Published on 25.09.19 in Vol 21, No 9 (2019): September
Preprints (earlier versions) of this paper are available at http://preprints.jmir.org/preprint/14394, first published Apr 15, 2019.
The Extent and Coverage of Current Knowledge of Connected Health: Systematic Mapping Study
Background: This study examines the development of the connected health (CH) research landscape with a view to providing an overview of the existing CH research. The research field of CH has experienced rapid growth coinciding with increasing pressure on health care systems to become more proactive and patient centered.
Objective: This study aimed to assess the extent and coverage of the current body of knowledge in CH. In doing so, we sought to identify specific topics that have drawn the attention of CH researchers and to identify research gaps, in particular those offering opportunities for further interdisciplinary research.
Methods: A systematic mapping study that combined scientific contributions from research in the disciplines of medicine, business, computer science, and engineering was used. Overall, seven classification criteria were used to analyze the papers, including publication source, publication year, research type, empirical type, contribution type, research topic, and the medical condition studied.
Results: The search resulted in 208 papers that were analyzed by a multidisciplinary group of researchers. The results indicated a slow start for CH research but showed a more recent steady upswing since 2013. The majority of papers proposed health care solutions (77/208, 37.0%) or evaluated CH approaches (49/208, 23.5%). Case studies (59/208, 28.3%) and experiments (55/208, 26.4%) were the most popular forms of scientific validation used. Diabetes, cancer, multiple sclerosis, and heart conditions were among the most prevalent medical conditions studied.
Conclusions: We conclude that CH research has become an established field of research that has grown over the last five years. The results of this study indicate a focus on technology-driven research with a strong contribution from medicine, whereas the business aspects of CH have received less research attention.
J Med Internet Res 2019;21(9):e14394
A variety of terms and concepts exist that describe the use of technology in health including Health IT, eHealth, Telemedicine, and Health Informatics. In the early 2000s , the term Connected Health (CH) began to appear. It did so in the context of research that investigated how information and communication technologies could advance health by connecting people, knowledge, technical artifacts, and organizations. Some years later, Poon and Zhang introduced a new CH information system based on a “four-layered architecture: personal, home, community, and hospital” [ ]. One of the most cited definitions for CH was introduced in 2013 [ ]:
Connected Health encompasses terms such as wireless, digital, electronic, mobile, and tele-health and refers to a conceptual model for health management where devices, services or interventions are designed around the patient’s needs, and health related data is shared, in such a way that the patient can receive care in the most proactive and efficient manner possible. All stakeholders in the process are connected by means of timely sharing and presentation of accurate and pertinent information regarding patient status through smarter use of data, devices, communication platforms, and people.
The European Network for the Joint Evaluation of Connected Health Technologies defines the CH vision as “a paradigm shift looking after the individual and community health in a process that speaks to the health journey of the person, through the entire lifespan, leveraging a variety of technologies to do so” . Achieving this vision will require attention to be paid to policy and regulation, technology and interoperability, training and education, business and revenue models, as well as citizen and clinician engagement [ ]. Successful implementation of the CH vision needs time and effort from all health care stakeholders.
Given the recent growth in CH research, we set out to map its evolution up to the present day. We use a systematic mapping study to chart the research landscape combining scientific contributions from the research disciplines of medicine, business, computer science, and engineering. Although previous CH reviews do exist, they are confined to descriptions of how CH solutions are being used in specific conditions such as cancer [, ] or in specific measurement technologies such as measurement of vital signs [ ] or weight [ ]. Past efforts also concentrated on presenting CH-related literature in systematic ways [ , , ]. Our goal is to provide a comprehensive, interdisciplinary overview of existing CH research. This will help researchers understand how the field has developed since its earliest studies in the late 1990s. It will also identify those topics that have drawn the attention of the research community. This knowledge will add value by identifying gaps or interdisciplinary opportunities in the study of CH. Perhaps most importantly, it may also underpin future work to develop an integrated and interdisciplinary research agenda for CH that will answer efficacy, design, policy, and sustainability questions for patients, clinicians, technology developers, and businesses.
This paper followed a systematic mapping study method . Systematic mapping studies aim primarily to present an overview of a research area to report the quantity and type of literature and results that are published within it. The systematic mapping process comprises 3 steps: (1) the identification of relevant literature, (2) the composition of a classification scheme, and (3) the mapping of literature [ ]. presents the mapping process including the search for relevant literature, the definition of a scheme, and the mapping of relevant publications.
The method was used to examine the body of existing research conducted by researchers in medicine, business, computer science, and engineering to understand the nature of research conducted in the area of CH. A systematic mapping study was found to be suitable for this task as it provided a high-level framework for combining interdisciplinary research efforts as well as an analytical framework that spanned disciplinary boundaries.
The aim of this study was to present an overview of the available publications pertinent to CH. Following the systematic mapping study method, the study was guided by a set of mapping questions.presents the 6 mapping questions (MQs) and the rationale for conducting this study. More detail as to the logic supporting the selection of suitable MQs is included in the Data Extraction Strategy section below. The study search strategy as well as the inclusion and exclusion criteria (EC) were based on these 6 MQs.
|MQa1||Which publication channels are the main targets for CHb research?||To identify where CH research can be found and to identify targets for publication of future studies|
|MQ2||How has the frequency of studies related to CH changed over time?||To identify the publication trends over time of CH literature|
|MQ3||What are the research types of CH studies?||To explore the different types of research reported in the literature concerning CH|
|MQ4||Are CH studies empirically validated?||To discover whether research on CH has been validated through empirical studies|
|MQ5||What are the approaches that were reported in CH research?||To discover the CH approaches reported in the existing CH literature|
|MQ6||What are the main topics and conditions in CH literature?||To identify the research areas and health conditions discussed in papers|
aMQ: mapping question.
bCH: connected health.
As CH is inherently interdisciplinary, our goal was to use the systematic mapping method to study research contributions on the topic across disciplines. We, therefore, searched papers from the most recognized scientific literature databases in each of the chosen disciplines.
The papers of the study were retrieved from 7 databases of scientific literature, namely, (1) Institute of Electrical and Electronics Engineers Xplore Digital Library, (2) Association for Computing Machinery Digital Library, (3) ScienceDirect, (4) SpringerLink, (5) MEDLINE and PubMed, (6) Business Source Complete (EBSCO), and (7) ABI and INFORM Collection (ProQuest), with the help of the corresponding search engines. The search was performed in October 2018. Different search strings were proposed and discussed over the course of joint meetings to arrive at a set of primary keywords. Two of the authors tested different strings of potential keywords such as “Connect Health,” “Connecting Health,” “Connect-Health,” or “Connecting-Health.” After evaluating the search results, the authors agreed to proceed using the following search strings: (“Connected” AND “Health”) OR (“Connected” AND “-” AND “Health”).
The search was applied to the title, abstract, and keywords to include relevant papers. On the basis of our methodology, we included a wide selection of papers on the first iteration and thereafter relied upon the inclusion criteria and EC to identify the relevant literature .
Paper Selection Criteria
The search results that were retrieved from the 7 chosen search engines were merged in a single list and saved in a spreadsheet document. Duplicate entries were removed based on the digital object identifier (DOI) and the intertitle lexical distance (the Levenshtein metric was used to measure the lexical distance) with the help of a custom Python script . A total of 7 papers had to be manually reviewed as potential duplicates.
The final list of papers was distributed to all authors for analysis. On the basis of the area of expertise, pairs of authors were assigned to analyze papers retrieved from each database. A total of 3 areas of expertise were identified as follows: technical (computer science and engineering), medical, and business. Each pair of authors reviewed the title, abstract, and keywords and made a recommendation as to whether that paper should be included or excluded. Discrepancies across coding teams were resolved through further scrutiny of the paper.
The inclusion criteria were limited to studies that discussed CH. In total, 240 papers were identified after the removal of duplicates, whereas 32 papers were excluded after meeting at least one of the following exclusion criteria: EC1—papers that focus on CH comorbidities, that is, the paper discusses the connection between health conditions, not CH as a concept; EC2—papers that focus on law; EC3—papers that focus on medical procedures only, without connection to CH; and EC4—papers that focus on evaluating climate but not in relation to CH.presents the process of the study selection.
Data Extraction Strategy
The selected studies were analyzed to collect information that would give answers to the MQs according to the data extraction strategy outlined inbelow.
|Mapping questions||Description of classification categories|
|MQa1||Publication source and publication channel|
|MQ3||Research types : evaluation research—real-world CHb approaches are implemented and undergo evaluation; solution proposal—a new CH solution or a significant extension of an existing solution is proposed, and the evaluation of the solution is based either on empirical data or theoretical argumentation; opinion paper—a CH study that is based on the personal opinion of the author(s); review—studies that present a review of existing CH literature; other—the remainder of research types associated with CH studies. This is assigned to studies where research type is either unknown or does not fall into one of the aforementioned main categories (eg, experience papers, which express the personal experience of author(s) without providing any scientific evidence to support it)|
|MQ4||Empirical types [, ]: case study—an empirical inquiry that investigates a CH approach within its real-life context; survey—an empirical inquiry method for collecting quantitative information concerning a CH approach, for example, a questionnaire; experiment—an empirical method applied under controlled conditions to evaluate a CH approach; history-based evaluation—nonempirical studies evaluating CH approaches in previously completed projects; theory—nonempirical research approaches or theoretical evaluation of a CH approach; other—the remainder of CH studies that do not fit within the previous types|
|MQ5||Contribution types: method—a manner of procedure and steps taken to acquire knowledge in CH; tool-based technique—a technique based on a software tool to accomplish CH tasks; model—a system representation that allows CH to be investigated through a hierarchical structure; framework—a real or conceptual structure intended to serve as a support or guide for CH; other—the remainder of CH approaches. This includes CH studies of approach not fitting other classes, along with very rare approaches that have been grouped in this category to facilitate abstraction and visualization. The approaches grouped herein are feasibility study, field research, process, guideline, and network analysis|
|MQ6||Main topics and medical conditions|
aMQ: mapping question.
bCH: connected health.
MQ6 comprised 2 parameters: the topic of the paper and the medical condition examined within it. With regard to the topic of the paper, we did not have a predefined list of topics but relied on an open coding process where the researchers conducting the analysis selected a descriptive word for the topic of the paper. To identify the main topics of the included papers, the authors relied on the title, abstract, and keywords. After compiling all topic words, we curated the topic list to come up with a consistent list (eg, using the same word for body-worn sensors and wearables). Similarly, with regard to the medical condition examined, no predefined classification was used that allowed coders to assign the medical condition, if any, of each CH paper. Again, the resulting condition list was curated to develop a more consistent list (eg, using the same word for ageing and elderly).
The synthesis method used was based on the following steps: (1) enumerating the number of papers per publication channel and the number of papers per bibliographic source per year; (2) enumerating the primary studies that are classified in each MQ’s response; (3) presenting visualizations for the classification results, which have been used in the analysis; and (4) presenting a narrative summary to discuss the principal findings.
This section describes the results related to the systematic MQs presented in. gives an overview of the classification results for all the included papers [ - , - ]. Custom Python scripts have been developed to process the classification data and generate the tables ( ) and figures ( and ) of this section. The Pandas and the Matplotlib Python [ , ] libraries were used to manipulate the tabular input data and plot the results, respectively.
Mapping Question 1: Which Publication Channels are the Main Targets for Connected Health Research?
The majority of the CH papers were published in scientific journals (139/208, 66.8%), whereas 32.9% (68/208) were published in scientific conferences.lists the publication forums that have published at least two CH papers.
Mapping Question 2: How Has the Frequency of Studies Related to Connected Health Changed Over Time?
presents the publication trend per year from 2000 to 2018. It must be noted that the analysis does not include the full body of CH work published in 2018 as our search was performed before the end of that year. We have added a projection for year 2018, estimating the total number of papers. Our projection assumes that publication frequency would remain consistent till the year end. As shows, there is a gap in publications from 2001 to 2004. Less than 5 papers per year were published until 2008, whereas from 2013 to 2017, the number of publications rises steadily.
Mapping Question 3: What are the Research Types of Connected Health Studies?
shows the research types of the included studies. The majority of the papers are solution proposal studies (77/208, 37.0%), 23.5% (49/208) of the selected studies evaluated CH approaches, 20.6% (43/208) reviewed literature, 16.8% (35/208) reported the opinions of authors about CH, and 1.9% (4/208) of the papers analyzed were classified as other.
Mapping Question 4: Are Connected Health Studies Empirically Validated?
presents our findings as to whether or not the included studies were empirically validated and, if so, the empirical validation approaches used. The majority of the studies were, in fact, empirically validated. More specifically, 28.3% (59/208) were validated in case studies, 26.4% (55/208) in controlled experiments, and 13.4% (28/208) with surveys. Nonempirical papers included, for example, those focused on theory (25/208, 12.0%) and those using history-based evaluation (11/208, 5.2%).
Mapping Question 5: What Are the Approaches That Were Reported in Connected Health Research?
shows the wide range of approaches taken in the included CH studies. The approaches most frequently reported belonged to other categories (66/208, 31.7%), followed by methods (56/208, 26.9%) and tool-based techniques (43/208, 20.6%). Only 10.0% (21/208) of the papers were classified as presenting frameworks, with 8.1% (17/208) suggesting models.
Mapping Question 6: What Are the Main Topics and Diseases in Connected Health Literature?
and present the results for the main topic and condition of the included CH studies. Topics with fewer than two occurrences have been omitted from . The most common research topics of the included CH papers were health care (×16) and disease management (×13), followed by telemedicine/telehealth (×11) and electronic health (eHealth)/mobile health (×9). lists all research topics and their frequencies, whereas lists the conditions and their frequencies. As for the main conditions reported in our study, diabetes (×12), aging (×10), cardiovascular diseases (×10), cancer (×7), chronic diseases (x7), and dementia (x4) were among the prevalent conditions found in the selected studies.
|Publication source||References||Number of published papers|
|Studies in Health Technology and Informatics||Topaz and Pruinelli (2017) , Wu et al (2017) [ ], O’Neill et al (2012) [ ], Feied et al (2009) [ ], Goossen (2017) [ ], Singh and Kvedar (2009) [ ], Maglaveras et al (2016) [ ], Saranto et al (2017) [ ], Skiba et al (2016) [ ], Kreuzthaler et al (2017) [ ], Goossen-Baremans et al (2017) [ ], Sermeus et al (2016) [ ], Silvello (2018) [ ], Tonheim and Babic (2018) [ ]||14|
|Journal of Medical Systems||Wen (2013) , Das and Goswami (2013) [ ], Santos et al (2016) [ ], Chang et al (2013) [ ], Vlahu-Gjorgievska et al (2016) [ ]|
Xu and Wu (2015) [ ], Lin et al (2016) [ ], Xie et al (2014) [ ], Kim and Lee (2014) [ ]
|Telemedicine and eHealtha||Ford et al (2018) , McConnochie et al (2016) [ ], Kvedar et al (2009) [ ], Aberger et al (2014) [ ], Trout et al (2017) [ ], Ternullo et al (2013) [ ], Kvedar et al (2009) [ ]||7|
|JMIR mHealth and uHealth||Wang et al (2018) , El Amrani et al (2017) [ ], Dur et al (2018) [ ], Wang et al (2018) [ ], Harte et al (2017) [ ], Argent et al (2018) [ ], Sathyanarayana et al (2016) [ ]||7|
|Health Affairs (Millwood)||Frist (2014) , Kvedar et al (2014) [ ], Iglehart (2014) [ ], Weinstein and Lopez (2014) [ ]||4|
|JMIRb||Sperrin et al (2016) , Gay and Leijdekkers (2015) [ ], Loiselle and Ahmed (2017) [ ], Agboola et al (2015) [ ]||4|
|QJMc: An International Journal of Medicine||Caulfield (2013) , Ansary et al (2013) [ ], Agboola et al (2013) [ ], Caulfield and Donnelly (2013) [ ]||4|
|Journal of Diabetes Science and Technology||Watson et al (2008) , Watson et al (2009) [ ], Pelletier et al (2011) [ ], Helal et al (2009) [ ]||4|
|Journal of the American Academy of Audiology||Saunders and Jacobs (2015) , Krupinski (2015) [ ], Gladden et al (2015) [ ]||3|
|JMIR Research Protocols||Mountford et al (2018) , Wang et al (2018) [ ]||2|
|International Journal of Medical Informatics||Giunti et al (2018) , Karampela et al (2018) [ ]||2|
|Maturitas||Chouvarda et al (2015) , Stara et al (2018) [ ]||2|
|JMIR Human Factors||Harte et al (2017) , Harte et al (2018) [ ]||2|
|Journal of Personalized Medicine||Agboola and Kvedar (2012) , Jethwani et al (2010) [ ]||2|
|Revue de l\'infirmiere||Warnet (2017) , Raymond and Léo (2017) [ ]||2|
|In the 31st International Symposium on computer-based medical systems||Barbosa et al (2018) , Barbosa et al (2018) [ ]||2|
|In the 14th International Conference on Telecommunications||Starič et al (2017) , Maramis et al (2017) [ ]||2|
|In Proceedings of the International Workshop on Software Engineering in Healthcare Systems||Carroll and Richardson (2016) , Abdullah et al (2018) [ ]||2|
|BMCd Medical Informatics and Decision Making||Allaert et al (2017) , Tharmalingam et al (2016) [ ]||2|
|In the First International Conference on Connected Health: Applications, Systems, and Engineering Technologies||Sinharay et al (2016) , Gawanmeh (2016) [ ]||2|
|Journal of Evaluation in Clinical Practice||Barr et al (2012) , Barr et al (2014) [ ]||2|
|American Journal of Hospice and Palliative Medicine||Aktas et al (2015) , Thomas et al (2017) [ ]||2|
aeHealth: electronic health.
bJMIR: Journal of Medical Internet Research.
cQJM: Quarterly Journal of Medicine.
dBMC: BioMed Central.
|Health care||16 (7.6)|
|Disease management||13 (6.2)|
|Electronic health/mobile health||9 (4.3)|
|Consumer health informatics||7 (3.3)|
|Information and communication technologies challenges||5 (2.4)|
|Personal health devices||4 (1.9)|
|Medical education||3 (1.4)|
|User-centered design||3 (1.4)|
|The internet of things||3 (1.4)|
|Software engineering||2 (0.9)|
|Medication adherence||2 (0.9)|
|Lifestyle coaching||2 (0.9)|
|Service delivery||2 (0.9)|
|No (condition)||131 (62.9)|
|Cardiovascular diseases||10 (4.8)|
|Chronic diseases||7 (3.3)|
|Multiple sclerosis||3 (1.4)|
|Mental health||2 (0.9)|
|General health||2 (0.9)|
|Chronic skin disease (psoriasis, dermatology)||1 (0.4)|
|Vital signs||1 (0.4)|
|Renal conditions||1 (0.4)|
|Dental issues||1 (0.4)|
|Palliative care||1 (0.4)|
|Urinary incontinence||1 (0.4)|
|Rheumatoid arthritis||1 (0.4)|
|Blood transfusion service||1 (0.4)|
|Hearing issues||1 (0.4)|
|Environmental exposure||1 (0.4)|
This section discusses the results and main findings of this study. First, each mapping question is discussed in its specific subsection. Finally, the limitations of this study are discussed.
Publication channels provide information about how research activities in CH have been established in the scientific community. The results of this study show that the majority of CH publications appear in peer-reviewed scientific journals (139/208, 66.8%). Although both journals and conferences aim to disseminate research and contribute to the development of a field, journals are typically considered more prestigious because of manuscript review criteria and acceptance practices. In addition, journals usually present more extended pieces of research work and contribute toward the establishment of a knowledge base for a field. Although the process of publication is longer compared with conferences, journals potentially have a larger impact in terms of visibility and audience reach [- ]. CH studies are often published in peer-reviewed journals with high impact factors, such as the Journal of Medical Systems, Studies in Health Technology and Informatics, Telemedicine and eHealth, and Journal of Medical Internet Research. This indicates that CH research efforts to date have focused on the establishment of a body of knowledge. On the other hand, conferences offer a dynamic environment that enables researchers to communicate with colleagues, exchange research interests, and receive specialized feedback. Conference publications could, therefore, be considered innovation-laden venues that denote the evolution of research in a field, as they often facilitate the presentation of novel ideas based on preliminary results. Conferences appear to be channels for the introduction and establishment of innovative research to experts of a particular area of research [ - ]. The first published conference papers on the topic of CH appeared in 2016. In the following two years, CH research was accepted and published by two international conferences. This finding could indicate efforts to further develop a research community to highlight and nurture CH research. The establishment of the European Network for the Joint Evaluation of Connected Health Technologies research coordination program, the funding of two Innovative Training Network CH projects (cancer: activating technology for connected health [CATCH] and connected health early stage researcher support system [CHESS]), and the expansion of the European Connected Health Alliance organization across Europe have all served to connect stakeholders under the umbrella of CH [ - ]. This coordination of effort has potentially led to the increase in both journal and conference publications as researchers come together around a shared interest in CH.
The papers matching our inclusion criteria, while spanning a publishing period from 2000 to 2018, show that CH research has attracted increasing attention since 2013. A publication gap between 2001 and 2004 coincides with the infancy of the CH field, likely reflecting the fact that the evolution of CH research was a slow and gradual process underpinned by the fermentation of experts from different academic disciplines. Overall,draws a very typical picture of the evolution of a research field, with sporadic publications in the beginning followed by an exponential increase in the yearly production of scientific literature. One could argue that the discourse around personal health records (PHRs) and patient services started around early 2000s, whereas the focus until that point had tended toward classic telemedicine. The PHR concept, and the shift from telemedicine to patient-centered services may have then driven the publication of CH-related papers. The growth of publications after 2009 can be attributed to various factors. The emergence of CH in the past decade coincides with a demographic shift where the older population is ultimately projected to outnumber the young people [ ]. This increasing aging population with its chronic and degenerative diseases has been projected to exert severe financial pressure on future health care systems [ , ]. At the same time, the development of new technologies has facilitated the promotion of CH solutions. The proliferation of devices and apps enabled by internet of things in health care over the last decade [ ], along with the adoption of smartphones and wearables by everyday users, has transformed health care delivery, enabling remote health monitoring and personalization of health care services [ , , ]. Likewise, providers such as Amazon, Google, Salesforce, International Business Machines corporation, and Microsoft began to establish new data centers for hosting cloud computing apps in 2009 [ ]. Taking that into consideration, we could argue that the emergence and evolution of the CH approach from 2009 onward reflects a demand for the provision of CH services to exploit technological advances and bring together patients and stakeholders to “offer the correct information to the correct person at the correct time” and make better decisions for health and care [ ]. In terms of eHealth policies and regulations, the trends are consistent with the development of the CH paradigm as, according to the World Health Organization, the number of countries with eHealth and telehealth policies or strategies has started to increase significantly since 2009 [ ].
Our results show that CH researchers focused primarily on suggesting novel solutions or extending existing research to explain, identify, and provide details of the CH approach (77/208, 37.0%). The 23.5% (49/208) of papers that centered on evaluation also represent attempts to comprehend and develop previous research through evaluating a solution with a valid approach [, ]. This leads us to conclude that much of CH research is at a development stage, where new concepts are proposed, developed, and evaluated to demonstrate their potential value. However, the existence of a significant number of literature reviews (43/208, 20.6%) indicates that there is maturity in the discipline that allows reviews of the existing research. Through these reviews, researchers aim to identify the research gaps to drive the growth of future research endeavors. If we view this finding alongside the publication trend, which shows that the body of CH research grew over the last few years, then we could argue that there is rapid growth in this discipline. This argument is given weight by the commission of European Union–funded projects such as CHESS in September 2015 and CATCH in 2016 [ , ]. Another factor to consider is that CH as a vision builds upon the best possible utilization of health data. Therefore, the growth of CH research can be considered to also be related to the availability of relevant health data. From 2016 onward, the amount of available networked data is more than 10.000 billion GB, almost double the amount of available data in 2014 [ ].
Our findings support the idea that over half of the CH studies are based on empirically informed approaches. More specifically, the majority of the solution proposals were empirically validated with case studies (59/208, 28.3%), followed by experiments (55/208, 26.4%), whereas 13.4% (28/208) used surveys. Case studies have been shown to be particularly suited to how and why questions, real-life contexts, and the building of theory . They offer an opportunity to use real-time methodologies where the collection of data and empirical material “takes place at the same time as such data are unfolding and where events depend on each other in a sequential order” [ ]. In particular, case studies can offer an “opportunity to observe and analyze a phenomenon previously inaccessible to scientific investigation” [ ]. This predominance of case study approaches to the study of CH reflects the relative immaturity of this field of research and a need to build understanding and theoretical contributions in the area through better understanding of individual cases and their contextual parameters. An experiment, on the other hand, is predicated on the analysis of covariance and assumes that participants can be assigned at random, that there are equal numbers of cases in each cell of the factorial design, and “ the correlations between or among the independent variables of a factorial design are zero” [ ]. The high number of experiment-based studies can be likely explained by the high number of papers exploring specific technical solutions that can be validated in controlled conditions. This raises the possibility that CH researchers are channeled into empirical approaches that have long been considered gold standard in engineering and health research.
The results for this MQ show that the majority of the included papers belong to other types of studies (66/208, 31.7%), which means that they used approaches that were not defined by our classification scheme. This finding could arise from a variety of factors. More than half of the included papers were from the medical discipline, a fact that has given rise to classification challenges, as reviewers were not able to fit them into one of the defined categories. Although mapping studies are common in the medical discipline , classifying research approaches that spanned studies from different disciplines was difficult. A more detailed classification scheme that incorporated classification systems from all disciplines may have delivered more precise results but would have made aggregation difficult and may have obscured any similarities across disciplines. Methods (56/208, 26.9%) were reported to be among the most frequent approaches, followed by tool-based techniques (43/208, 20.6%). This potentially reflects both the relative immaturity and the inherently interdisciplinary nature of the field of CH at this stage. Before researchers can develop models or frameworks that might be applied to CH, they must come to an agreement as to those methods and techniques that are both feasible and acceptable across the new field. The interdisciplinary nature of CH research makes it even more important to focus on methods. As Klein puts it: interdisciplinarity is “a means of solving problems and answering questions that cannot be satisfactorily addressed using single methods or approaches” [ ]. Researchers prefer, however, those methods that are traditional to their discipline [ ] and so time must be spent discussing and agreeing to those methods and techniques that can span the interdisciplinary boundaries of CH.
Research Topics and Conditions
The topic analysis shows that technical and medical disciplines dominate the research topics of the papers, with some references to related disciplines such as education or innovation research. The topic descriptions show a large body of papers discussing measurement-based monitoring with sensors and wearables. This reflects the fast development of body-worn sensors and wireless communication methods that allow the transfer and storage of large amounts of data for further analysis. Another body of papers focused on patient perspectives in CH solutions through a consumer viewpoint or user-centered design, which might reflect an increasing interest in patient empowerment and self-management solutions. The growth of CH as a research field might also reflect regulatory moves toward a data economy where rules for using personal data are clearer (eg, General Data Protection Regulation). Related topics included security, privacy, and interoperability issues. It has been suggested that leveraging interoperable CH technologies for chronic disease management can have multiple positive effects not only on patients but also on clinical outcomes, thus contributing, for example, to the promotion of outpatient care . Although the implementation of CH interoperable scenarios in real-life contexts, such as the Whole System Demonstrator Program in the United Kingdom, had overall positive outcomes [ ], issues related to security and lack of data standardization are among the challenges yet to be overcome [ , ].
Diabetes, cancer, and chronic heart conditions dominate the medical conditions covered. This is unsurprising given that these are leading health problems on the global stage . This may also indicate that lifestyle-related conditions are especially suited to CH, as lifestyle changes require patient empowerment and may benefit from technologies used for unobtrusive measurement and personal health devices. Papers discussing issues related to aging, including dementia and falls were often present; among less common conditions, multiple sclerosis seemed to draw more attention.
Owing to the interdisciplinary nature of our topic, we used an interdisciplinary team of researchers for analysis. Having researchers with different backgrounds could decrease inter-rater reliability, especially where we did not have a predefined list of values, as with the topic and condition parameters. Nevertheless, for the analysis of results, the authors relied upon the interpretation of descriptive statistics and visualizations, thus decreasing the threat to validity. In the same vein, to alleviate the authors’ influence on the classification process, the development of the classification scheme relied on widely accepted guidelines . The differences between content and style of abstracts in different research disciplines and traditions may have resulted in slight differences in information retrieval process. In some cases, the abstract did not include all information needed to classify the paper, and the researchers had to read parts of the full text to obtain all relevant information. However, the vast majority of the 208 publications identified have been classified purely based on the title, abstract, and keywords. In our view, subtle differences in the publication screening process have had only minor impacts on the main conclusions drawn from the 208 publications identified in our study.
The differences in publication practices between the disciplines probably had an influence on how the results of MQ1 were interpreted, as the role of conference and journal publications differs between disciplines . For example, many highly regarded conferences within the business discipline do not publish conference proceedings (eg, European Group for Organizational Studies). Indeed, even those conferences that do publish proceedings may only do so for a subsection of the best papers, and authors will still be offered the option of removing their papers from those proceedings to protect future publishing opportunities (eg, Academy of Management). These factors combine to mean that verbal discussions may well have commenced within the business academic community in conferences that are not reflected within our review as it deals only with published material.
As the methodology of the systematic mapping study that we used in this research was originally developed in the context of software engineering, it is likely that some of the analysis parameters were less optimal in other disciplines. This is reflected, for example, in the large number of studies classified into the category other for the parameter approach. In the joint analysis meetings, the coding authors shared experiences of their difficulties in classifying the papers within the agreed analysis parameters. Alternative solutions were discussed, but it was difficult to reach a consensus that would have been satisfactory across disciplines. Ultimately, we decided to use the classification parameters proposed by our methodology. The validity of our conclusions is only applicable within the CH context.
To limit the threat related to the identification of primary studies and to include as many relevant papers as possible, 2 of the authors ran several iterations to test different strings of keywords. The adoption of the final set of keywords was used as it returned the largest number of studies. However, the list of studies might be incomplete, as additional or different terms might have an impact on the final selection of papers . Nevertheless, in light of the interdisciplinary endeavor and the scope of the study, we believe that we have included the majority of the relevant literature. For the bibliographic search, no timeframe was defined; hence, the representativeness of the included studies was not affected by this factor. The results of this study should be considered under the prism of the specific search string and classification scheme and offer a baseline for future endeavors.
Our search strategy and inclusion criteria have omitted studies that are referenced in grey literature. However, the literature search was conducted in the world’s most leading and comprehensive databases for scientific knowledge. Furthermore, to alleviate the threat of publications’ nonavailability because of subscription paywalls, we performed the initial screening using a combination of university libraries to improve our access to papers. To address validity threats because of duplication, duplicate entries were removed based on the DOI and the intertitle lexical distance with the help of a custom Python script, which was ultimately manually reviewed to ensure duplicate removal.
On the basis of our results, we can conclude that CH research is an established field of research. The interdisciplinary nature of the field can be seen especially in papers at the intersection of the medical and technical disciplines. The number of papers in the business research publication forums is still smaller. However, business-related themes are visible in topics of papers, such as consumer orientation and innovation research, although at a much smaller scale than the topics of more technical and medical nature. For CH to succeed, money needs to move differently around the health care system. Most developed health care systems continue to reimburse care in a cure rather than a prevention mode. Cutting-edge technologies and redesigned care pathways may fail if they run contrary to the flow of health care finance. Our findings emphasize the need to increase business research in the area of CH or to find the vocabularies and keywords necessary to link existing business research with CH endeavors.
There is a growing need to involve and engage patients in their own care and, by extension, in the design of digital solutions to improve their efficacy. Tailored CH interventions may more effectively reach the intended audience in a meaningful way, but this requires in-depth understanding of the condition’s needs, barriers, and facilitators. The important role that health care professionals play in the health care system is in contrast with their lack of involvement in the design of CH. In the same vein, recent research suggests that health care professionals’ education in Europe is lacking in the area of health care information technologies . Emerging trends such as user-centered design and the inclusion of patient representatives attempt to address these problems by creating CH solutions that are tailored to the characteristics and tasks of the intended users. Adoption of these and similar approaches could further the field of CH research and implementation.
Given that CH research has become far more widespread in the years since 2013, perhaps it is time to devote more research resources to the scalability of CH as reflected in empirical approaches that facilitate the use of larger populations.
We see our findings as the foundations of a research roadmap for CH researchers that challenge current thinking in health care. Such a research agenda would go beyond investigations into the feasibility of individual technical solutions to examine and develop ecosystems of stakeholders, technologies, and infrastructures that together form new kinds of systemic solutions. Such an agenda would require more focus on research that addresses interdisciplinary methodological questions alongside the creation of vocabularies and frameworks for researchers working in different disciplines to effectively collaborate and examine interdisciplinary research questions through joint methodological approaches.
This paper is based upon work from European Cooperation in Science and Technology (COST) Action ENJECT TD 1405, supported by COST.
This research has been supported by a grant from the Tatra banka Foundation (2018vs108).
MK and MI conceived, designed, led overall study conduct. MK and CM carried out the data collection and curation of visualizations. MK and MI and drafted the first version of the manuscript. All the authors except CM led analysis and interpretation of the data, NM proofread the final manuscript and suggested modifications. All authors read and approved the final manuscript.
Conflicts of Interest
Classification results for all the included papers.XLSX File (Microsoft Exel File), 17KB
- Mountford N, Chouvarda I, Isomursu M, Caulfield B. Vectors and drivers of connected health in Europe: a foundation for integrated care. Int J Integr Care 2017 Oct 17;17(5):305. [CrossRef]
- Poon CC, Zhang YT. Perspectives on high technologies for low-cost healthcare. IEEE Eng Med Biol Mag 2008;27(5):42-47. [CrossRef] [Medline]
- Caulfield BM, Donnelly SC. What is connected health and why will it change your practice? QJM 2013 Aug;106(8):703-707. [CrossRef] [Medline]
- Mountford N, Kessie T, Quinlan M, Maher R, Smolders R, van Royen P, et al. Connected Health in Europe: Where are We Today?. Dublin, Ireland: ENJECT Consortium; 2017.
- Wait S, Han D, Muthu V, Oliver K, Chrostowski S, Florindi F, et al. Towards sustainable cancer care: reducing inefficiencies, improving outcomes—a policy report from the All.Can initiative. J Cancer Policy 2017 Sep;13:47-64. [CrossRef]
- Giunti G, Giunta DH, Guisado-Fernandez E, Bender JL, Fernandez-Luque L. A biopsy of breast cancer mobile applications: state of the practice review. Int J Med Inform 2018 Feb;110:1-9 [FREE Full text] [CrossRef] [Medline]
- Agboola SO, Kvedar JC. Institutional profile: center for connected health. Per Med 2012 May;9(3):337-340. [CrossRef] [Medline]
- Khan Y, Ostfeld AE, Lochner CM, Pierre A, Arias AC. Monitoring of vital signs with flexible and wearable medical devices. Adv Mater 2016 Jun;28(22):4373-4395. [CrossRef] [Medline]
- Sperrin M, Rushton H, Dixon WG, Normand A, Villard J, Chieh A, et al. Who self-weighs and what do they gain from it? A retrospective comparison between smart scale users and the general population in England. J Med Internet Res 2016 Jan 21;18(1):e17 [FREE Full text] [CrossRef] [Medline]
- Ostherr K, Killoran P, Shegog R, Bruera E. Death in the digital age: a systematic review of information and communication technologies in end-of-life care. J Palliat Med 2016 Apr;19(4):408-420 [FREE Full text] [CrossRef] [Medline]
- Karampela M, Ouhbi S, Isomursu M. Personal health data: a systematic mapping study. Int J Med Inform 2018 Oct;118:86-98. [CrossRef] [Medline]
- Petersen K, Feldt R, Mujtaba S, Mattsson M. Systematic Mapping Studies in Software Engineering. In: Proceedings of the 12th International Conference on Evaluation and Assessment in Software Engineering. 2008 Presented at: EASE'08; June 26-27, 2008; Swindon, UK p. 68-77 URL: http://dl.acm.org/citation.cfm?id=2227115.2227123
- Kitchenham BA, Budgen D, Brereton OP. Using mapping studies as the basis for further research – a participant-observer case study. Inf Softw Technol 2011 Jun;53(6):638-651. [CrossRef]
- Levenshtein VI. Binary codes capable of correcting deletions, insertions, and reversals. Sov Phys Dokl 1996;10(8):707-710 [FREE Full text]
- Brereton P, Kitchenham BA, Budgen D, Turner M, Khalil M. Lessons from applying the systematic literature review process within the software engineering domain. J Syst Software 2007 Apr;80(4):571-583. [CrossRef]
- Jorgensen M, Shepperd M. A systematic review of software development cost estimation studies. IIEEE Trans Software Eng 2007;33(1):33-53. [CrossRef]
- Chouvarda IG, Goulis DG, Lambrinoudaki I, Maglaveras N. Connected health and integrated care: toward new models for chronic disease management. Maturitas 2015 Sep;82(1):22-27. [CrossRef] [Medline]
- Warnet S. ['Health professionals will become experts in the world of connected health']. Rev Infirm 2017 Nov;66(235):21-23. [CrossRef] [Medline]
- Raymond G, Léo M. [E-health applications and their users]. Rev Infirm 2017 Nov;66(235):24-25. [CrossRef] [Medline]
- Gorwood P. [The contribution of digital technology to mental healthcare: much hope, a few concerns]. Soins Psychiatr 2017;38(311):12-15. [CrossRef] [Medline]
- Wang J, Cai C, Padhye N, Orlander P, Zare M. A behavioral lifestyle intervention enhanced with multiple-behavior self-monitoring using mobile and connected tools for underserved individuals with type 2 diabetes and comorbid overweight or obesity: pilot comparative effectiveness trial. JMIR Mhealth Uhealth 2018 Apr 10;6(4):e92 [FREE Full text] [CrossRef] [Medline]
- Harte R, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, Quinlan LR, et al. A human-centered design methodology to enhance the usability, human factors, and user experience of connected health systems: a three-phase methodology. JMIR Hum Factors 2017 Mar 16;4(1):e8 [FREE Full text] [CrossRef] [Medline]
- Harte R, Quinlan LR, Glynn L, Rodriguez-Molinero A, Scharf T, Carenas C, et al. A multi-stage human factors and comfort assessment of instrumented insoles designed for use in a connected health infrastructure. J Pers Med 2015 Dec 16;5(4):487-508 [FREE Full text] [CrossRef] [Medline]
- Bloss CS, Wineinger NE, Peters M, Boeldt DL, Ariniello L, Kim JY, et al. A prospective randomized trial examining health care utilization in individuals using multiple smartphone-enabled biosensors. PeerJ 2016;4:e1554 [FREE Full text] [CrossRef] [Medline]
- Patel MS, Volpp KG, Rosin R, Bellamy SL, Small DS, Fletcher MA, et al. A randomized trial of social comparison feedback and financial incentives to increase physical activity. Am J Health Promot 2016 Jul;30(6):416-424 [FREE Full text] [CrossRef] [Medline]
- Wen F. A robust uniqueness-and-anonymity-preserving remote user authentication scheme for connected health care. J Med Syst 2013 Dec;37(6):9980. [CrossRef] [Medline]
- Das AK, Goswami A. A secure and efficient uniqueness-and-anonymity-preserving remote user authentication scheme for connected health care. J Med Syst 2013 Jun;37(3):9948. [CrossRef] [Medline]
- Santos DF, Gorgônio KC, Perkusich A, Almeida HO. A standard-based and context-aware architecture for personal healthcare smart gateways. J Med Syst 2016 Oct;40(10):224. [CrossRef] [Medline]
- Chang YF, Yu SH, Shiao DR. A uniqueness-and-anonymity-preserving remote user authentication scheme for connected health care. J Med Syst 2013 Apr;37(2):9902. [CrossRef] [Medline]
- DePasse JW, Chen CE, Sawyer A, Jethwani K, Sim I. Academic medical centers as digital health catalysts. Healthc (Amst) 2014 Sep;2(3):173-176. [CrossRef] [Medline]
- Ford AR, Gibbons CM, Torres J, Kornmehl HA, Singh S, Young PM, et al. Access to dermatological care with an innovative online model for psoriasis management: results from a randomized controlled trial. Telemed J E Health 2019 Jul;25(7):619-627 [FREE Full text] [CrossRef] [Medline]
- Mountford N, Zubiete ED, Kessie T, Garcia-Zapirain B, Nuño-Solinís R, Coyle D, et al. Activating technology for connected health in cancer: protocol for a research and training program. JMIR Res Protoc 2018 Jan 24;7(1):e14 [FREE Full text] [CrossRef] [Medline]
- Fernandez-Luque L, Staccini P. All that glitters is not gold: consumer health informatics and education in the era of social media and health apps. Findings from the yearbook 2016 section on consumer health informatics. Yearb Med Inform 2016 Nov 10(1):188-193 [FREE Full text] [CrossRef] [Medline]
- Kuziemsky CE, Gogia SB, Househ M, Petersen C, Basu A. Balancing health information exchange and privacy governance from a patient-centred connected health and telehealth perspective. Yearb Med Inform 2018 Aug;27(1):48-54 [FREE Full text] [CrossRef] [Medline]
- Jethwani K, Kvedar J, Kvedar J. Behavioral phenotyping: a tool for personalized medicine. Per Med 2010 Nov;7(6):689-693. [CrossRef] [Medline]
- Saunders G, Jacobs P. Beyond the audiology clinic: innovations and possibilities of connected health. J Am Acad Audiol 2015 Oct;26(9):748-749. [CrossRef] [Medline]
- Topaz M, Pruinelli L. Big data and nursing: implications for the future. Stud Health Technol Inform 2017;232:165-171. [CrossRef] [Medline]
- Watson AJ, Grant RW, Bello H, Hoch DB. Brave new worlds: how virtual environments can augment traditional care in the management of diabetes. J Diabetes Sci Technol 2008 Jul;2(4):697-702 [FREE Full text] [CrossRef] [Medline]
- Gay V, Leijdekkers P. Bringing health and fitness data together for connected health care: mobile apps as enablers of interoperability. J Med Internet Res 2015 Nov 18;17(11):e260 [FREE Full text] [CrossRef] [Medline]
- Spruijt-Metz D, Hekler E, Saranummi N, Intille S, Korhonen I, Nilsen W, et al. Building new computational models to support health behavior change and maintenance: new opportunities in behavioral research. Transl Behav Med 2015 Sep;5(3):335-346 [FREE Full text] [CrossRef] [Medline]
- McConnochie KM, Wood NE, Alarie C, Ronis S. Care offered by an information-rich pediatric acute illness connected care model. Telemed J E Health 2016 Jun;22(6):465-472. [CrossRef] [Medline]
- Hao T, Chang H, Ball M, Lin K, Zhu X. cHRV uncovering daily stress dynamics using bio-signal from consumer wearables. In: Gundlapalli AV, Jaulent MC, Zhao D, editors. MEDINFO 2017: Precision Healthcare through Informatics. Amsterdam, Netherlands: IOS Press; 2017:98-102.
- Weinstein RS, Krupinski EA, Doarn CR. Clinical examination component of telemedicine, telehealth, mhealth, and connected health medical practices. Med Clin North Am 2018 May;102(3):533-544. [CrossRef] [Medline]
- Wu Y, Wang Y, Ji M. Competencies related to informatics and information management for practicing nurses in select countries in Asia. Stud Health Technol Inform 2017;232:86-96. [CrossRef] [Medline]
- Adeshina AM, Hashim R. Computational approach for securing radiology-diagnostic data in connected health network using high-performance GPU-accelerated AES. Interdiscip Sci 2017 Mar;9(1):140-152. [CrossRef] [Medline]
- Cohen M. Connected health and multiple sclerosis. Rev Neurol (Paris) 2018 Jun;174(6):480-485. [CrossRef] [Medline]
- McElnay JC. Connected health and the pharmacist. Int J Pharm Pract 2011 Feb;19(1):3-4. [CrossRef] [Medline]
- Frist WH. Connected health and the rise of the patient-consumer. Health Aff (Millwood) 2014 Feb;33(2):191-193. [CrossRef] [Medline]
- Kvedar JC, Herzlinger R, Holt M, Sanders JH. Connected health as a lever for healthcare reform: dialogue with featured speakers from the 5th annual connected health symposium. Telemed J E Health 2009 May;15(4):312-319. [CrossRef] [Medline]
- Barr PJ, McElnay JC, Hughes CM. Connected health care: the future of health care and the role of the pharmacist. J Eval Clin Pract 2012 Feb;18(1):56-62. [CrossRef] [Medline]
- El Amrani L, Engberink AO, Ninot G, Hayot M, Carbonnel F. Connected health devices for health care in french general medicine practice: cross-sectional study. JMIR Mhealth Uhealth 2017 Dec 21;5(12):e193 [FREE Full text] [CrossRef] [Medline]
- Kvedar J, Coye MJ, Everett W. Connected health: a review of technologies and strategies to improve patient care with telemedicine and telehealth. Health Aff (Millwood) 2014 Feb;33(2):194-199. [CrossRef] [Medline]
- Colorafi K. Connected health: a review of the literature. Mhealth 2016;2:13 [FREE Full text] [CrossRef] [Medline]
- Aktas A, Hullihen B, Shrotriya S, Thomas S, Walsh D, Estfan B. Connected health: cancer symptom and quality-of-life assessment using a tablet computer: a pilot study. Am J Hosp Palliat Care 2015 Mar;32(2):189-197. [CrossRef] [Medline]
- Iglehart JK. Connected health: emerging disruptive technologies. Health Aff (Millwood) 2014 Feb;33(2):190. [CrossRef] [Medline]
- Séblain D, Capitaine A, Khonsari RH. Connected toothbrush, augmented reality and oral hygiene in children with cleft lip and palate. J Stomatol Oral Maxillofac Surg 2019 Feb;120(1):83-85. [CrossRef] [Medline]
- Vlahu-Gjorgievska E, Koceski S, Kulev I, Trajkovik V. Connected-health algorithm: development and evaluation. J Med Syst 2016 Apr;40(4):109. [CrossRef] [Medline]
- Wang J, Coleman DC, Kanter J, Ummer B, Siminerio L. Connecting smartphone and wearable fitness tracker data with a nationally used electronic health record system for diabetes education to facilitate behavioral goal monitoring in diabetes care: protocol for a pragmatic multi-site randomized trial. JMIR Res Protoc 2018 Apr 2;7(4):e10009 [FREE Full text] [CrossRef] [Medline]
- Xu L, Wu F. Cryptanalysis and improvement of a user authentication scheme preserving uniqueness and anonymity for connected health care. J Med Syst 2015 Feb;39(2):10. [CrossRef] [Medline]
- Bond R, Finlay DD, Guldenring D, Breen C. Data driven computer simulation to analyse an ECG limb lead system used in connected health environments. Methods Inf Med 2016 May 17;55(3):258-265. [CrossRef] [Medline]
- Anderson D, Liu R, Subramony JA, Cammack J. Design control considerations for biologic-device combination products. Adv Drug Deliv Rev 2017 Mar;112:101-105. [CrossRef] [Medline]
- Dur O, Rhoades C, Ng MS, Elsayed R, van Mourik R, Majmudar MD. Design rationale and performance evaluation of the wavelet health wristband: benchtop validation of a wrist-worn physiological signal recorder. JMIR Mhealth Uhealth 2018 Oct 16;6(10):e11040 [FREE Full text] [CrossRef] [Medline]
- Watson AJ, Kvedar JC, Rahman B, Pelletier AC, Salber G, Grant RW. Diabetes connected health: a pilot study of a patient- and provider-shared glucose monitoring web application. J Diabetes Sci Technol 2009 Mar 1;3(2):345-352 [FREE Full text] [CrossRef] [Medline]
- Wang J, Chu CF, Li C, Hayes L, Siminerio L. Diabetes educators' insights regarding connecting mobile phone- and wearable tracker-collected self-monitoring information to a nationally-used electronic health record system for diabetes education: descriptive qualitative study. JMIR Mhealth Uhealth 2018 Jul 26;6(7):e10206 [FREE Full text] [CrossRef] [Medline]
- Lin C, Song Z, Song H, Zhou Y, Wang Y, Wu G. Differential privacy preserving in big data analytics for connected health. J Med Syst 2016 Apr;40(4):97. [CrossRef] [Medline]
- Sapci AH, Sapci HA. Digital continuous healthcare and disruptive medical technologies: m-health and telemedicine skills training for data-driven healthcare. J Telemed Telecare 2018 Aug 22:- (epub ahead of print). [CrossRef] [Medline]
- Novillo-Ortiz D, Dumit EM, D'Agostino M, Becerra-Posada F, Kelley ET, Torrent-Sellens J, et al. Digital health in the Americas: advances and challenges in connected health. BMJ Innov 2018 Jul;4(3):123-127 [FREE Full text] [CrossRef] [Medline]
- Stara V, Harte R, di Rosa M, Glynn L, Casey M, Hayes P, et al. Does culture affect usability? A trans-European usability and user experience assessment of a falls-risk connected health system following a user-centred design methodology carried out in a single European country. Maturitas 2018 Aug;114:22-26. [CrossRef] [Medline]
- Kvedar JC, Nesbitt T, Kvedar JG, Darkins A. E-patient connectivity and the near term future. J Gen Intern Med 2011 Nov;26(Suppl 2):636-638 [FREE Full text] [CrossRef] [Medline]
- Turnin MC, Schirr-Bonnans S, Martini J, Buisson JC, Taoui S, Chauchard MC, et al. Educ@dom: comparative study of the telemonitoring of patients with type 2 diabetes versus standard monitoring-study protocol for a randomized controlled study. Diabetol Metab Syndr 2017;9:52 [FREE Full text] [CrossRef] [Medline]
- Harte R, Hall T, Glynn L, Rodríguez-Molinero A, Scharf T, Quinlan LR, et al. Enhancing home health mobile phone app usability through general smartphone training: usability and learnability case study. JMIR Hum Factors 2018 Apr 26;5(2):e18 [FREE Full text] [CrossRef] [Medline]
- Aberger EW, Migliozzi D, Follick MJ, Malick T, Ahern DK. Enhancing patient engagement and blood pressure management for renal transplant recipients via home electronic monitoring and web-enabled collaborative care. Telemed J E Health 2014 Sep;20(9):850-854 [FREE Full text] [CrossRef] [Medline]
- O'Neill SA, Nugent CD, Donnelly MP, McCullagh P, McLaughlin J. Evaluation of connected health technology. Technol Health Care 2012;20(3):151-167. [CrossRef] [Medline]
- Bushko R. Future of ehealth: can consumers cure themselves? Stud Health Technol Inform 2009;149:178-184. [Medline]
- Weinstein RS, Lopez AM. Health literacy and connected health. Health Aff (Millwood) 2014 Jun;33(6):1103-1104. [CrossRef] [Medline]
- Harte RP, Glynn LG, Broderick BJ, Rodriguez-Molinero A, Baker PM, McGuiness B, et al. Human centred design considerations for connected health devices for the older adult. J Pers Med 2014 Jun 4;4(2):245-281 [FREE Full text] [CrossRef] [Medline]
- Harte R, Quinlan LR, Glynn L, Rodríguez-Molinero A, Baker PM, Scharf T, et al. Human-centered design study: enhancing the usability of a mobile phone app in an integrated falls risk detection system for use by older adult users. JMIR Mhealth Uhealth 2017 May 30;5(5):e71 [FREE Full text] [CrossRef] [Medline]
- Pelletier A, Jethwani K, Bello H, Kvedar J, Grant R. Implementing a web-based home monitoring system within an academic health care network: barriers and facilitators to innovation diffusion. J Diabetes Sci Technol 2011 Jan 1;5(1):32-38 [FREE Full text] [CrossRef] [Medline]
- Casey M, Hayes PS, Heaney D, Dowie L, Ólaighin G, Matero M, et al. Implementing transnational telemedicine solutions: a connected health project in rural and remote areas of six northern periphery countries series on European collaborative projects. Eur J Gen Pract 2013 Mar;19(1):52-58. [CrossRef] [Medline]
- Xie Q, Liu W, Wang S, Han L, Hu B, Wu T. Improvement of a uniqueness-and-anonymity-preserving user authentication scheme for connected health care. J Med Syst 2014 Sep;38(9):91. [CrossRef] [Medline]
- Feied CF, Handler JA, Gillam M, Smith MS. Indistinguishable from magic: health and wellness in a future of sufficiently advanced technology. Stud Health Technol Inform 2009;149:29-48. [Medline]
- Goossen W. Informatics competencies in connected health: annotated bibliography. Stud Health Technol Inform 2017;232:241-251. [Medline]
- Krupinski EA. Innovations and possibilities in connected health. J Am Acad Audiol 2015 Oct;26(9):761-767. [CrossRef] [Medline]
- Singh K, Kvedar JC. Innovations in connected health. Stud Health Technol Inform 2009;149:111-129. [CrossRef] [Medline]
- Maglaveras N, Kilintzis V, Koutkias V, Chouvarda I. Integrated care and connected health approaches leveraging personalised health through big data analytics. Stud Health Technol Inform 2016;224:117-122. [CrossRef] [Medline]
- Sweeney KT, Leamy DJ, Ward TE, McLoone S. Intelligent Artifact Classification for Ambulatory Physiological Signals. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology. 2010 Presented at: EMBS'10; August 31-September 4, 2010; Buenos Aires, Argentina p. 6349-6352. [CrossRef]
- Hay I, Lim K, Wartena F. Interoperability for device manufacturers: building a personal, connected health ecosystem. Biomed Instrum Technol 2012;46(Suppl 2):71-77. [CrossRef] [Medline]
- Caulfield BM. Introduction: review series--connected health. QJM 2013 Aug;106(8):701. [CrossRef] [Medline]
- Loiselle CG, Ahmed S. Is connected health contributing to a healthier population? J Med Internet Res 2017 Nov 10;19(11):e386 [FREE Full text] [CrossRef] [Medline]
- Trout KE, Rampa S, Wilson FA, Stimpson JP. Legal mapping analysis of state telehealth reimbursement policies. Telemed J E Health 2017 Oct;23(10):805-814. [CrossRef] [Medline]
- Carroll N, Richardson I. Mapping a careflow network to assess the connectedness of connected health. Health Informatics J 2019 Mar;25(1):106-125. [CrossRef] [Medline]
- Campo D, Khettab H, Yu R, Genain N, Edouard P, Buard N, et al. Measurement of aortic pulse wave velocity with a connected bathroom scale. Am J Hypertens 2017 Sep 1;30(9):876-883 [FREE Full text] [CrossRef] [Medline]
- Wang J. Mobile and connected health technologies for older adults aging in place. J Gerontol Nurs 2018 Jun 1;44(6):3-5. [CrossRef] [Medline]
- Rothman BS, Gupta RK, McEvoy MD. Mobile technology in the perioperative arena: rapid evolution and future disruption. Anesth Analg 2017 Mar;124(3):807-818. [CrossRef] [Medline]
- Merchant RM, Groeneveld PW. Neighborhood-level disparities in resuscitation and the potential of connected health. JAMA Cardiol 2017 Oct 1;2(10):1118-1119. [CrossRef] [Medline]
- Saranto K, Ronquillo C, Velez O. Nursing competencies for multiple modalities of connected health technologies. Stud Health Technol Inform 2017;232:172-182. [CrossRef] [Medline]
- Kim KW, Lee JD. On the security of two remote user authentication schemes for telecare medical information systems. J Med Syst 2014 May;38(5):17. [CrossRef] [Medline]
- Lee D, Helal S, Anton S, de Deugd S, Smith A. Participatory and persuasive telehealth. Gerontology 2012;58(3):269-281 [FREE Full text] [CrossRef] [Medline]
- Ternullo J, Jethwani K, Lane S, Myint UK, Havasy R, Carter M, et al. Partners healthcare center for connected health. Telemed J E Health 2013 May;19(5):363-367. [CrossRef] [Medline]
- Argent R, Daly A, Caulfield B. Patient involvement with home-based exercise programs: can connected health interventions influence adherence? JMIR Mhealth Uhealth 2018 Mar 1;6(3):e47 [FREE Full text] [CrossRef] [Medline]
- Skiba DJ, Barton AJ, Estes K, Gilliam E, Knapfel S, Lee C, et al. Preparing the next generation of advanced practice nurses for connected care. Stud Health Technol Inform 2016;225:307-313. [Medline]
- Haluza D, Naszay M, Stockinger A, Jungwirth D. Prevailing opinions on connected health in Austria: results from an online survey. Int J Environ Res Public Health 2016 Aug 11;13(8):813 [FREE Full text] [CrossRef] [Medline]
- Barr PJ, Brady SC, Hughes CM, McElnay JC. Public knowledge and perceptions of connected health. J Eval Clin Pract 2014 Jun;20(3):246-254. [CrossRef] [Medline]
- Weinhandl ED, Collins AJ. Relative risk of home hemodialysis attrition in patients using a telehealth platform. Hemodial Int 2018 Jul;22(3):318-327. [CrossRef] [Medline]
- Bollyky JB, Bravata D, Yang J, Williamson M, Schneider J. Remote lifestyle coaching plus a connected glucose meter with certified diabetes educator support improves glucose and weight loss for people with type 2 diabetes. J Diabetes Res 2018;2018:3961730 [FREE Full text] [CrossRef] [Medline]
- Kreuzthaler M, Martínez-Costa C, Kaiser P, Schulz S. Semantic technologies for re-use of clinical routine data. Stud Health Technol Inform 2017;236:24-31. [Medline]
- Goossen-Baremans A, Collins S, Park HA. Semanticification in connected health. Stud Health Technol Inform 2017;232:133-151. [CrossRef] [Medline]
- Sathyanarayana A, Joty S, Fernandez-Luque L, Ofli F, Srivastava J, Elmagarmid A, et al. Sleep quality prediction from wearable data using deep learning. JMIR Mhealth Uhealth 2016 Nov 4;4(4):e125 [FREE Full text] [CrossRef] [Medline]
- Helal A, Cook DJ, Schmalz M. Smart home-based health platform for behavioral monitoring and alteration of diabetes patients. J Diabetes Sci Technol 2009 Jan;3(1):141-148 [FREE Full text] [CrossRef] [Medline]
- Fernandez-Luque L, Vilmarlund V, Borycki E, Schulz S, Kuziemsky C, Marschollek M, et al. Social media as catalyzer for connected health: hype or hope? Perspectives from IMIA working groups. In: Sermeus W, Procter PM, Weber P, editors. Nursing Informatics 2016: eHealth for All: Every Level Collaboration - From Project to Realization. Amsterdam, Netherlands: IOS Press; 2016:602-604.
- Thomas S, Walsh D, Shrotriya S, Aktas A, Hullihen B, Estfan B, et al. Symptoms, quality of life, and daily activities in people with newly diagnosed solid tumors presenting to a medical oncologist. Am J Hosp Palliat Care 2017 Aug;34(7):611-621. [CrossRef] [Medline]
- Gladden C, Beck L, Chandler D. Tele-audiology: expanding access to hearing care and enhancing patient connectivity. J Am Acad Audiol 2015 Oct;26(9):792-799. [CrossRef] [Medline]
- Landers SH. The case for 'connected health' at home. Cleve Clin J Med 2013 Jan;80(Electronic Suppl 1):eS27-eS29. [CrossRef] [Medline]
- Ansary A, Azuma A, Komatireddy R, Barrett PM. The connected health of cardiovascular medicine: current status and future directions. QJM 2013 Nov;106(11):979-982 [FREE Full text] [CrossRef] [Medline]
- Agboola SO, Ju W, Elfiky A, Kvedar JC, Jethwani K. The effect of technology-based interventions on pain, depression, and quality of life in patients with cancer: a systematic review of randomized controlled trials. J Med Internet Res 2015 Mar 13;17(3):e65 [FREE Full text] [CrossRef] [Medline]
- Agboola SO, Ball M, Kvedar JC, Jethwani K. The future of connected health in preventive medicine. QJM 2013 Sep;106(9):791-794. [CrossRef] [Medline]
- Ni M, Brown LG, Lawler D, Ellis TD, Deangelis T, Latham NK, et al. The rehabilitation enhancing aging through connected health (REACH) study: study protocol for a quasi-experimental clinical trial. BMC Geriatr 2017 Sep 20;17(1):221 [FREE Full text] [CrossRef] [Medline]
- Allaert FA, Mazen NJ, Legrand L, Quantin C. The tidal waves of connected health devices with healthcare applications: consequences on privacy and care management in European healthcare systems. BMC Med Inform Decis Mak 2017 Jan 17;17(1):10 [FREE Full text] [CrossRef] [Medline]
- Tharmalingam S, Hagens S, Zelmer J. The value of connected health information: perceptions of electronic health record users in Canada. BMC Med Inform Decis Mak 2016 Jul 16;16:93 [FREE Full text] [CrossRef] [Medline]
- Deng Y, Liu NY, Tsow F, Xian X, Krajmalnik-Brown R, Tao N, et al. Tracking personal health-environment interaction with novel mobile sensing devices. Sensors (Basel) 2018 Aug 14;18(8):E2670 [FREE Full text] [CrossRef] [Medline]
- Weaver SJ, Che XX, Petersen LA, Hysong SJ. Unpacking care coordination through a multiteam system lens: a conceptual framework and systematic review. Med Care 2018 Mar;56(3):247-259. [CrossRef] [Medline]
- Kvedar JC, Hwang J, Moorhead T, Orlov LM, Ubel PA. Up from crisis: overhauling healthcare information, payment, and delivery in extraordinary times. Dialogue with featured speakers from the 6th annual connected health symposium. Telemed J E Health 2009 Sep;15(7):634-641. [CrossRef] [Medline]
- Aldeer M, Martin RP. Medication Adherence Monitoring Using Modern Technology. In: Proceedings of the 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference. 2017 Presented at: UEMCON'17; October 19-21, 2017; New York, USA p. 491-497. [CrossRef]
- Härmä A, Helaoui R. Probabilistic Scoring of Validated Insights for Personal Health Services. In: Proceedings of the Symposium Series on Computational Intelligence (SSCI). 2016 Presented at: SSCI'16; December 6-9, 2016; Athens, Greece p. 1-6. [CrossRef]
- Majma N, Babamir SM, Monadjemi A. Utilizing Fuzzy Colored Petri-Nets to Monitor Cardiac Pacemaker Behavior. In: Proceedings of the 10th International Conference on Application of Information and Communication Technologies. 2016 Presented at: AICT'16; October 12-14, 2016; Baku, Azerbaijan p. 1. [CrossRef]
- Ahouandjinou AS, Assogba K, Motamed C. Smart and Pervasive ICU Based-IoT for Improving Intensive Health Care. In: Proceedings of the International Conference on Bio-engineering for Smart Technologies. 2016 Presented at: BioSMART'16; December 4-7, 2016; Dubai, United Arab Emirates p. 1-4. [CrossRef]
- Djelouat H, Baali H, Amira A, Bensaali F. Joint Sparsity Recovery for Compressive Sensing Based EEG System. In: Proceedings of the 17th International Conference on Ubiquitous Wireless Broadband. 2017 Presented at: ICUWB'17; September 12-15, 2017; Salamanca, Spain p. 1-5. [CrossRef]
- Santos DF, Perkusich A, Almeida HO. Standard-Based and Distributed Health Information Sharing for mHealth IoT Systems. In: Proceedings of the 16th International Conference on e-Health Networking, Applications and Services. 2014 Presented at: Healthcom'14; October 15-18, 2014; Natal, Brazil p. 94-98. [CrossRef]
- Bellagente P, Depari A, Ferrari P, Flammini A, Sisinni E, Rinaldi S. M3IoT — Message-Oriented Middleware for M-health Internet of Things: Design and Validation. In: Proceedings of the International Instrumentation and Measurement Technology Conference. 2018 Presented at: I2MTC'18; May 14-17, 2018; Houston, TX, USA p. 1-6. [CrossRef]
- Neggazi M, Amira A, Hamami L. A Wireless Reconfigurable System for Falls Detection. In: Proceedings of the 11th International Conference on Information Science, Signal Processing and their Applications. 2012 Presented at: ISSPA'12; July 2-5, 2012; Montreal, QC, Canada p. 77-82. [CrossRef]
- Karamitsios K, Orphanoudakis T. Efficient IoT Data Aggregation for Connected Health Applications. In: Proceedings of the Symposium on Computers and Communications (ISCC). 2017 Presented at: ISCC'17; July 3-6, 2017; Heraklion, Greece p. 1182-1185. [CrossRef]
- Sinharay A, Ghosh D, Deshpande P, Alam S, Banerjee R, Pal A. Smartphone Based Digital Stethoscope for Connected Health--A Direct Acoustic Coupling Technique. In: Proceedings of the First International Conference on Connected Health: Applications, Systems and Engineering Technologies. 2016 Presented at: CHASE'16; June 27-29, 2016; Washington, DC, USA p. 193-198. [CrossRef]
- Aldeer M, Martin RP, Howard RE. PillSense: Designing a Medication Adherence Monitoring System Using Pill Bottle-Mounted Wireless Sensors. In: Proceedings of the International Conference on Communications Workshops (ICC Workshops). 2018 Presented at: ICC Workshops'18; May 20-24, 2018; Kansas City, MO, USA p. 1-6. [CrossRef]
- Daponte P, Lamonaca F, Picariello F, de Vito L, Mazzilli G, Tudosa I. A Survey of Measurement Applications Based on IoT. In: Proceedings of the Workshop on Metrology for Industry 4.0 and IoT. 2018 Presented at: IEEE'18; April 16-18, 2018; Brescia, Italy p. 1-6. [CrossRef]
- Starič KD, Bukovec P, Caulfield B, Bogdanova AM, Belani H. ICT-Assisted Personalized Therapy and Rehabilitation in Urinary Incontinence. In: Proceedings of the 14th International Conference on Telecommunications. 2017 Presented at: ConTEL'17; June 28-30, 2017; Zagreb, Croatia p. 69-74. [CrossRef]
- Chaher Y, Belaud JP, Pingaud H. Managing Open Innovation in Connected Health Through a Living Lab. In: Proceedings of the International Conference on Engineering, Technology and Innovation (ICE/ITMC). 2017 Presented at: ICE/ITMC'17; June 27-29, 2017; Funchal, Portugal p. 577-583. [CrossRef]
- da Silva JM, Oliveira C, Mendes B, Dias R, Marques T. Design for Dependability and Autonomy of a Wearable Cardiac and Coronary Monitor. In: Proceedings of the Euromicro Conference on Digital System Design. 2015 Presented at: DSD'15; August 26-28, 2015; Funchal, Portugal p. 567-570. [CrossRef]
- Barbosa P, Queiroz J, Santos D, Figueiredo A, Leite F, Galdino K. RE4CH: Requirements Engineering for Connected Health. In: Proceedings of the 31st International Symposium on Computer-Based Medical Systems. 2018 Presented at: CBMS'18; June 18-21, 2018; Karlstad, Sweden p. 292-297. [CrossRef]
- Hassanalieragh M, Page A, Soyata T, Sharma G, Aktas M, Mateos G, et al. Health Monitoring and Management Using Internet-of-Things (IoT) Sensing with Cloud-Based Processing: Opportunities and Challenges. In: Proceedings of the International Conference on Services Computing. 2015 Presented at: SCC'15; June 27- July 2, 2015; New York, NY, USA p. 285-292. [CrossRef]
- Carroll N. Key success factors for smart and connected health software solutions. Computer 2016 Nov;49(11):22-28. [CrossRef]
- Liu J, Zhang C, Fang Y. EPIC: a differential privacy framework to defend smart homes against internet traffic analysis. IEEE Internet Things J 2018 Apr;5(2):1206-1217. [CrossRef]
- Djelouat H, Baali H, Amira A, Bensaali F. CS-Based Fall Detection for Connected Health Applications. In: Proceedings of the Fourth International Conference on Advances in Biomedical Engineering. 2017 Presented at: ICABME'17; October 19-21, 2017; Beirut, Lebanon p. 1-4. [CrossRef]
- Stephanie L. Singapore’s NEHR: Challenges on the Path to Connected Health. In: Proceedings of the International Conference on Industrial Engineering and Engineering Management. 2017 Presented at: IEEM'17; December 10-13, 2017; Singapore, Malaysia p. 1128-1132. [CrossRef]
- Giunti G, Guisado-Fernandez E, Caulfield B. Connected Health in Multiple Sclerosis a Mobile Applications Review. In: Proceedings of the 30th International Symposium on Computer-Based Medical Systems. 2017 Presented at: CBMS'17; June 22-24, 2017; Thessaloniki, Greece p. 660-665. [CrossRef]
- Kilintzis V, Maramis C, Maglaveras N. Wrist Sensors — An Application to Acquire Sensory Data From Android Wear® Smartwatches for Connected Health. In: Proceedings of the International Conference on Biomedical & Health Informatics. 2017 Presented at: BHI'17; February 16-19, 2017; Orlando, FL, USA p. 125-128. [CrossRef]
- Lim YY, Garcia MS, Cuneen M, Thompson G, Assem H, Kenny L, et al. OP 4 learning to evaluate and manage antenatal blood pressure at home (LEANBH). Pregnancy Hypertens 2017 Jul;9:10-11. [CrossRef]
- Gao J, Yi P, Chi Z, Zhu T. A smart medical system for dynamic closed-loop blood glucose-insulin control. Smart Health 2017 Jun;1-2:18-33. [CrossRef]
- Zhai X, Ali AA, Amira A, Bensaali F. ECG encryption and identification based security solution on the Zynq SoC for connected health systems. J Parallel Distr Com 2017 Aug;106:143-152. [CrossRef]
- Santos DF, Almeida HO, Perkusich A. A personal connected health system for the internet of things based on the constrained application protocol. Comput Electr Eng 2015 May;44:122-136. [CrossRef]
- Charlon Y, Campo E, Brulin D. Design and evaluation of a smart insole: application for continuous monitoring of frail people at home. Expert Syst Appl 2018 Apr;95:57-71. [CrossRef]
- Barik RK, Dubey AC, Tripathi A, Pratik T, Sasane S, Lenka RK, et al. Mist data: leveraging mist computing for secure and scalable architecture for smart and connected health. Procedia Comput Sci 2018;125:647-653. [CrossRef]
- Lim YY, Garcia MS, Cuneen M, Mattson M, Thompson G, Assem H, et al. P 47 learning to evaluate and manage antenatal blood pressure at home (LEANBH). Pregnancy Hypertens 2017 Jul;9:58-59. [CrossRef]
- Dowd WN, Cowell AJ, Regan D, Moran K, Slevin P, Doyle G, et al. An exploratory cost-effectiveness analysis of the connected health intervention to improve care for people with dementia: a simulation analysis. Health Serv Outcomes Res Method 2017 Dec 15;18(1):47-62. [CrossRef]
- Fitzgerald S, Kachersky L, Saldanha N, Chung E, Farrell L, Laud G, et al. The Dark Side of Connected Health Technology: How Connectivity Creates Exercise Addiction Among Conscientious Users. In: Proceedings of The Association for Consumer Research Conference. 2016 Presented at: ACR'16; October 27-30, 2016; Berlin,Germany.
- Battistella R, Burchfield D. The future of employment-based health insurance. J Healthc Manag 2000;45(1):46-56; discussion 56. [Medline]
- Gross N, Connolly N, McNamara P. The Case Centre. 2015. Connected Health Technology: Private Pharmacies Competing Innovatively in Ireland URL: https://www.thecasecentre.org/main/products/view?id=131345 [accessed 2019-09-02]
- Mountford N, Kessie T. Towards a more holistic understanding of whole organizational networks: anthropological approaches in evolving markets. Electron J Bus Res Methods 2017;15(2):74-84 [FREE Full text]
- Alchihabi A, Dervis A, Ever E, Al-Turjman F. A generic framework for optimizing performance metrics by tuning parameters of clustering protocols in WSNs. Wireless Netw 2018 Jan 25;25(3):1031-1046. [CrossRef]
- Bucci S, Barrowclough C, Ainsworth J, Morris R, Berry K, Machin M, et al. Using mobile technology to deliver a cognitive behaviour therapy-informed intervention in early psychosis (Actissist): study protocol for a randomised controlled trial. Trials 2015 Sep 10;16:404 [FREE Full text] [CrossRef] [Medline]
- Burmaoglu S, Saritas O, Kıdak LB, Berber İ. Evolution of connected health: a network perspective. Scientometrics 2017 Jun 15;112(3):1419-1438. [CrossRef]
- Hassan L, Swarbrick C, Sanders C, Parker A, Machin M, Tully MP, et al. Tea, talk and technology: patient and public involvement to improve connected health 'wearables' research in dementia. Res Involv Engagem 2017;3:12 [FREE Full text] [CrossRef] [Medline]
- McGrath D, Greene BR, Sheehan K, Walsh L, Kenny RA, Caulfield B. Stability of daily home-based measures of postural control over an 8-week period in highly functioning older adults. Eur J Appl Physiol 2015 Feb;115(2):437-449. [CrossRef] [Medline]
- O’Neill SA, Mason S, Parente G, Donnelly MP, Nugent CD, McClean S, et al. Video reminders as cognitive prosthetics for people with dementia. Ageing Int 2010 Nov 23;36(2):267-282. [CrossRef]
- Carroll N, Travers M, Richardson I. Connecting Multistakeholder Analysis Across Connected Health Solutions. In: Proceedings of the International Joint Conference on Biomedical Engineering Systems and Technologies. 2016 Presented at: BIOSTEC'16; February 21-23, 2016; Rome, Italy p. 319-339. [CrossRef]
- O'Leary P, Buckley P, Richardson I. Modelling Care Pathways in a Connected Health Setting. In: Proceedings of the International Symposium on Foundations of Health Informatics Engineering and Systems. 2013 Presented at: FHIES'13; August 21-23, 2013; Macau, China p. 32-40. [CrossRef]
- Myneni S, Rogith D, Franklin A. Digilego: A Standardized Analytics-Driven Consumer-Oriented Connected Health Framework. In: Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. 2018 Presented at: SBP-BRiMS'18; July 10-13, 2018; Washington DC, USA p. 263-273. [CrossRef]
- Synnott J, McComb S, Nugent C, McLaughlin J. NI-CHIC: A Model for Academic Engagement with Industry. In: Proceedings of the Conference on the Ambient Intelligence for Health. 2015 Presented at: AmIHEALTH'15; December 1-4, 2015; Puerto Varas, Chile p. 258-263. [CrossRef]
- Weitzel M, Smith A, Lee D, de Deugd S, Helal S. Participatory Medicine: Leveraging Social Networks in Telehealth Solutions. In: Proceedings of the International Conference on Smart Homes and Health Telematics. 2009 Presented at: ICOST'09; July 1-3, 2009; Tours, France p. 40-47. [CrossRef]
- Galway L, Zhang S, Nugent C, McClean S, Finlay D, Scotney B. Utilizing Wearable Sensors to Investigate the Impact of Everyday Activities on Heart Rate. In: Proceedings of the International Conference on Smart Homes and Health Telematics. 2011 Presented at: ICOST'11; June 20-22, 2011; Montreal, QC, Canada p. 184-191. [CrossRef]
- Leijdekkers P, Gay V. Improving User Engagement by Aggregating and Analysing Health and Fitness Data on a Mobile App. In: Proceedings of the International Conference on Smart Homes and Health Telematics. 2015 Presented at: ICOST'15; June 10-12, 2015; Geneva, Switzerland p. 325-330. [CrossRef]
- Alkobaisi S, Bae WD, Narayanappa S. SCHAS: A Visual Evaluation Framework for Mobile Data Analysis of Individual Exposure to Environmental Risk Factors. In: Proceedings of the International Symposium on Spatial and Temporal Databases. 2015 Presented at: SSTD'15; August 26-28, 2015; Hong Kong, China p. 484-490. [CrossRef]
- Carroll N, Richardson I. Aligning Healthcare Innovation and Software Requirements Through Design Thinking. In: Proceedings of the International Workshop on Software Engineering in Healthcare Systems. 2016 Presented at: SEHS'16; May 14-22, 2016; Austin, Texas p. 1-7. [CrossRef]
- Moon J, Yang H, Lee Y, Won D. Improvement of User Authentication Scheme Preserving Uniqueness and Anonymity for Connected Health Care. In: Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication. 2017 Presented at: IMCOM'17; January 5-7, 2017; Beppu, Japan. [CrossRef]
- Richardson I, O'Mahony J, Howarth P, O'Connor P, Glenny L. Connected Health: From Rural Ireland to Rural India. In: Proceedings of the International Workshop on Software Engineering in Healthcare Systems. 2016 Presented at: SEHS''16; May 14-22, 2016; Austin, Texas p. 39-42. [CrossRef]
- O'Sullivan P, Connolly A, Carroll N, Richardson I. IBM's Smarter Care: Challenges and Strategies. In: Proceedings of the 20th International Conference on Evaluation and Assessment in Software Engineering. 2016 Presented at: EASE'16; June 1-3, 2016; Limerick, Ireland. [CrossRef]
- Kuziemsky C, Abbas RM, Carroll N. Toward a Connected Health Delivery Framework. In: Proceedings of the International Workshop on Software Engineering in Healthcare Systems. 2018 Presented at: SEHS'18; May 28, 2018; Gothenburg, Sweden p. 46-49. [CrossRef]
- Aldeer M, Martin RP, Howard RE. Tackling the Fidelity-Energy Trade-Off in Wireless Body Sensor Networks. In: Proceedings of the International Conference on Connected Health: Applications, Systems and Engineering Technologies. 2017 Presented at: CHASE'17; July 17-19, 2017; Philadelphia, PA, USA p. 1-7. [CrossRef]
- Rodolfo I, Laranjo L, Correia N, Duarte C. Design Strategy for a National Integrated Personal Health Record. In: Proceedings of the 8th Nordic Conference on Human-Computer Interaction: Fun, Fast, Foundational. 2014 Presented at: NordiCHI'14; October 26-30, 2014; Helsinki, Finland p. 411-420. [CrossRef]
- Yuan C, Kropczynski J, Wirth R, Rosson MB, Carroll JM. Investigating Older Adults' Social Networks and Coproduction Activities for Health. In: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare. 2017 Presented at: PervasiveHealth'17; May 23-26, 2017; Barcelona, Spain p. 68-77. [CrossRef]
- Karamitsios K, Orphanoudakis T, Dagiuklas T. Evaluation of IoT-Based Distributed Health Management Systems. In: Proceedings of the 20th Pan-Hellenic Conference on Informatics. 2016 Presented at: PCI'16; November 10-12, 2016; Patras, Greece. [CrossRef]
- Veiga JJ, Ward TE. Data Collection Requirements for Mobile Connected Health an End User Development Approach. In: Proceedings of the 1st International Workshop on Mobile Development. 2016 Presented at: Mobile!'16; October 31, 2016; Amsterdam, Netherlands p. 23-30. [CrossRef]
- Srinivasan K, Currim F, Ram S, Lindberg C, Sternberg E, Skeath P, et al. Feature Importance and Predictive Modeling for Multi-Source Healthcare Data With Missing Values. In: Proceedings of the 6th International Conference on Digital Health Conference. 2016 Presented at: DH'16; April 11-13, 2016; Montréal, Québec, Canada p. 47-54. [CrossRef]
- Abdullah NN, Clancey WJ, Raj A, Zain AZ, Khalid KF, Ooi A. Application of a Double-Loop Learning Approach for Healthcare Systems Design in an Emerging Market. In: Proceedings of the International Workshop on Software Engineering in Healthcare Systems. 2018 Presented at: SEHS'18; May 28, 2018; Gothenburg, Sweden p. 10-13. [CrossRef]
- Cao Y, Hou P, Brown D, Wang J, Chen S. Distributed Analytics and Edge Intelligence: Pervasive Health Monitoring at the Era of Fog Computing. In: Proceedings of the 2015 Workshop on Mobile Big Data. 2015 Presented at: Mobidata'15; June 21, 2015; Hangzhou, China p. 43-48. [CrossRef]
- O'Leary P, Carroll N, Clarke P, Richardson I. Untangling the Complexity of Connected Health Evaluations. In: Proceedings of the 2015 International Conference on Healthcare Informatics. 2015 Presented at: ICHI'15; October 21-23, 2015; Dallas, TX, USA p. 272-281. [CrossRef]
- Davey SM, Brennan M, Meenan BJ, McAdam R. A Framework to Manage the Innovation Strategies of New Technology Based Firms. In: First International Technology Management Conference. 2011 Presented at: ICE'11; June 27-30, 2011; San Jose, CA, USA p. 1007-1013. [CrossRef]
- Al Disi M, Djelouat H, Amira A, Bensaali F. The Accuracy and Efficacy of Real-Time Compressed ECG Signal Reconstruction on a Heterogeneous Multicore Edge-Device. In: Proceedings of the 21st Euromicro Conference on Digital System Design. 2018 Presented at: DSD'18; August 29-31, 2018; Prague, Czech Republic p. 458-463. [CrossRef]
- Nyberg T, Xiong G, Luostarinen J. Connected Health Services Internet, Mobile and Wireless Technologies in Healthcare. In: Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics. 2011 Presented at: SOLI'11; July 10-12, 2011; Beijing, China p. 220-224. [CrossRef]
- Barbosa P, Leite F, Santos D, Figueiredo A, Galdino K. Introducing Traceability Information Models in Connected Health Projects. In: Proceedings of the 31st International Symposium on Computer-Based Medical Systems. 2018 Presented at: CNMS'18; July 23, 2018; Karlstad, Sweden p. 18-23. [CrossRef]
- Saranummi N. In the spotlight: health information systems--PHR and value based healthcare. IEEE Rev Biomed Eng 2009;2:15-17. [CrossRef] [Medline]
- Parvin S, Gawanmeh A, Venkatraman S, Alwadi A, Al-Karaki JN. Efficient Lightweight Mechanism for Node Authentication in WBSN. In: Advances in Science and Engineering Technology International Conferences (ASET). 2018 Presented at: ASET'18; February 6-April 5, 2018; Abu Dhabi, United Arab Emirates p. 1-6. [CrossRef]
- Martins AF, Santos DF, Perkusich A, Almeida HO. IEEE 11073 And Connected Health: Preparing Personal Health Devices for the Internet. In: Proceedings of the International Conference on Consumer Electronics. 2014 Presented at: ICCE'14; January 10-13, 2014; Las Vegas, NV, USA p. 274-275. [CrossRef]
- Nambiar AR, Reddy N, Dutta D. Connected Health: Opportunities and Challenges. In: Proceedings of the International Conference on Big Data. 2017 Presented at: Big Data'17; December 11-14, 2017; Boston, MA, USA p. 1658-1662. [CrossRef]
- Gawanmeh A. Open Issues in Reliability, Safety, and Efficiency of Connected Health. In: Proceedings of the First International Conference on Connected Health: Applications, Systems and Engineering Technologies. 2016 Presented at: CHASE'16; June 27-29, 2016; Washington, DC, USA p. 1-6. [CrossRef]
- Stenhaug M, Johansen HD, Johansen D. Transforming Healthcare Through Life-Long Personal Digital Footprints. In: Proceedings of the First International Conference on Connected Health: Applications, Systems and Engineering Technologies. 2016 Presented at: CHASE'16; June 27-29, 2016; Washington, DC, USA p. 36-41. [CrossRef]
- Ali AA, Zhai X, Amira A, Bensaali F, Ramzan N. Heterogeneous Implementation of ECG Encryption and Identification on the Zynq SoC. In: Proceedings of the 24th Annual International Symposium on Field-Programmable Custom Computing Machines. 2016 Presented at: FCCM'16; May 1-3, 2016; Washington, DC, USA p. 139. [CrossRef]
- Gomes YF, Santos DF, Almeida HO, Perkusich A. Integrating MQTT and ISO/IEEE 11073 For Health Information Sharing in the Internet of Things. In: Proceedings of the International Conference on Consumer Electronics. 2015 Presented at: ICCE'15; January 9-12, 2015; Las Vegas, NV, USA p. 200-201. [CrossRef]
- Bellekens X, Hamilton A, Seeam P, Nieradzinska K, Franssen Q, Seeam A. Pervasive eHealth Services a Security and Privacy Risk Awareness Survey. In: Proceedings of the International Conference On Cyber Situational Awareness, Data Analytics And Assessment. 2016 Presented at: CyberSA'16; June 13-14, 2016; London, UK p. 1-4. [CrossRef]
- Anumala H, Busetty SM. Distributed Device Health Platform Using Internet of Things Devices. In: Proceedings of the International Conference on Data Science and Data Intensive Systems. 2015 Presented at: DSDIS'15; December 11-13, 2015; Sydney, NSW, Australia p. 525-531. [CrossRef]
- O'Quigley C, Sabourin M, Coyle S, Connolly J, Condall J, Curran K, et al. Characteristics of a Piezo-Resistive Fabric Stretch Sensor Glove for Home-Monitoring of Rheumatoid Arthritis. In: Proceedings of the 11th International Conference on Wearable and Implantable Body Sensor Networks Workshops. 2014 Presented at: BSN'14; June 16-19, 2014; Zurich, Switzerland p. 23-26. [CrossRef]
- Baali H, Zhai X, Djelouat H, Amira A, Bensaali F. Inequality indexes as sparsity measures applied to ventricular ectopic beats detection and its efficient hardware implementation. IEEE Access 2018;6:9464-9472. [CrossRef]
- Antoniou PE, Rivera-Romero O, Karagianni M, Bamidis PD. Towards Evidence Based M-Health Application Design in Cancer Patient Healthy Lifestyle Interventions. In: Proceedings of the 30th International Symposium on Computer-Based Medical Systems. 2017 Presented at: CBMS'17; June 22-24, 2017; Thessaloniki, Greece p. 690-695. [CrossRef]
- Asim M, Petkovi M, Qu M, Wang C. An Interoperable Security Framework for Connected Healthcare. In: Proceedings of the Consumer Communications and Networking Conference. 2011 Presented at: CCNC'11; January 9-12, 2011; Las Vegas, NV, USA p. 116-120. [CrossRef]
- Maramis C, Chouvarda I, Maglaveras N, Isomursu M. Introducing a Framework for Reporting Behavioral Informatics Interventions. In: Proceedings of the International Conference on Telecommunications. 2017 Presented at: ConTEL'17; June 28-30, 2017; Zagreb, Croatia p. 63-68. [CrossRef]
- Cao Y, Chen S, Hou P, Brown D. FAST: A Fog Computing Assisted Distributed Analytics System to Monitor Fall for Stroke Mitigation. In: Proceedings of the International Conference on Networking, Architecture and Storage. 2015 Presented at: NAS'15; August 6-7, 2015; Boston, MA, USA p. 2-11. [CrossRef]
- Silvello A. How connected insurance is reshaping the health insurance industry. Stud Health Technol Inform 2018;251:179-182. [Medline]
- Tonheim AN, Babic A. Assessing information needs for a personal multiple sclerosis application. Stud Health Technol Inform 2018;247:486-490. [Medline]
- Vaughan PW. Quality and innovation: redesigning a coordinated and connected health system. Healthc Pap 2017;16(3):35-39. [CrossRef] [Medline]
- Van Alstin CM. Virtual reality: coming to a hospital near you. VR may take connected health to a whole new level. Health Manag Technol 2016 Oct;37(3):6-9. [Medline]
- Skiba DJ. Connected health 2015: the year of virtual patient visits. Nurs Educ Perspect 2015;36(2):131-133. [Medline]
- Leskinen H, Korpelainen J, Mäkiniemi M. The university hospital as a hub for connected health: Oulu Healthworld, Northern Scandinavia. World Hosp Health Serv 2012;48(4):20-24. [Medline]
- Glaser J. Tipping point. The arrival of connected health. J Healthc Inf Manag 2008;22(4):21-23. [Medline]
- Mathur A, Kvedar JC, Watson AJ. Connected health: a new framework for evaluation of communication technology use in care improvement strategies for type 2 diabetes. Curr Diabetes Rev 2007 Nov;3(4):229-234. [CrossRef] [Medline]
- Whitlinger D, Ayyagari D, McClure D, Fisher J, Lopez F. Straight talk. Collaboration fosters connected health: a new paradigm of proactive heathcare. Mod Healthc 2007 May 21;37(21):47-50. [Medline]
- Gerdsen F, Müeller S, Jablonski S, Prokosch HU. Standardized exchange of medical data between a research database, an electronic patient record and an electronic health record using CDA/SCIPHOX. AMIA Annu Symp Proc 2005:963 [FREE Full text] [Medline]
- Noroozi B, Morshed BI. Coil Distance and Angle Misalignment Effects on the Mutual Inductance for 13.56 MHz WRAP Sensors. In: Proceedings of the United States National Committee of URSI National Radio Science Meeting. 2018 Presented at: USNC-URSI NRSM'18; January 4-7, 2018; Boulder, CO, USA p. 1-2. [CrossRef]
- Rahimi N, Ibarra M. A Review of Multiple User Center Design Methods for New Product Development in Smart and Connected Health Applications. In: Proceedings of the Conference on Portland International Center for Management of Engineering and Technology; Infrastructure and Service Integration. 2014 Presented at: PICMET'14; July 27-31, 2014; Kanazawa, Japan p. 3498-3510.
- Pandas. Python Data Analysis Library URL: https://pandas.pydata.org/ [accessed 2019-07-16]
- Matplotlib: Python Plotting. URL: https://matplotlib.org/ [accessed 2019-07-16]
- Montesi M, Owen JM. From conference to journal publication: how conference papers in software engineering are extended for publication in journals. J Am Soc Inf Sci 2008 Mar;59(5):816-829. [CrossRef]
- Knight LV, Steinbach TA. Selecting an appropriate publication outlet: a comprehensive model of journal selection criteria for researchers in a broad range of academic disciplines. Int J Doctoral Stud 2008;3:59-79. [CrossRef]
- Donovan SK. The importance of resubmitting rejected papers. J Sch Publ 2007;38(3):151-155. [CrossRef]
- CATCH ITN - eHealth for Cancer Patients. URL: https://www.catchitn.eu [accessed 2019-07-16]
- Community Research and Development Information Service. Connected Health Early Stage Researcher Support System URL: https://cordis.europa.eu/project/rcn/198323/factsheet/en [accessed 2019-07-16]
- European Connected Health Alliance | (ECHAlliance). URL: https://echalliance.com/ [accessed 2019-07-16]
- World Health Organization. 2015. Ageing and Life-Course: World Report on Ageing and Health 2015 URL: http://www.who.int/ageing/events/world-report-2015-launch/en/ [accessed 2019-07-16]
- Bloom DE, Canning D, Fink G. Implications of population ageing for economic growth. Oxf Rev Econ Policy 2011 May 13;26(4):583-612. [CrossRef]
- Farahani B, Firouzi F, Chang V, Badaroglu M, Constant N, Mankodiya K. Towards fog-driven IoT ehealth: promises and challenges of IoT in medicine and healthcare. Future Gener Comp Sy 2018 Jan;78:659-676. [CrossRef]
- Statista. Number of Smartphones Sold to End Users Worldwide From 2007 to 2020 (in Million Units) URL: https://www.statista.com/statistics/263437/global-smartphone-sales-to-end-users-since-2007/ [accessed 2019-07-16]
- Statista. Forecast Wearables Unit Shipments Worldwide From 2014 to 2023 (in Millions) URL: https://www.statista.com/statistics/437871/wearables-worldwide-shipments/ [accessed 2019-07-16]
- Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I. Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comp Sy 2009 Jun;25(6):599-616. [CrossRef]
- World Health Organization. Global Diffusion of eHealth: Making Universal Health Coverage Achievable Report of the Third Global Survey on eHealth. Geneva, Switzerland: World Health Organization; 2016.
- Rizzatti L. EE Times | Electronic Engineering Times. 2016. Digital Data Storage is Undergoing Mind-Boggling Growth URL: https://www.eetimes.com/author.asp?section_id=36&doc_id=1330462 [accessed 2019-07-16]
- Eisenhardt KM. Building theories from case study research. Acad Manage Rev 1989 Oct 1;14(4):532-550. [CrossRef]
- Neergaard H, Ulhøi JP. Handbook of Qualitative Research Methods in Entrepreneurship. Cheltenham, United Kingdom: Edward Elgar Publishing; 2007.
- Yin RK. Case Study Research: Design and Methods. Thousand Oaks, CA: Sage Publications; 2009.
- Kerlinger FN. Foundations of Behavioural Research: Educational, Psychological and Sociological Enquiry. New York, United States: Holt, Rinehart and Winston Publishers; 1986.
- Klein JT. Interdisciplinarity: History, Theory, and Practice. Detroit, Michigan, United States: Wayne State University Press; 1990.
- Bradbeer J. Barriers to interdisciplinarity: disciplinary discourses and student learning. J Geogr High Educ 1999 Nov;23(3):381-396. [CrossRef]
- Wagner KH, Brath H. A global view on the development of non communicable diseases. Prev Med 2012 May(54 Suppl):S38-S41. [CrossRef] [Medline]
- Freyne J, Coyle L, Smyth B, Cunningham P. Relative status of journal and conference publications in computer science. Commun ACM 2010 Nov 1;53(11):124-132. [CrossRef]
- Garousi V, Mesbah A, Betin-Can A, Mirshokraie S. A systematic mapping study of web application testing. Inf Softw Technol 2013 Aug;55(8):1374-1396. [CrossRef]
- Giunti G, Guisado-Fernandez E, Belani H, Lacalle-Remigio JR. Mapping the access of future doctors to health information technologies training in the European union: cross-sectional descriptive study. J Med Internet Res 2019 Aug 12;21(8):e14086 [FREE Full text] [CrossRef] [Medline]
|BMC: BioMed Central|
|CATCH: cancer: activating technology for connected health|
|CH: connected health|
|CHESS: connected health early stage researcher support system|
|COST: Cooperation in Science and Technology|
|DOI: digital object identifier|
|EC: exclusion criteria|
|eHealth: electronic health|
|JMIR: Journal of Medical Internet Research|
|MQ: mapping questions|
|PHR: personal health record|
|QJM: Quarterly Journal of Medicine.|
Edited by M Tilney; submitted 15.04.19; peer-reviewed by I Mircheva, B Chaudhry, C Perrin, MS Aslam, M Reynolds; comments to author 20.06.19; revised version received 27.07.19; accepted 18.08.19; published 25.09.19
©Maria Karampela, Minna Isomursu, Talya Porat, Christos Maramis, Nicola Mountford, Guido Giunti, Ioanna Chouvarda, Fedor Lehocki. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.09.2019.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.