oncology, and the nervous system [38]. Another study assessed the skills of medical residents, doctors, and clinics working with telepsychiatry, with a focus on e-mental health (e-MH) care [44].
In the “other” category, articles describing a combination of past practices and other areas, such as costs, were included. The study by [56] assessed the current literature to verify whether specialization in telehealth offset the effective cost. The authors found specializations such as teledermatology, teleophthalmology, and telecardiology offset the amount invested in that healthcare service.
Some of the service delivery types and other themes combined with the most representative e-health practices in the literature are discussed below.
Health literacy is knowledge and skills related to health, and it can be obtained through in-person and/or online environments [70]. The latter includes websites, social media, and the use of health data systems [71]. An aspect related to this area in the analyzed studies is low health literacy, as seen in the studies by [72,73]; when searching for health information, internet users must use a critical approach to determine if the information obtained is correct. Often, the information posted online is presented erroneously, which may misguide or misinform the user about the content.
Mhealth or mobile health and monitoring consists of using smartphone applications to help in disease treatment, identification, and support [74]. It also encompasses health exam scheduling and patient monitoring performed via devices with wireless sensors that check essential vital signs, such as blood glucose level and blood pressure [38]. The results of these exams are stored on the device, thus allowing for the transmission of data from exams done at home [75].
In telehealth, when an intervention is combined with interaction with a healthcare professional, it can be defined as telemonitoring of patients with diseases that need follow-up [43]. This enables doctors to see patients without having to go to the hospital or doctor’s office [45]. Such a service delivery can be employed with mental health patients who require therapy [44], enabling them to participate in sessions at home at more flexible times [76]. It can also be used to monitor the symptoms of cancer patients undergoing treatment [77].
The systems related to the category “technology” entail the creation of encryptions to protect the data of patients who access their medical records online, as well as data protection in the systems of hospitals, pharmacies, and clinics [52,53] so that data remain confidential and secure [54]. Technology also involves creating support for the systems [78] and developing mobile devices that can be used in the healthcare sector, such as wearable sensors [79]. Further, it includes the use of Internet of Things (IoT) [80], cloud storage [81], and Big Data [82] in the areas of e-health.
Regarding the research question “What are the main service delivery types and medical fields served in e-health?” we found that the main areas of service provision are health literacy, mhealth and monitoring, telehealth, and systems combined with technology. In turn, the main medical fields served that are highlighted in the literature are telepsychiatry, teledermatology, telerehabilitation, teleophthalmology, telecardiology, and teledentistry.
As for the research question “What are the main barriers to e-health service delivery?” we found that costs, laws, and system data security of are the main barriers to be overcome. We identified studies related to e-health practices experiencing barriers in terms of costs related to the use of telemedicine [83], regulation and legislation [38], security in the use of cloud computing [84], limitations in clinical trials of existing digital interventions [64], and limitations in databases [58]. In mHealth, a limiting factor is mobile device battery life [85], as the devices with applications or monitoring equipment must have the battery charged to avoid any problems during use [86]. Further, geographic distance is a primary limiting factor, as each country has different health-related applications available to the population [87] and barriers between patient and physician [38].
3.2.2. Main Diseases Treated
Figure 4 shows the main diseases treated in e-health (total and percentage), addressing the research question “What are the most commonly treated diseases and in which countries have e-health services been used?” The most commonly treated diseases are mental illnesses, multiple diseases (diabetes mellitus 1 and 2, stress, depression, and anxiety), cancer, eating disorders, chronic illness, cardiovascular diseases, and sexually transmitted diseases (STDs). Regarding the countries that currently use e-health, we identified the following countries where studies have been conducted: United States, Canada, Australia, Germany, Sub-Saharan Africa, Africa, Netherlands, Sweden, Switzerland, China, Italy, Greece, Finland, Iran, Iraq, Bangladesh, Pakistan, Saudi Arabia, United Kingdom, Spain, France, Italy, and Portugal.
Some of the studies evaluate more than one type of issue, for instance, diabetes mellitus (DM), cardiovascular diseases, and chronic lung diseases [39]; mental illnesses such as depression, anxiety, dementia [76]; others, such as the oral health of pregnant women in prenatal care, anti-smoking, organ transplants [88]; cancer, such as breast cancer, skin cancer, and lung cancer [77]; eating disorders, including care regarding infant nutrition, diabetes, and obesity in adults [75]; chronic illness, such as chronic inflammatory rheumatic diseases (CIRDs), asthma, and chronic pain [10]; cardiovascular diseases [89]; cerebrovascular accident (CVA), coronary artery disease, and atrial fibrillation (AF) [90]; sexually transmitted diseases (STDs), such as HIV and/or sexually transmitted infections (STIs) [50]; human papillomavirus (HPV) and child sexual abuse [91].
Mental illnesses and the studies combining more than one type of disease represented 40% of diseases treated with e-health addressed in the literature. The studies deal mainly with randomized clinical trials applied to groups of people. For example, in the study conducted by [92], the authors verified how a telerehabilitation program works to help control type 2 DM. In the study by [93], a randomized clinical trial (RCT) was carried out with 13 primary brain tumor patients. Using the ReMind App, the pilot study obtained favorable results from patients but still required improvement. On the other hand, [94] observed 66 stroke (CVA) patients and their caregivers for eight weeks, using an e-health system as a treatment aid to do physical exercise. They found no significant effect on patient improvement during that period.
Other authors have chosen to review randomized studies, such as the study by [95], who compared the estimated sizes of combined effects through meta-analyses of analysis of covariance (ANCOVA), simple analysis of change score (SACS), and simple analysis of final values (SAFV), using RCTs of digital interventions with glycated hemoglobin HbA1c as the main result or intervention for disease treatment using e-health practices. Finally, in the study by [96], the use of mhealth for intervention as a form of treatment for patients with hallucinations was investigated.
3.2.3. Technologies Associated with E-Health
From the final portfolio (446 articles), 57 publications were selected that address topics related to technology applied in healthcare. When answering the question “What are the most used technologies in e-health?” we identified IoT, cloud computing, Big Data, security, cryptography, algorithms, among others, as shown in Figure 5.
The technology applied to healthcare includes IoT to integrate medical sensors [80], authenticate, encrypt [97], and maintain security and confidentiality during data exchanges [98] and between physicians and patients [99]. It is vital that users are confident that the systems used are protected [100] and authenticated to ensure the privacy of stored data [51,101]. The cloud system facilitates data storage at a low cost while also being secure and private [42,81,84].
The use of Big Data entails the analysis, diagnosis, and treatment of diseases [82,102]. There is also the use of wireless sensors applied to clothing, which can be used to monitor a patient when performing physical exercise [103,104,105].
The first authors of each of the 57 articles addressing technology in e-health are from 35 different countries, principally China (with 10 articles); India (6 articles); the United States, Australia, and Italy (3 articles each); and Greece, Algeria, Pakistan, and Saudi Arabia (2 articles each). Other countries, such as Spain, South Africa, and Mexico, had only one study. Articles related to technology were published in 38 journals, mainly Future Generation Computer Systems (7 articles); IEEE Access (4); International Journal of Information Management (4); Journal of Medical Systems (3); Computers & Electrical Engineering (2); Health and Technology (2); Information Sciences (1); and Telematics and Informatics (1). In the literature review by [106] on the application of cloud computing in e-health, 44 studies published between 2010 and 2013 were analyzed. The authors were from countries including the United States (11), Australia (4), China (3), India (2), and Spain (1). As we can see, the results found by [106] are similar to those reported herein.
Through an analysis of the literature, we found that technology can provide benefits across healthcare practices, such as the development of products, processes, and systems, as well as support decision-making. Nonetheless, data security and privacy remain a concern, both for developers and users; regardless of how efficient technologies are becoming, there can always be failures. Thus, there is room for in-depth studies and the development of technologies with more secure systems.
4. Conclusions
To achieve its proposed objective, the present study used a systematic literature review of articles published from 2014 to 2019, resulting in the analysis of 446 articles. Six research questions were defined to analyze the literature on e-health practices. Through the analysis, four categories of the most common practices in the field were identified: “mhealth or mobile health”; “telehealth or telemedicine”; “technology”; and “others.” The main services provided with e-health practices are health literacy, mhealth and monitoring, telehealth, and systems combined with technology. Regarding the fields of medical specialties that offer consultations via telehealth, the following were identified: telepsychiatry, teledermatology, telerehabilitation, teleophthalmology, telecardiology, and teledentistry. Other fields were also found that offer services in e-health, such as geriatrics, general medicine, endocrinology, pediatrics, gynecology, and oncology.
Furthermore, 146 of the 446 studies analyzed use one of the common practices for disease diagnosis/treatment/monitoring, with mental illnesses and studies combining the treatment of multiple disease corresponding to 40%. Among the most frequently treated diseases are diabetes mellitus, cardiovascular diseases, chronic lung diseases, and mental illnesses (depression, anxiety, dementia). In terms of the countries that current use e-health, countries in Europe (Austria and Germany), Africa (Sub-Saharan countries), Asia (China), and North America (United States and Canada) stand out.
In relation to the technologies adopted in e-health practices, IoT, cloud computing, Big Data, security, and systems are among the most common.
Systemic reviews such as the one presented herein are important to provide more precise targeting of the practices and technologies that can be adopted in different procedures and processes, considering the context of each country. In general, such analyses can offer information and guide physicians and patients in the use of “new” services.
A study can always be improved, and the present one is no exception. Although the methodology applied followed careful steps and well-defined filters, the choice of only three keywords (considered comprehensive) may have resulted in the exclusion of some relevant studies in the analysis.
The present study was completed at the beginning of the global COVID-19 pandemic, during which physicians and patients began to use considerably more e-health practices and services due to the restrictions imposed by social isolation. Further studies are needed to address the growth in e-health practices, including services, diseases, and new approaches that are in greater demand, and the breakdown of government-imposed restrictions on expanding the use of e-health.
Author Contributions
All authors contributed in some way to the study design. M.H.d.F. wrote the article and had the help of F.K., C.T.P. guided and corrected the manuscript. B.P. made the final correction of the manuscript. P.R. helped in the correction of the manuscript. All authors have read and agreed to the published version of the manuscript.
Funding
This research was funded by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—Brazil (CAPES)—Finance Code 001 and Fundação Araucária.
Informed Consent Statement
Not applicable.
Acknowledgments
The authors would like to thank the Organizations and Society Research Laboratory, Federal University of Technology—Paraná, Brazil.
Conflicts of Interest
The authors declare no conflict of interest.
Appendix A
Table A1
Final portfolio.
Author | Title | Journal | Impact |
Year | Citations | InOrdinatio 10 |
---|---|---|---|---|---|---|
Stoyanov, S.R.; Hides, L.; Kavanagh, D.J.; Zelenko, O.; Tjondronegoro, D.; Mani, M. | Mobile app rating scale: A new tool for assessing the quality of health mobile apps | JMIR mHealth and uHealth | 4.301 | 2015 | 550 | 550.00 |
[38] Silva, B.M.C.; Rodrigues, J.J.P.C.; Torre-Díez, I.D.L.; Lopez-Coronado, M.; Saleem, K. | Mobile-health: A review of current state in 2015 | J. Biomed. Inf. | 2.950 | 2015 | 454 | 514.00 |
[83] Flodgren, G.; Rachas, A.; Farmer, A.J.; Inzitari, M.; Shepperd, S. | Interactive telemedicine: Effects on professional practice and health care outcomes | Cochrane Database Syst. Rev. | 7.755 | 2015 | 245 | 305.01 |
[39] Whitehead, L.; Seaton, P. | The effectiveness of self-management mobile phone and tablet apps in long-term condition management: A systematic review | J. Med. Internet. Res. | 4.945 | 2016 | 206 | 276.00 |
Sultan, N. | Making use of cloud computing for healthcare provision: Opportunities and challenges | International Journal of Information Management | 5.063 | 2014 | 202 | 252.01 |
[105] Wang, J.B.; Cadmus-Bertram, L.A.; Natarajan, L.; White, M.M.; Madanat, H.; Nichols, J.F.; Ayala, G.X.; Pierce, J.P. | Wearable sensor/device (Fitbit One) and SMS text-messaging prompts to increase physical activity in overweight and obese adults: A randomized controlled trial | Telemed. e-Health | 1.996 | 2015 | 173 | 233.00 |
Fortino, G.; Galzarano, S.; Gravina, R.; Li, W. | A framework for collaborative computing and multi-sensor data fusion in body sensor networks | Information Fusion | 10.716 | 2015 | 167 | 227.01 |
Boudreaux, E.; Waring, M.; Hayes, R.; Sadasivam, R.; Mullen, S.; Pagoto, S. | Evaluating and selecting mobile health apps: strategies for healthcare providers and healthcare organizations | Transl. Behav. Med. | 2.237 | 2014 | 173 | 223.00 |
[3] Ross, J.; Stevenson, F.; Lau, R.; Murray, E. | Factors that influence the implementation of e-health: A systematic review of systematic reviews (an update) | Implement Sci. | 0 | 2016 | 149 | 219.00 |
Naslund, J.; Marsch, L.; McHugo, G.; Bartels, S. | Emerging mHealth and eHealth interventions for serious mental illness: A review of the literature | J. Ment. Health | 2.604 | 2015 | 156 | 216.00 |
[56] Torre-Díez, I.D.L.; Lopez-Coronado, M.; Vaca, C.; Saez Aguado, J.; De Castro, C. | Cost-utility and cost-effectiveness studies of telemedicine, electronic, and mobile health systems in the literature: A Systematic review | Telemedicine and e-Health | 1.996 | 2015 | 150 | 210.00 |
Firth, J.; Torous, J.; Nicholas, J.; Carney, R.; Rosenbaum, S.; Sarris, J. | Can smartphone mental health interventions reduce symptoms of anxiety? A meta-analysis of randomized controlled trials | J. Affect Disord. | 4.084 | 2017 | 123 | 203.00 |
Riley, R.D.; Ensor, J.; Snell, K.I.E.; Debray, T.P.A.; Altman, D.G., Moons, K.G.M.; Collins, G.S. | External validation of clinical prediction models using big datasets from e-health records or IPD meta-analysis: Opportunities and challenges | BMJ—British Medical Journal | 27.604 | 2016 | 121 | 191.03 |
Poria, S.; Cambria, E.; Hussain, A.; Huang, G.B. | Towards an intelligent framework for multimodal affective data analysis | Neural Networks | 5.785 | 2015 | 131 | 191.01 |
[74] Larsen, M.E.; Nicholas, J.; Christensen, H. | A systematic assessment of smartphone tools for suicide prevention | Plos One | 2.776 | 2016 | 121 | 191.00 |
[64] Hollis, C.; Falconer, C.; Martin, J.; Whittington, C.; Stockton, S.; Glazebrook, C.; Davies, E. | Annual research review: digital health interventions for children and young people with mental health problems—a systematic and meta-review | J. Child. Psychol. Psychiatry | 6.129 | 2017 | 109 | 189.01 |
Sultan, N. | Reflective thoughts on the potential and challenges of wearable technology for healthcare provision and medical education | International Journal of Information Management | 5.063 | 2015 | 114 | 174.01 |
Aaronson, N.; Mattioli, V.; Minton, O.; Weis, J.; Johansen, C.; Dalton, S.; Verdonck-De Leeuw, I.; Stein, K.; Alfano, C.; Mehnert, A.; De Boer, A.; Van De Poll-Franse, L. | Beyond treatment—psychosocial and behavioural issues in cancer survivorship research and practice | Eur. J. Cancer | 6.680 | 2014 | 123 | 173.01 |
Ben-Zeev, D.; Schueller, S.M.; Begale, M.; Duffecy, J.; Kane, J.M.; Mohr, D.C. | Strategies for mHealth research: lessons from 3 mobile intervention studies | Adm. Policy. Ment. Health | 2.681 | 2015 | 111 | 171.00 |
[80] Moosavi, S.R.; Gia, T.N.; Rahmani, A.-M.; Nigussie, E.; Virtanen, S.; Isoaho, J.; Tenhunen, H. | SEA: A secure and efficient authentication and authorization architecture for IoT-based healthcare using smart gateways | Procedia Comput. Sci. | 0 | 2015 | 111 | 171.00 |
Wagner, L.I.; Schink, J.; Bass, M.; Patel, S.; Diaz, M.V.; Rothrock, N.; Pearman, T.; Gershon, R.; Penedo, F.J.; Rosen, S.; Cella, D. | Bringing PROMIS to practice: Brief and precise symptom screening in ambulatory cancer care | Cancer | 6.162 | 2015 | 110 | 170.01 |
Zhang, X.; Yu, P.; Yan, J.; Spil, I.T.A.M. | Using diffusion of innovation theory to understand the factors impacting patient acceptance and use of consumer e-health innovations: A case study in a primary care clinic | BMC Health Serv. Res. | 1.932 | 2015 | 110 | 170.00 |
Ebert, D.; Berking, M.; Cuijpers, P.; Lehr, D.; Pörtner, M.; Baumeister, H. | Increasing the acceptance of internet-based mental health interventions in primary care patients with depressive symptoms. A randomized controlled trial | J. Affect. Disord. | 4.084 | 2015 | 109 | 169.00 |
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Carmel, A.; Cornelius-Schecter, A.; Frankel, B.; Jannat-Khah, D.; Sinha, S.; Pelzman, F.; Safford, M. | Evaluation of the Patient Activated Learning System (PALS) to improve knowledge acquisition, retention, and medication decision making among hypertensive adults: Results of a pilot randomized controlled trial | Patient Educ. Couns. | 2.821 | 2019 | 0 | 100.00 |
Chang, Y.W.; Hsu, P.Y.; Wang, Y.; Chang, P.Y. | Integration of online and offline health services: The role of doctor-patient online interaction | Patient Educ. Couns. | 2.821 | 2019 | 0 | 100.00 |
Fang, S.Y.; Wang, Y.L.; Lu, W.H.; Lee, K.T.; Kuo, Y.L.; Fetzer, S.J. | Long-term effectiveness of an E-based survivorship care plan for breast cancer survivors: A quasi-experimental study | Patient Educ. Couns. | 2.821 | 2019 | 0 | 100.00 |
Helle, C.; Hillesund, E.; Wills, A.; Øverby, N. | Examining the effects of an eHealth intervention from infant age 6 to 12 months on child eating behaviors and maternal feeding practices one year after cessation: The Norwegian randomized controlled trial Early Food for Future Health | Plos One | 2.776 | 2019 | 0 | 100.00 |
Denis, F.; Voog, E.; Pointreau, Y.; Bourgeois, H.; Seegers, V.; Le Du, K. | Prospective study of a web-mediated management of febrile neutropenia related to chemotherapy (Bioconnect) | Support Care Cancer | 2.754 | 2019 | 0 | 100.00 |
Sadegh, S.S.; Saadat, P.K.; Sepehri, M.M.; Assadi, V. | A framework for m-health service development and success evaluation | International Journal of Medical Informatics | 2.721 | 2018 | 10 | 100.00 |
Frontoni, E.; Mancini, A.; Baldi, M.; Paolanti, M.; Moccia, S.; Zingaretti, P.; Landro, V.;Misericordia, P. | Sharing health data among general practitioners: The Nu.Sa. project | International Journal of Medical Informatics | 2.721 | 2019 | 0 | 100.00 |
Gu, D.; Li, T.; Wang, X.; Yang, X.; Yu, Z. | Visualizing the intellectual structure and evolution of electronic health and telemedicine research | International Journal of Medical Informatics | 2.721 | 2019 | 0 | 100.00 |
Kagawa, R.; Shinohara, E.; Imai, T.; Kawazoe, Y.; Ohe, K. | Bias of inaccurate disease mentions in electronic health record-based phenotyping | International Journal of Medical Informatics | 2.721 | 2019 | 0 | 100.00 |
Parks, R.; Wigand, R.; Othmani, M.; Serhier, Z.; Bouhaddou, O. | Electronic health records implementation in Morocco: Challenges of silo efforts and recommendations for improvements | International Journal of Medical Informatics | 2.721 | 2019 | 0 | 100.00 |
Krijnen-De Bruin, E.; Muntingh, A.; Hoogendoorn, A.; Van Straten, A.; Batelaan, N.; Maarsingh, O.; Van Balkom, A.; Van Meijel, B. | The GET READY relapse prevention programme for anxiety and depression: A mixed-methods study protocol | BMC Psychiatry | 2.666 | 2019 | 0 | 100.00 |
Habboushe, J.; Altman, C.; Lip, G. | Time trends in use of the CHADS 2 and CHA 2 DS 2 VASc scores, and the geographical and specialty uptake of these scores from a popular online clinical decision tool and medical reference | International Journal of Clinical Practice | 2.613 | 2019 | 0 | 100.00 |
Droes, R.M.; Van Rijn, A.;Rus, E.; Dacier, S.; Meiland, F. | Utilization, effect, and benefit of the individualized Meeting Centers Support Program for people with dementia and caregivers | Clin. Interv. Aging. | 2.585 | 2019 | 0 | 100.00 |
Berger, M.; Steinberg, D.; Askew, S.; Gallis, J.; Treadway, C.; Egger, J.; Kay, M.; Batch, B.; Finkelstein, E.; Devries, A.; Brewer, A.; Bennett, G. | The Balance protocol: A pragmatic weight gain prevention randomized controlled trial for medically vulnerable patients within primary care | BMC Public Health | 2.567 | 2019 | 0 | 100.00 |
Ohana, S.; Barnoy, S. | Israeli e-patients’ Informational Needs | Nurs. Outlook | 2.54 | 2019 | 0 | 100.00 |
Albarrak, A.I.; Mohammed, R.; Almarshoud, N.; Almujalli, L.; Aljaeed, R.; Altuwaijiri, S.; Albohairy, T. | Assessment of physician’s knowledge, perception and willingness of telemedicine in Riyadh region, Saudi Arabia | J. Infect. Public Health | 2.487 | 2019 | 0 | 100.00 |
Zhou, J.; Fan, T. | Understanding the factors influencing patient e-health literacy in online health communities (OHCs): A social cognitive theory perspective | Int. J. Environ. Res Public Health | 2.468 | 2019 | 0 | 100.00 |
Rathnayake, S.; Senevirathna, A. | Self-reported eHealth literacy skills among nursing students in Sri Lanka: A cross-sectional study | Nurse Educ Today | 2.442 | 2019 | 0 | 100.00 |
[102] Waschkau, A.; Wilfling, D.; Steinhaeuser, J. | Are Big Data analytics helpful in caring for multimorbid patients in general practice?—a scoping review | BMC Fam. Pract. | 2.431 | 2019 | 0 | 100.00 |
Firet, L.; De Bree, C.; Verhoeks, C.; Teunissen, D.; Lagro-Janssen, A. | Mixed feelings: General practitioners’ attitudes towards eHealth for stress urinary incontinence—a qualitative study | BMC Fam. Pract. | 2.431 | 2019 | 0 | 100.00 |
Gagnon, M.-P.;Ndiaye, M.A.; Larouche, A.; Chabot, G.; Chabot, C., Buyl, R.; Fortin, J.-P.; Giguere, A.; Leblanc, A.; Legare, F.; Motulsky, A.;Sicotte, C.; Witteman, H.O.; Kavanagh, E.; Lepinay, F.; Roberge, J.; Deletroz, C.; Abbasgholizadeh-Rahimi, S. | Optimising patient active role with a user-centred eHealth platform (CONCERTO plus) in chronic diseases management: A study protocol for a pilot cluster randomised controlled trial | BMJ Open | 2.376 | 2019 | 0 | 100.00 |
Beishuizen, C.; Akenine, U.; Barbera, M.; Rosenberg, A.; Fallah Pour, M.; Richard, E.; Soininen, H.; Mangialasche, F.; Kivipelto, M.; Pols, A.; Moll Van Charante, E. | Integrating nurses’ experiences with supporting behaviour change for cardiovascular prevention into a self-management internet platform in Finland and the Netherlands: A qualitative study | BMJ Open | 2.376 | 2019 | 0 | 100.00 |
Kocher, A.; Simon, M.; Dwyer, A.A.; Villiger, P.M.; Kunzler-Heule, P.; De Geest, S.; Berben, L.; Nicca, D. | Developing a rare disease chronic care model: Management of systemic sclerosis (MANOSS) study protocol | Journal of Advanced Nursing | 2.376 | 2019 | 0 | 100.00 |
Ladan, M.A.; Wharrad, H.; Windle, R. | eHealth adoption and use among healthcare professionals in a tertiary hospital in Sub-Saharan Africa: A Qmethodology study | PEERJ | 2.353 | 2019 | 0 | 100.00 |
Huang, R.-C.; Silva, D.; Beilin, L.; Neppe, C.; Mackie, K.; Roffey, E.; Gibson, L.; D’vaz, N.;Christian, H.;Reid, C.; Prescott, S. | Feasibility of conducting an early pregnancy diet and lifestyle e-health intervention: The Pregnancy Lifestyle Activity Nutrition (PLAN) project | J. Dev. Orig. Health Dis. | 2.34 | 2019 | 0 | 100.00 |
Vamos, C.A.; Griner, S.B.; Kirchharr, C.; Green, S.M.; Debate, R.; Daley, E.M.; Quinonez, R.B.; Boggess, K.A; Jacobs, T.; Christiansen, S. | The development of a theory-based eHealth app prototype to promote oral health during prenatal care visits | Transl. Behav. Med. | 2.237 | 2019 | 0 | 100.00 |
[59] Devan, H.; Godfrey, H.K.; Perry, M.A.; Hempel, D.; Saipe, B.; Hale, L.; Grainger, R. | Current practices of health care providers in recommending online resources for chronic pain self-management | J. Pain Res. | 2.236 | 2019 | 0 | 100.00 |
Vehko, T.; Hyppönen, H.; Puttonen, S.; Kujala, S.; Ketola, E.; Tuukkanen, J.; Aalto, A.-M.; Heponiemi, T. | Experienced time pressure and stress: electronic health records usability and information technology competence play a role | BMC Med. Inform. Decis. Mak. | 2.067 | 2019 | 0 | 100.00 |
[92] Duruturk, N.; Özköslü, M.A. | Effect of tele-rehabilitation on glucose control, exercise capacity, physical fitness, muscle strength and psychosocial status in patients with type 2 diabetes: A double blind randomized controlled trial | Prim. Care Diabetes | 2.008 | 2019 | 0 | 100.00 |
Van Schaik, P.; Thornhill, E.; Davies, M.; Flynn, D.; Kusev, P. | The use of information in online healthcare provider choice | Int. J. Hum. Comput. Stud. | 2.006 | 2019 | 0 | 100.00 |
Arduini, D.; Zanfei, A. | An overview of scholarly research on public e-services? A meta-analysis of the literature | Telecomm Policy | 2.000 | 2014 | 50 | 100.00 |
Doarn, C.; Zacharias, S.; Keck, C.; Tabangin, M.; Dealarcon, A.; Kelchner, L. | Design and implementation of an interactive website for pediatric voice therapy—the concept of in-between care: A telehealth model | Telemedicine and e-Health | 1.996 | 2019 | 0 | 100.00 |
Doarn, C.R.; Dorogi, A.; Tikhtman, R.; Pallerla, H.; Vonder Meulen, M.B. | Opinions on the role of telehealth in a large Midwest academic health center: A case study | Telemedicine and e-Health | 1.996 | 2019 | 0 | 100.00 |
Rebchuk, A.; Deptuck, H.; O’Neill, Z.; Fawcett, D.; Silverberg, N.; Field, T. | Validation of a novel telehealth administration protocol for the NIH toolbox-cognition battery | Telemedicine and e-Health | 1.996 | 2019 | 0 | 100.00 |
Murchie, P.; Masthoff, J.; Walter, F.; Rahman, K.; Allan, J.; Burrows, N.; Proby, C.; Lee, A.; Johnston, M.; Durrani, A.; Depasquale, I.; Brant, B.; Neilson, A.; Meredith, F.; Treweek, S.; Hall, S.; McDonald, A. | Achieving Self-Directed Integrated Cancer Aftercare (ASICA) in melanoma: Protocol for a randomised patient-focused pilot trial of delivering the ASICA intervention as a means to earlier detection of recurrent and second primary melanoma | Trials | 1.975 | 2019 | 0 | 100.00 |
Gerrits, O. | The future of healthcare has arrived: Who dares take up the challenge? | Neth. Heart J. | 1.972 | 2019 | 0 | 100.00 |
Van Den Bosch, S.; Van De Voort, N.; Xi, T.; Kool, R.; Bergé, S.; Faber, M. | Oral and maxillofacial surgery is ready for patient-centred eHealth interventions—the outcomes of a scoping review | International Journal of Oral and Maxillofacial Surgery | 1.961 | 2019 | 0 | 100.00 |
Warth, L.L.; Dyb, K. | eHealth initiatives; the relationship between project work and institutional practice | BMC Health Serv, Res, | 1.932 | 2019 | 0 | 100.00 |
Heisler, M.; Choi, H.; Mase, R.; Long, J.A.; Reeves, P.J. | Effectiveness of technologically enhanced peer support in improving glycemic management among predominantly African American, low-income adults with diabetes | Diabetes Educator | 1.910 | 2019 | 0 | 100.00 |
Ferguson, M.; Leighton, P.; Brandreth, M.; Wharrad, H. | Development of a multimedia educational programme for first-time hearing aid users: A participatory design | International Journal of Audiology | 1.821 | 2018 | 10 | 100.00 |
Leung, C.; Shaipanich, T. | Current practice in the management of pulmonary nodules detected on computed tomography chest scans | Can. Respir. J. | 1.803 | 2019 | 0 | 100.00 |
Shin, E.; Shim, J.-M. | Listen to doctors, friends, or both? Embedded they produce thick knowledge and promote health | J. Health Commun. | 1.773 | 2019 | 0 | 100.00 |
[66] Jansson, M.M.; Harjumaa, M.; Puhto, A.-P.; Pikkarainen, M. | Healthcare professionals’ proposed eHealth needs in elective primary fast-track hip and knee arthroplasty journey: A qualitative interview study | J. Clin. Nurs. | 1.757 | 2019 | 0 | 100.00 |
Kiberu, V.; Mars, M.; Scott, R. | Development of an evidence-based e-health readiness assessment framework for Uganda | Health Information Management Journal | 1.742 | 2019 | 0 | 100.00 |
Aromatario, O.; Hoye, A.V.; Vuillemin, A.; Foucaut, A.-M.; Crozet, C.; Pommier, J.; Cambon, L. | How do mobile health applications support behaviour changes? A scoping review of mobile health applications relating to physical activity and eating behaviours | Public Health | 1.696 | 2019 | 0 | 100.00 |
Lie, S., Karlsen, B., Graue, M. and Oftedal, B. | The influence of an eHealth intervention for adults with type 2 diabetes on the patient–nurse relationship: A qualitative study | Scand. J. Caring Sci. | 1.642 | 2019 | 0 | 100.00 |
Momenipour, A.; Pennathur, P. | Balancing documentation and direct patient care activities: A study of a mature electronic health record system | Int. J. Ind. Ergon. | 1.571 | 2019 | 0 | 100.00 |
[60] Zitkus, V.; Butkiene, R.; Butleris, R.; Maskeliunas, R.; Damasevicius, R.; Wozniak, M. | Minimalistic approach to coreference resolution in Lithuanian medical records | Comput. Math. Methods Med. | 1.563 | 2019 | 0 | 100.00 |
Wingo, B.C.; Yang, D.; Davis, D.; Padalabalanarayanan, S.; Hopson, B.; Thirumalai, M.; Rimmer, J.H. | Lessons learned from a blended telephone/e-health platform for caregivers in promoting physical activity and nutrition in children with a mobility disability | Disabil. Health J. | 1.471 | 2019 | 0 | 100.00 |
[46] Vyas, K.S.; Hambrick, H.R.; Shakir, A.; Morrison, S.D.; Tran, D.C.; Pearson, K.; Vasconez, H.C.; Mardini, S.; Gosman, A.A.; Dobke, M.; Granick, M.S. | A systematic review of the use of telemedicine in plastic and reconstructive surgery and dermatology | Annals of Plastic Sugery | 1.448 | 2017 | 20 | 100.00 |
Brignone, L.; Edleson, J. | The dating and domestic violence app Rubric: Synthesizing clinical best practices and digital health app standards for relationship violence prevention smartphone apps | Int. J. Hum. Comput. Interact. | 1.354 | 2019 | 0 | 100.00 |
[88] Triplett, K.; El-Behadli, A.; Masood, S.; Sullivan, S.; Desai, D. | Digital medicine program with pediatric solid organ transplant patients: Perceived benefits and challenges | Pediatr. Transplant. | 1.326 | 2019 | 0 | 100.00 |
Garai, A.; Pentek, I.; Adamko, A. | Revolutionizing healthcare with IoT and cognitive, cloud-based telemedicine | Acta Polytechnica Hungarica | 1.286 | 2019 | 0 | 100.00 |
Eden, R.; Burton-Jones, A.; Grant, J.; Collins, R.; Staib, A; Sullivan, C. | Digitising an Australian university hospital: Qualitative analysis of staff-reported impacts | Australian Health Review | 1.228 | 2019 | 0 | 100.00 |
Ross, P.; Cross, R. | Rise of the e-nurse: The power of social media in nursing | Contemp. Nurse | 1.216 | 2019 | 0 | 100.00 |
Castaneda, P.; Sales, A., Osborne, N. and Corriere, M. | Scope, themes, and medical accuracy of eHealth peripheral artery disease community forums | Annals of Vascular Surgery | 1.179 | 2019 | 0 | 100.00 |
Charnock, V. | Electronic healthcare records and data quality | Health Info. Libr. J. | 1.179 | 2019 | 0 | 100.00 |
Peterson, S.; Kuntz, C.; Roush, J. | Use of a modified treatment-based classification system for subgrouping patients with low back pain: Agreement between telerehabilitation and face-to-face assessments | Physiother. Theory Pract. | 1.158 | 2019 | 0 | 100.00 |
Veldhuijzen, G.; Van Esch, A.; Klemt-Kropp, M.; Terhaar Sive Droste, J.; Drenth, J. | E-patient counseling trial (E-PACO): Computer based education versus nurse counseling for patients to prepare for colonoscopy | JOVE—Journal of Visualized Experiments | 1.108 | 2019 | 0 | 100.00 |
Kerdjidj, O.; Amira, A.; Ghanem, K.; Ramzan, N.; Katsigiannis, S.; Chouireb, F. | An FPGA implementation of the matching pursuit algorithm for a compressed sensing enabled e-health monitoring platform | Microprocessors and Microsystems | 1.045 | 2019 | 0 | 100.00 |
Serafica, R.; Inouye, J.; Lukkahatai, N.; Braginsky, N.; Pacheco, M.; Daub, K. | The use of mobile health to assist self-management and access to services in a rural community | CIN—Computers Informatics Nursing | 1.029 | 2019 | 0 | 100.00 |
Abaza, H.; Marschollek, M. | mHealth application areas and technology combinations*. A comparison of literature from high and low/middle income countries | Methods Inf. Med. | 1.024 | 2017 | 20 | 100.00 |
Souza, T.; Lobão, W.; Santos, C.; Almeida, M.; Moreira Júnior, E. | Factors associated with the acceptance of the influenza vaccine among health workers: Knowledge, attitude and practice [Fatores associados à aceitação da vacina influenza entre trabalhadores de saúde: conhecimento, atitude e prática] | Cien. Saude. Colet. | 1.008 | 2019 | 0 | 100.00 |
Brown, L.J.; Jones, G.M.; Bond, M.J. | E-health: Psychosocial challenges for South Australian rural mental health consumers | Rural Remote Health | 0.985 | 2019 | 0 | 100.00 |
Kips, J.; Lambert, J.; Ongenae, K.; De Sutter, A.; Verhaeghe, E. | Teledermatology in Belgium: A pilot study | Acta Clinica Belgica | 0.960 | 2019 | 0 | 100.00 |
Clanchy, K.; Tweedy, S.; Trost, S. | The Adapted Physical Activity Program: A theory-driven, evidence-based physical activity intervention for people with brain impairment | Brain Impairment | 0.958 | 2019 | 0 | 100.00 |
Berndt, R.-D.; Preik, P.; Takenga, C. | TeleDermatology: the teledermatological solution mSkin® for daily practice | Hautarzt | 0.828 | 2019 | 0 | 100.00 |
Jedamzik, S. | Digital health and nursing: the future is now [Digitale Gesundheit und Pflege: Die Zukunft ist jetzt] | Unfallchirurg | 0.716 | 2019 | 0 | 100.00 |
Khan, I.; Xitong, G.; Ahmad, Z.; Shahzad, F. | Investigating factors impelling the adoption of e-health: A perspective of African expats in China | Sage Open | 0.675 | 2019 | 0 | 100.00 |
Alghazo, J.M. | Intelligent security and privacy of electronic health records using biometric images | Current Medical Imaging Reviews | 0.533 | 2019 | 0 | 100.00 |
De Leon-Castaneda, C. | Electronic health (e-health): A conceptual framework for implementation in health services | Gac. Med. Mex. | 0.283 | 2019 | 0 | 100.00 |
Chadi, N.; Weisbaum, E.; Malboeuf-Hurtubise, C.; Kohut, S.A.; Viner, C.; Palaniyar, N.; Kaufman, M.; Locke, J.; Vo, D.X. | In-person vs. eHealth mindfulness-based intervention for adolescents with chronic illnesses: A pilot randomized trial | Adolescent Psychiatry | 0 | 2019 | 0 | 100.00 |
Voutsidou, S.; Moraitis, E.; Jelastopoulou, E.; Sissouras, A.; Charalampous, G. | Electronic health applications in primary medical health care: Advantages and expectations | Archives of Hellenic Medicine | 0 | 2019 | 0 | 100.00 |
Spyridaki, A.; Antonakos, I.; Apostolakis, I.; Tountas, I. | Investigation of the effectiveness of mobile health applications for chronic diseases | Archives of Hellenic Medicine | 0 | 2019 | 0 | 100.00 |
Ramos, A.C.; Bouzas-Lorenzo, R.; del Olmo, A.M.; Buceta, B.B. | Opinión de los facultativos y usuarios sobre avances de la e-salud en atención primaria | Aten. Prim. | 0 | 2019 | 0 | 100.00 |
Guarda, P. | “OK Google, am I sick?’’: Artificial intelligence, e-health, and data protection regulation | Biolaw Journal-Rivista Di Biodiritto | 0 | 2019 | 0 | 100.00 |
Klocek, A.; Smahelova, M.; Knapova, L.; Elavsky, S. | GPs’ perspectives on eHealth use in the Czech Republic: A cross-sectional mixed-design survey study | BJGP Open | 0 | 2019 | 0 | 100.00 |
Reddeman, L.; Bourgeois, N.; Angl, E.N.; Heinrich, M.; Hillier, L.; Finn, H.; Bosiak, B.; Agarwal, P.; Mawson, R.; Propp, R.; Ivers, N.M. | How should family physicians provide physical activity advice? Qualitative study to inform the design of an e-health intervention | Can. Fam. Physician | 0 | 2019 | 0 | 100.00 |
Borries, T.M.; Dunbar, A.; Bhukhen, A.; Rismany, J.; Kilham, J., Feinn, R.; Meehan Sr., T.P. | The impact of telemedicine on patient self-management processes and clinical outcomes for patients with types I or II diabetes mellitus in the United States: A scoping review | Diabetes & Metabolic Syndrome-Clinical Research & Reviews | 0 | 2019 | 0 | 100.00 |
Howarth, A.; Quesada, J.; Donnelly, T.; Mills, P.R. | The development of “Make One Small Change”: An e-health intervention for the workplace developed using the Person-Based Approach | Digital Health | 0 | 2019 | 0 | 100.00 |
Krivenko V, N.; Elishev, V.G.; Kriventsova, L.A. | The impact of innovation on the performance of health care in the economic security system of the region | Ekonomika Regiona-Economy of Region | 0 | 2019 | 0 | 100.00 |
Seckin, G.; Hughes, S.; Yeatts, D.; Degreve, T. | Digital pathways to positive health perceptions: Does age moderate the relationship between medical satisfaction and positive health perceptions among middle-aged and older internet users? | Innov. Aging | 0 | 2019 | 0 | 100.00 |
Al-Sharekh, S.I.; Al-Shqeerat, K.H.A. | Security challenges and limitations in IoT environments | IJCSNS | 0 | 2019 | 0 | 100.00 |
Azcarraga, J.; Raduban, J.; Christine Gendrano, M.; Azcarraga, A. | Identity concealment when uploading pictures of patients in a tele-medicine system | International Journal of E-Health and Medical Communications | 0 | 2019 | 0 | 100.00 |
Khennou, F.; Chaoui, N.E.H.; Khamlichi, Y.I. | A migration methodology from legacy to new electronic health record based OpenEHR | International Journal of E-Health and Medical Communications | 0 | 2019 | 0 | 100.00 |
Christie, H.L.; Martin, J.L.; Connor, J.; Tange, H.J.; Verhey, F.R., de; Vugt, M.E.; Orrell, M. | eHealth interventions to support caregivers of people with dementia may be proven effective, but are they implementation-ready? | Internet Interv. | 0 | 2019 | 0 | 100.00 |
De Cicco, L.; Mascolo, S.; Palmisano, V.; Ribezzo, G. | Reducing the network bandwidth requirements for 360 degrees immersive video streaming | Internet Technology Letters | 0 | 2019 | 0 | 100.00 |
[78] Schimmer, R.; Orre, C.; Oberg, U.; Danielsson, K.; Hornsten, A. | Digital person-centered self-management support for people with type 2 diabetes: Qualitative study exploring design challenges | JMIR Diabetes | 0 | 2019 | 0 | 100.00 |
Goodall, G.; Ciobanu, I.; Taraldsen, K.; Sorgaard, J.; Marin, A., Draghici, R.; Zamfir, M.-V.; Berteanu, M.; Maetzler, W.; Serrano, J.A. | The use of virtual and immersive technology in creating personalized multisensory spaces for people living with dementia (SENSE-GARDEN): Protocol for a multisite before-after trial | JMIR Res. Protoc. | 0 | 2019 | 0 | 100.00 |
Prasad, M.; Manjunath, C.; Murthy, A.K.; Sampath, A.; Jaiswal, S.; Mohapatra, A. | Integration of oral health into primary health care: A systematic review | J. Family Med. Prim. Care | 0 | 2019 | 0 | 100.00 |
Bhatia, R.; Taneja, U. | Factors affecting indian consumers’ intention to use eHealth services | Journal of Health Management | 0 | 2019 | 0 | 100.00 |
Farzana, S.; Islam, S. | Symmetric key-based patient controlled secured electronic health record management protocol | Journal of High Speed Networks | 0 | 2019 | 0 | 100.00 |
Øvrelid, E; Halvorsen, M. | Supporting process innovation with lightweight IT at an emergency unit | Journal of Integrated Design and Process Science | 0 | 2019 | 0 | 100.00 |
Eke, E.; Kisi, M.; Ugurluoglu, D. | A research on awareness of e-health practices | Journal of Mehmet Akif Ersoy University Economics and Administrative Sciences Faculty | 0 | 2019 | 0 | 100.00 |
Anya, O.; Tawfik, H.; Alani, M.; Hu, J. | Cybersecurity design considerations for cross-boundary clinical decision support | J Reliab. Intell. Environ. | 0 | 2019 | 0 | 100.00 |
Kruczek, A. | e-health—modern technologies in mental health care | Postepy. Psychiatrii. I. Neurologii. | 0 | 2019 | 0 | 100.00 |
Costa, W.L.G.; Pereira, E.; Kontonatsios, G. | Use of smartphones for hypoglycaemia prediction—A feasibility study | Procedia Comput Sci | 0 | 2019 | 0 | 100.00 |
Senges, E.; Guiot, D.; Chandon, J.-L. | Desired ageing well: Predictive validity for consumers aged 50–80 | Recherche Et Applications En Marketing-English Edition | 0 | 2019 | 0 | 100.00 |
Webers, C.; Beckers, E.; Boonen, A.; Van Eijk-Hustings, Y.; Vonkeman, H.; Van De Laar, M.; Van Tubergen, A. | Development, usability and acceptability of an integrated eHealth system for spondyloarthritis in the Netherlands (SpA-Net) | RMD Open | 0 | 2019 | 0 | 100.00 |
Vesnic-Alujevic, L.; Pereira, A.G.; Breitegger, M. | Wearable sensors exploring EU policy narratives by engaging the extended peer community | Tecnoscienza | 0 | 2019 | 0 | 100.00 |
Metz, M.J.; Veerbeek, M.A.; Elfeddali, I.; De Beurs, E.; Van Der Feltz-Cornelis, C.M.; Beekman, A.T.F. | Shared decision making in mental health care; evaluation of the added value for patients and clinicians | Tijdschr. Psychiatr. | 0 | 2019 | 0 | 100.00 |
Allner, R.; Wilfling, D.; Kidholm, K.; Steinhäuser, J. | Telemedizinprojekte im ländlichen Raum Deutschlands. Eine systematische Bewertung mit dem “Modell zur Evaluation von telemedizinischen Anwendungen”. TT—[Telemedicine projects in rural areas of Germany. A systematic evaluation with the “M” | Z. Evid. Fortbild. Qual. Gesundhwes | 0 | 2019 | 0 | 100.00 |
Scherer, M.; Szecsenyi, J.; Gerlach, F. | Digitalisation in medicine—Who proceeds and who looks behind a plea for a DEGAM digital strategy [Digitalisierung in der medizin—Wer schreitet voran, wer schaut hinterher? Ein plädoyer für eine DEGAM-digitalstrategie] | Z. Allgemeinmed. | 0 | 2019 | 0 | 100.00 |
Gebre-Mariam, M.; Bygstad, B. | What can enterprise architecture do for healthcare? A framework of antecedents and benefits | Electronic Government | 0 | 2019 | 0 | 100.00 |
Ivanova, O.; Wambua, S.; Mwaisaka, J.; Bossier, T.; Thiongo, M.; Michielsen, K.; Gichangi, P. | Evaluation of the ELIMIKA Pilot Project: Improving ART adherence among HIV positive youth using an eHealth intervention in Mombasa, Kenya | African Journal of Reproductive Health | 0.547 | 2019 | 0 | 100.00 |
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Figures and Tables
Figure 3. Distribution of articles by country and number of articles published by journal.
Type of analysis used to address the research questions.
Type of Analysis | Research Question |
---|---|
Bibliometric analysis | In which countries and journals are studies on e-health practices published? |
Content analysis | What are the main e-health practices used worldwide? |
E-health practices and fields.
E-Health Practices | Specification of Service Delivery Types and Other E-Health-Related Topics Found in the Articles | Medical Fields Identified in the Articles | Authors |
---|---|---|---|
Mhealth or Mobile Health | Mhealth; assessment; systems assessment; information; telehealth; monitoring; health literacy. | General medicine; emergency; pediatrics; cardiology; oncology; psychiatry; neurology; dermatology; gynecology; hematology; infectiology/infectious diseases; radiotherapy/radiology; diagnostic imaging; gastroenterology; anesthesiology; nutrition; orthopedics; respiratory system/otorhinolaryngology; general surgery; urology; geriatrics; endocrinology; nephrology; ophthalmology. | [37,38,39,40,41,42] |
Telehealth or Telemedicine | Telehealth; intervention; interaction; mhealth; systems; technology. | Telepsychiatry; teledermatology; teledentistry; telerehabilitation; teleophthalmology; telecardiology. | [43,44,45,46,47,48] |
Technology | Technology; others; mhealth; patient monitoring; support; systems; telehealth; knowledge level; health literacy; systems assessment; program. | [49,50,51,52,53,54] | |
Others | Others; diagnosis; telehealth; mhealth; costs; programs; problems; project; quality of services; general e-health; care; project assessment; benefits; development; diagnosis; evaluation system; impact x cost-benefit; use and acceptance/barriers; knowledge level; mhealth; treatments; professionals’ views; study groups; intervention assessment; health literacy; technology; telehealth; randomized controlled trial—RCT; standardized service. | Nursing; oncology; gynecology; psychology; neurology; cardiology; psychiatry. | [55,56,57,58,59,60,61,62,63,64,65,66] |
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© 2021 by the authors.
Abstract
E-health can be defined as a set of technologies applied with the help of the internet, in which healthcare services are provided to improve quality of life and facilitate healthcare delivery. As there is a lack of similar studies on the topic, this analysis uses a systematic literature review of articles published from 2014 to 2019 to identify the most common e-health practices used worldwide, as well as the main services provided, diseases treated, and the associated technologies that assist in e-health practices. Some of the key results were the identification of the four most common practices used (mhealth or mobile health; telehealth or telemedicine; technology; and others) and the most widely used technologies associated with e-health (IoT, cloud computing, Big Data, security, and systems).
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Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer
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1 Department of Production Engineering, Federal University of Technology—Paraná (UTFPR), Ponta Grossa 84017-220, Brazil;
2 Division of Physical Education, State University of Ponta Grossa—Paraná (UEPG), Ponta Grossa 84030-900, Brazil;
3 Department of Accounting Sciences, Federal University of Technology—Paraná (UTFPR), Pato Branco 85503-390, Brazil;