Telemedicine Chapter 21: Telemedicine and Chronic Conditions

This chapter is part of Literature reviews carried out for the Heath Service Executive National Telehealth Steering Group April – July 2020

Systematic Reviews

Lee, Jung-Ah et al (2019) [Systematic Review] Effective Behavioral Intervention Strategies Using Mobile Health Applications for Chronic Disease Management: A Systematic Review[34]

Background: Mobile health (mHealth) has continuously been used as a method in behavioral research to improve self-management in patients with chronic diseases. However, the evidence of its effectiveness in chronic disease management in the adult population is still lacking. We conducted a systematic review to examine the effectiveness of mHealth interventions on process measures as well as health outcomes in randomized controlled trials to improve chronic disease management. Methods: Relevant randomized controlled studies that were published between January 2005 and March 2016 were searched in six databases: PubMed, CINAHL, EMBASE, the Cochrane Library, PsycINFO, and Web of Science. The inclusion criteria were RCTs that conducted an intervention using mobile devices such as smartphones or tablets for adult patients with chronic diseases to examine disease management or health promotion. Results: Of the 12 RCTs reviewed, 10 of the mHealth interventions demonstrated statistically significant improvement in some health outcomes. The most common features of mHealth systems used in the reviewed RCTs were real-time or regular basis symptom assessments, pre-programed reminders, or feedbacks tailored specifically to the data provided by participants via mHealth devices. Most studies developed their own mHealth systems including mobile apps. Training of mHealth systems was provided to participants in person or through paper-based instructions. None of the studies reported the relationship between health outcomes and patient engagement levels on the mHealth system. Conclusions: Findings from mHealth intervention studies for chronic disease management have shown promising aspects, particularly in improving self-management and some health outcomes.

Sprogis, Stephanie K. et al (2019) [Systematic Review] Patient Acceptability of Wearable Vital Sign Monitoring Technologies in the Acute Care Setting: A Systematic Review[35]

Aims and objectives: To examine patient acceptability of wearable vital sign monitoring devices in the acute setting. Background: Wearable vital sign monitoring devices may improve patient safety, yet hospital patients’ acceptability of these devices is largely unreported. Design: A systematic review. Methods: Cumulative Index to Nursing and Allied Health Literature Complete, MEDLINE Complete and EMBASE were searched, supplemented by reference list hand searching. Studies were included if they involved adult hospital patients (≥18 years), a wearable monitoring device capable of assessing ≥1 vital sign, and measured patient acceptability, satisfaction or experience of wearing the device. No date restrictions were enforced. Quality assessments of quantitative and qualitative studies were undertaken using the Downs and Black Checklist for Measuring Study Quality and the Critical Appraisal Skills Programme Qualitative Research Checklist, respectively. Meta-analyses were not possible given data heterogeneity and low research quality. Reporting adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and a Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist was completed. Results: Of the 427 studies screened, seven observational studies met the inclusion criteria. Six studies were of low quality and one was of high quality. In two studies, patient satisfaction was investigated. In the remaining studies, patient experience, patient opinions and experience, patient perceptions and experience, device acceptability, and patient comfort and concerns were investigated. In four studies, patients were mostly accepting of the wearable devices, reporting positive experiences and satisfaction relating to their use. In three studies, findings were mixed. Conclusion: There is limited high-quality research examining patient acceptability of wearable vital sign monitoring devices as an a priori focus in the acute setting. Further understanding of patient perspectives of these devices is required to inform their continued use and development. Relevance to clinical practice: The provision of patient-centred nursing care is contingent on understanding patients’ preferences, including their acceptability of technology use.

Adamse, Corine et al (2018) [Systematic Review] The Effectiveness of Exercise-Based Telemedicine on Pain, Physical Activity and Quality of Life in the Treatment of Chronic Pain: A Systematic Review[36]

Introduction: The aim of this study was to systematically review the evidence on the effectiveness of exercise-based telemedicine in chronic pain. Methods: We searched the Cochrane, PubMed, MEDLINE, EMBASE, CINAHL and PEDRO databases from 2000 to 2015 for randomised controlled trials, comparing exercise-based telemedicine intervention to no intervention or usual care in adults with chronic pain. Primary outcome data were pooled using random effect meta-analysis. Primary outcomes were pain, physical activity (PA), limitations in activities of daily living (ADL) and quality of life (QoL). Secondary outcomes were barriers, facilitators and usability of telemedicine. Results: Sixteen studies were included. Meta-analyses were performed in three subgroups of studies with comparable control conditions. Telemedicine versus no intervention showed significantly lower pain scores (MD -0.57, 95% CI -0.81; -0.34), but not for telemedicine versus usual care (MD -0.08, 95% CI -0.41; 0.26) or in addition to usual care (MD -0.25, 95% CI -1.50; 1.00). Telemedicine compared to no intervention showed non-significant effects for PA (MD 19.93 min/week, 95% CI -5.20; 45.06) and significantly diminished ADL limitations (SMD -0.20, 95% CI -0.29; -0.12). No differences were found for telemedicine in addition to usual care for PA or for ADL (SMD 0.16, 95% CI -0.66; 0.34). Telemedicine versus usual care showed no differences for ADL (SMD 0.08, 95% CI -0.37; 0.53). No differences were found for telemedicine compared to the three control groups for QoL. Limited information was found on the secondary outcomes. Conclusions: Exercise-based telemedicine interventions do not seem to have added value to usual care. As substitution of usual care, telemedicine might be applicable but due to limited quality of the evidence, further exploration is needed for the rapidly developing field of telemedicine.

Albahri, O.S. et al (2018) [Systematic Review] Systematic Review of Real-time Remote Health Monitoring System in Triage and Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations[37]

The new and ground-breaking real-time remote monitoring in triage and priority-based sensor technology used in telemedicine have significantly bounded and dispersed communication components. To examine these technologies and provide researchers with a clear vision of this area, we must first be aware of the utilised approaches and existing limitations in this line of research. To this end, the ScienceDirect, IEEE Xplore and Web of Science databases were checked for articles on triage and priority-based sensor technology in telemedicine. The retrieved articles were filtered according to the type of telemedicine technology explored. A total of 150 articles were selected and classified into two categories. The first category includes reviews and surveys of triage and priority-based sensor technology in telemedicine. The second category includes articles on the three-tiered architecture of telemedicine. Tier 1 represents the users. Sensors acquire the vital signs of the users and send them to Tier 2, which is the personal gateway that uses local area network protocols or wireless body area network. Medical data are sent from Tier 2 to Tier 3, which is the healthcare provider in medical institutes. Then, the motivation for using triage and priority-based sensor technology in telemedicine, the issues related to the obstruction of its application and the development and utilisation of telemedicine are examined on the basis of the findings presented in the literature.

Baig, Mirza Mansoor et al (2017) [Systematic Review] A Systematic Review of Wearable Patient Monitoring Systems – Current Challenges and Opportunities for Clinical Adoption[38]

The aim of this review is to investigate barriers and challenges of wearable patient monitoring (WPM) solutions adopted by clinicians in acute, as well as in community, care settings. Currently, healthcare providers are coping with ever-growing healthcare challenges including an ageing population, chronic diseases, the cost of hospitalization, and the risk of medical errors. WPM systems are a potential solution for addressing some of these challenges by enabling advanced sensors, wearable technology, and secure and effective communication platforms between the clinicians and patients. A total of 791 articles were screened and 20 were selected for this review. The most common publication venue was conference proceedings (13, 54%). This review only considered recent studies published between 2015 and 2017. The identified studies involved chronic conditions (6, 30%), rehabilitation (7, 35%), cardiovascular diseases (4, 20%), falls (2, 10%) and mental health (1, 5%). Most studies focussed on the system aspects of WPM solutions including advanced sensors, wireless data collection, communication platform and clinical usability based on a specific area or disease. The current studies are progressing with localized sensor-software integration to solve a specific use-case/health area using non-scalable and ‘silo’ solutions. There is further work required regarding interoperability and clinical acceptance challenges. The advancement of wearable technology and possibilities of using machine learning and artificial intelligence in healthcare is a concept that has been investigated by many studies. We believe future patient monitoring and medical treatments will build upon efficient and affordable solutions of wearable technology.

Vegesna, Ashok et al (2017) [Systematic Review] Remote Patient Monitoring via Non-Invasive Digital Technologies: A Systematic Review[39]

Background: We conducted a systematic literature review to identify key trends associated with remote patient monitoring (RPM) via noninvasive digital technologies over the last decade. Materials and methods: A search was conducted in EMBASE and Ovid MEDLINE. Citations were screened for relevance against predefined selection criteria based on the PICOTS (Population, Intervention, Comparator, Outcomes, Timeframe, and Study Design) format. We included studies published between January 1, 2005 and September 15, 2015 that used RPM via noninvasive digital technology (smartphones/personal digital assistants [PDAs], wearables, biosensors, computerized systems, or multiple components of the formerly mentioned) in evaluating health outcomes compared to standard of care or another technology. Studies were quality appraised according to Critical Appraisal Skills Programme. Results: Of 347 articles identified, 62 met the selection criteria. Most studies were randomized control trials with older adult populations, small sample sizes, and limited follow-up. There was a trend toward multicomponent interventions (n = 26), followed by smartphones/PDAs (n = 12), wearables (n = 11), biosensor devices (n = 7), and computerized systems (n = 6). Another key trend was the monitoring of chronic conditions, including respiratory (23%), weight management (17%), metabolic (18%), and cardiovascular diseases (16%). Although substantial diversity in health-related outcomes was noted, studies predominantly reported positive findings. Conclusions: This review will help decision makers develop a better understanding of the current landscape of peer-reviewed literature, demonstrating the utility of noninvasive RPM in various patient populations. Future research is needed to determine the effectiveness of RPM via noninvasive digital technologies in delivering patient healthcare benefits and the feasibility of large-scale implementation. Conflict of interest statement: Statement AV is a postdoctoral student from Jefferson College of Population Health and a US HEOR Fellow at Novartis Pharmaceuticals Corporation. MT is a postdoctoral student from Scott and White Health Plan, University of Texas at Austin and a US HEOR Fellow at Novartis Pharmaceuticals Corporation. SA and MA are employees of Novartis Pharmaceuticals Corporation. Novartis Pharmaceuticals Corporation provided funding for this work.

Stephani, Victor et al (2016) [Systematic Review] A Systematic Review of Randomized Controlled Trials of mHealth Interventions Against Non-Communicable Diseases in Developing Countries[40]

Background: The reasons of deaths in developing countries are shifting from communicable diseases towards non-communicable diseases (NCDs). At the same time the number of health care interventions using mobile phones is growing rapidly. We review studies assessing the health-related impacts of mHealth on NCDs in low- and middle-income countries. Methods: A systematic literature search of three major databases was performed in order to identify randomized controlled trials of mHealth interventions. Identified studies were reviewed concerning key characteristics of the trial and the intervention; and the relationship between intervention characteristics and outcomes was qualitatively assessed. Results: The search algorithms retrieved 994 titles. 8 RCTs were included in the review, including a total of 4375 participants. Trials took place mostly in urban areas, tested different interventions ranging from health promotion over appointment reminders and medication adjustments to clinical decision support systems) and included patients with different diseases: diabetes, asthma, hypertension. Except for one study all showed rather positive effects of mHealth interventions on reported outcome measures. Furthermore, our results suggest that particular types of mHealth interventions that were found to have positive effects on patients with communicable diseases and for improving maternal care are likely to be effective also for NCDs. Conclusions: Despite rather positive results of included RCTs, a firm conclusion about the effectiveness of mHealth interventions against NCDs is not yet possible because of the limited number of studies, the heterogeneity of evaluated mHealth interventions and the wide variety of reported outcome measures. More research is needed to better understand the specific effects of different types of mHealth interventions on different types of patients with NCDs in low- and middle-income countries.

Miscellaneous

Bashi, Nazli et al (2020) [Scoping Review] Digital health interventions for chronic diseases: a scoping review of evaluation frameworks[41]

Background: Monitoring and evaluations of digital health (DH) solutions for the management of chronic diseases are quite heterogeneous and evidences around evaluating frameworks are inconsistent. An evidenced-based framework is needed to inform the evaluation process and rationale of such interventions. We aimed to explore the nature, extent and components of existing DH frameworks for chronic diseases. Methods: This review was conducted based on the five steps of Arksey and O’Malley’s scoping review methodology. Out of 172 studies identified from, PubMed, Embase and Web of Science, 11 met our inclusion criteria. The reviewed studies developed DH frameworks for chronic diseases and published between 2010 and 2018. Results: According to WHO guidelines for monitoring and evaluation of DH interventions, we identified seven conceptual frameworks, two results frameworks, one logical framework and one theory of change. The frameworks developed for providing interventions such as self-management, achieving personal goals and reducing relapse for cardiovascular disease, diabetes, chronic obstructive pulmonary disease and severe mental health. A few studies reported evaluation of the frameworks using randomised clinical trials (n=3) and feasibility testing via Likert scale survey (n=2). A wide range of outcomes were reported including access to care, cost-effectiveness, behavioural outcomes, patient-provider communications, technology acceptance and user experience. Conclusion: There is a lack of evidence on the application of consistent DH frameworks. Future research should address the use of evidence-based frameworks into the research design, monitoring and evaluation process. This review explores the nature of DH frameworks for the management of chronic diseases and provides examples to guide monitoring and evaluation of interventions.

Bradway, Meghan et al (2020) [Scoping Review] Methods and Measures Used to Evaluate Patient-Operated Mobile Health Interventions: Scoping Literature Review[42]

Background: Despite the prevalence of mobile health (mHealth) technologies and observations of their impacts on patients’ health, there is still no consensus on how best to evaluate these tools for patient self-management of chronic conditions. Researchers currently do not have guidelines on which qualitative or quantitative factors to measure or how to gather these reliable data. Objective: This study aimed to document the methods and both qualitative and quantitative measures used to assess mHealth apps and systems intended for use by patients for the self-management of chronic noncommunicable diseases. Methods: A scoping review was performed, and PubMed, MEDLINE, Google Scholar, and ProQuest Research Library were searched for literature published in English between January 1, 2015, and January 18, 2019. Search terms included combinations of the description of the intention of the intervention [eg self-efficacy and self-management] and description of the intervention platform [eg mobile app and sensor]. Article selection was based on whether the intervention described a patient with a chronic noncommunicable disease as the primary user of a tool or system that would always be available for self-management. The extracted data included study design, health conditions, participants, intervention type, methods used, and measured qualitative and quantitative data. Results: A total of 31 studies met the eligibility criteria. Studies were classified as either those that evaluated mHealth apps (ie single devices; n=15) or mHealth systems (ie more than one tool; n=17), and one study evaluated both apps and systems. App interventions mainly targeted mental health conditions including Post-Traumatic Stress Disorder, followed by diabetes and cardiovascular and heart diseases; among the 17 studies that described mHealth systems, most involved patients diagnosed with cardiovascular and heart disease, followed by diabetes, respiratory disease, mental health conditions, cancer, and multiple illnesses. The most common evaluation method was collection of usage logs (n=21), followed by standardized questionnaires (n=18) and ad-hoc questionnaires (n=13). The most common measure was app interaction (n=19), followed by usability/feasibility (n=17) and patient-reported health data via the app (n=15). Conclusions: This review demonstrates that health intervention studies are taking advantage of the additional resources that mHealth technologies provide. As mHealth technologies become more prevalent, the call for evidence includes the impacts on patients’ self-efficacy and engagement, in addition to traditional measures. However, considering the unstructured data forms, diverse use, and various platforms of mHealth, it can be challenging to select the right methods and measures to evaluate mHealth technologies. The inclusion of app usage logs, patient-involved methods, and other approaches to determine the impact of mHealth is an important step forward in health intervention research. We hope that this overview will become a catalogue of the possible ways in which mHealth has been and can be integrated into research practice.

O’Cathail, Micheal et al (2020) [Scoping Review] The Use of Patient-Facing Teleconsultations in the National Health Service: Scoping Review[43]

Background: The National Health Service (NHS) Long-Term Plan has set out a vision of enabling patients to access digital interactions with health care professionals within 5 years, including by video link. Objective: This review aimed to examine the extent and nature of the use of patient-facing teleconsultations within a health care setting in the UK and what outcome measures have been assessed. Methods: We conducted a systematic scoping review of teleconsultation studies following the Joanna Briggs Institute methodology. PubMed, Scopus, the Cochrane Library and the Cumulative Index to Nursing and Allied Health Literature were searched up to the end of December 2018 for publications that reported on the use of patient-facing teleconsultations in a UK health care setting. Results: The search retrieved 3132 publications, of which 101 were included for a full review. Overall, the studies were heterogeneous in design, in the specialty assessed, and reported outcome measures. The technology used for teleconsultations changed over time with earlier studies employing bespoke, often expensive, solutions. Two-thirds of the studies, conducted between 1995 and 2005, used this method. Later studies transitioned to web-based commercial solutions such as Skype. There were five outcome measures that were assessed: 1. technical feasibility; 2. user satisfaction; 3. clinical effectiveness; 4. cost; 5. logistical and operational considerations. Due to the changing nature of technology over time, there were differing technical issues across the studies. Generally, teleconsultations were acceptable to patients, but this was less consistent among health care professionals. However, among both groups, face-to-face consultations were still seen as the gold standard. A wide range of clinical scenarios found teleconsultations to be clinically useful but potentially limited to more straightforward clinical interactions. Due to the wide array of study types and changes in technology over time, it is difficult to draw definitive conclusions on the cost involved. However, cost savings for health care providers have been demonstrated by the goal-directed implementation of teleconsultations. The integration of technology into routine practice represents a complex problem with barriers identified in funding and hospital reimbursement, information technologies infrastructure, and integration into clinicians’ workflow.
Conclusions: Teleconsultations appear to be safe and effective in the correct clinical situations. Where offered, it is likely that patients will be keen to engage, although teleconsultations should only be offered as an option to support traditional care models rather than replace them outright. Health care staff should be encouraged and supported in using teleconsultations to diversify their practice. Health care organizations need to consider developing a digital technology strategy and implementation groups to assist health care staff to integrate digitally enabled care into routine practice. The introduction of new technologies should be assessed after a set period with service evaluations, including feedback from key stakeholders.

Seljelid, Berit et al (2020) [Review] Content and system development of a digital patient-provider communication tool to support shared decision making in chronic health care: InvolveMe[44]

Background: Chronic conditions present major health problems, affecting an increasing number of individuals who experience a variety of symptoms that impact their health related quality of life. Digital tools can be of support in chronic conditions, potentially improving patient-provider communication, promoting shared decision making for treatment and care, and possibly even improving patient outcomes. This study aimed to develop a digital tool for patient-provider communication in chronic health care settings and describes the data collection and subsequent content and software development of the InvolveMe tool. InvolveMe will provide patients with the opportunity to report symptoms and preferences to their health care providers (HCP), and to use secure messaging to interact with the HCPs. Method: The study employed a combination of interviews with patients with chronic conditions and focus groups with HCPs, examining experiences with chronic conditions and the potential use of a digital tool for support. Participants were recruited from two outpatient clinics at a university hospital. Data collected from interviews and focus groups were analysed using thematic analysis. Content and software development was informed by the data collection and by tool development workshops. Results: Analyses from interviews with patients (n = 14) and focus groups with HCPs (n = 11) generated three main themes: 1. making symptoms and challenges visible; 2. mastering a new life; and 3. digital opportunities for follow-up. Each main theme generated separate subthemes. Theme 1 and 2 gave input for content development of the symptom and needs assessment part of the tool, while theme 3 provided ideas for the software development of the InvolveMe tool. Tool development workshops with patients (n = 6) and HCPs (n = 6) supplemented the development. Conclusions: A digital tool such as InvolveMe has the potential to support shared decision making for patients with chronic health conditions. Through integration with an existing patient portal such a tool can provide opportunities for meaningful interactions and communication between patients and HCP’s, particularly with regards to symptoms, needs and preferences for care.

Bonacaro, Antonio et al (2019) [Literature Review] The use of wearable devices in preventing hospital readmission and in improving the quality of life of chronic patients in the homecare Setting: A Narrative Literature Review[45]

Introduction: According to the World Health Organisation chronic diseases are the leading cause of mortality in the world, representing 60% of all deaths. Strategies employed to tackle chronic diseases aim to act on risk factors through adopting a healthy lifestyle. These strategies can be greatly implemented from the adoption of wearable devices, which allow a thorough and mini- mally invasive monitoring of patients’ clinical data. This article aims to clarify whether wearable devices can help in preventing hospital readmission and improve quality of life in chronic patients. Method: A literature search of electronic databases was performed in January 2017. The following databases were searched: The Cochrane Database of Systematic Reviews, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), Pub Med, EMBASE and MEDLINE. Results: 33 articles met the inclusion criteria and were included in the literature review. Discussion: Various wearable devices are currently available to monitor and keep records of diffe- rent clinical information. Some of them are proved to prevent hospital re-admissions and to treat effectively life-threatening situations in certain categories of chronic patients. Higher level of acceptability and usability are achieved when users are involved in the testing stage prior to the release of the device and/or the features and terms of use are clearly described to patients and carers. Wearable devices are also proved to be more accurate than clinical assessment only in estimating the risk of falls in chronic patients, thus improving safety in the home care setting. Regardless of their features, wearable devices are yet to be used by both healthcare professionals and patients on a large scale.

Madrigal, Lillian et al (2019) [Cross-Sectional Study] Electronic Health Behaviors Among US Adults With Chronic Disease: Cross-Sectional Survey[46]

Background: With increased access to technology and the Internet, there are many opportunities for utilizing electronic health, Internet, or technology-delivered health services and information for the prevention and management of chronic diseases. Objective: The aim of this paper was to explore 1. the differences in technology use; 2. web-based health information seeking and use behaviors; 3. attitudes toward seeking health information on the Web; and 4. the level of eHealth literacy between adults aged 18 and 64 years with and without chronic disease. Methods: A cross-sectional Internet survey was conducted in March 2017 with 401 US adults. Participant responses were examined to understand associations between chronic disease status and eHealth behaviors such as Internet health-seeking behaviors and web-based behaviors related to health, tracking health indicators with a mobile app, patient portal use, and preferences for health information. Results: About 1 in 3 (252/401, 37.2%) participants reported at least 1 chronic disease diagnosis. Seventy-five percent (301/401) of all participants reported having ever searched for health information on the Web. Participants with a chronic disease reported significantly higher instances of visiting and talking to a health care provider based on health information found on the Web (40.0% [48/120] vs 25.8% [46/178], χ22=6.7; P=.01; 43.3% [52/120] vs 27.9% [50/179]; χ22=7.6; P=.006). The uses of health information found on the Web also significantly differed between participants with and without chronic diseases in affecting a decision about how to treat an illness or condition (49.2% [59/120] vs 35.0% [63/180], χ23=6.7; P=.04), changing the way they cope with a chronic condition or manage pain (40.8% [49/120] vs 19.4% [35/180], χ22=16.3; P<.001), and leading them to ask a doctor new questions or get a second opinion (37.5% [45/120] vs 19.6% [35/179], χ22=11.8; P<.001). Chronic disease participants were significantly more likely to be tracking health indicators (43.9% [65/148] vs 28.3%, [71/251] χ22=10.4; P=.006). In addition, participants with chronic disease diagnosis reported significantly higher rates of patient portal access (55.0% [82/149] vs 42.1% [106/252], χ22=6.3; P=.01) and use (40.9% [61/149] vs 21.0% [53/252], χ22=18.2; P<.001). Finally, both groups reported similar perceived skills in using the Internet for health information on the eHealth Literacy Scale (eHEALS). The majority of participants responded positively when asked about the usefulness of health information and importance of accessing health resources on the Web. Conclusions: The high rates of reported information seeking and use of Internet-based health technology among participants with chronic disease may reflect the uptake in eHealth to help manage chronic disease conditions. Health care providers and educators should continue to seek ways to interact and support patients in their management of chronic disease through eHealth platforms, including capitalizing on web-based resources, patient portals, and mobile phone apps for disease education and monitoring.

Maramba, Inocencio et al (2019) [Scoping Review] Methods of usability testing in the development of eHealth applications: A scoping review[47]

Background: The number of eHealth applications has exponentially increased in recent years, with over 325,000 health apps now available on all major app stores. This is in addition to other eHealth applications available on other platforms such as PC software, web sites and even gaming consoles. As with other digital applications, usability is one of the key factors in the successful implementation of eHealth apps. Reviews of the literature on empirical methods of usability testing in eHealth were last published in 2015. In the context of an exponentially increasing rate of App development year on year, an updated review is warranted. Objective: To identify, explore, and summarize the current methods used in the usability testing of eHealth applications. Methods: A scoping review was conducted on literature available from April 2014 up to October 2017. Four databases were searched. Literature was considered for inclusion if it was 1. focused on an eHealth application; 2. provided information about usability of the application; 3. provided empirical results of the usability testing; 4. a full or short paper published in English after March 2014. We then extracted data pertaining to the usability evaluation processes described in the selected studies. Results: 133 articles met the inclusion criteria. The methods used for usability testing, in decreasing order of frequency were: questionnaires (n = 105), task completion (n = 57), ‘Think-Aloud’ (n = 45), interviews (n = 37), heuristic testing (n = 18) and focus groups (n = 13). Majority of the studies used one (n = 45) or two (n = 46) methods of testing. The rest used a combination of three (n = 30) or four (n = 12) methods of testing usability. None of the studies used automated mechanisms to test usability. The System Usability Scale (SUS) was the most frequently used questionnaire (n = 44). The ten most frequent health conditions or diseases where eHealth apps were being evaluated for usability were the following: mental health (n = 12), cancer (n = 10), nutrition (n = 10), child health (n = 9), diabetes (n = 9), telemedicine (n = 8), cardiovascular disease (n = 6), HIV (n = 4), health information systems (n = 4) and smoking (n = 4). Further iterations of the app were reported in a minority of the studies (n = 41). The use of the ‘Think-Aloud’ (Pearson Chi-squared test: χ2 = 11.15, p < 0.05) and heuristic walkthrough (Pearson Chi-squared test: χ2 = 4.48, p < 0.05) were significantly associated with at least one further iteration of the app being developed. Conclusion: Although there has been an exponential increase in the number of eHealth apps, the number of studies that have been published that report the results of usability testing on these apps has not increased at an equivalent rate. The number of digital health applications that publish their usability evaluation results remains only a small fraction. Questionnaires are the most prevalent method of evaluating usability in eHealth applications, which provide an overall measure of usability but do not pinpoint the problems that need to be addressed. Qualitative methods may be more useful in this regard. The use of multiple evaluation methods has increased. Automated methods such as eye tracking have not gained traction in evaluating health apps. Further research is needed into which methods are best suited for the different types of eHealth applications, according to their target users and the health conditions being addressed.

Triantafyllidis, Andreas et al (2019) [Review of Systematic Reviews] Features, Outcomes, and Challenges in Mobile Health Interventions for Patients Living With Chronic Diseases: A Review of Systematic Reviews[48]

Background: Mobile health technology has the potential to play a key role in improving the health of patients with chronic non-communicable diseases. Objectives: We present a review of systematic reviews of mHealth in chronic disease management, by showing the features and outcomes of mHealth interventions, along with associated challenges in this rapidly growing field. Methods: We searched the bibliographic databases of PubMed, Scopus, and Cochrane to identify systematic reviews of mHealth interventions with advanced technical capabilities such as Internet-linked apps, interoperation with sensors and communication with clinical platforms utilized in randomized clinical trials. The original studies included the reviews were synthesized according to their intervention features, the targeted diseases, the primary outcome, the number of participants and their average age, as well as the total follow-up duration. Results: We identified 5 reviews respecting our inclusion and exclusion criteria, which examined 30 mHealth interventions. The highest percentage of the interventions targeted patients with diabetes (n = 19, 63%), followed by patients with psychotic disorders (n = 7, 23%), lung diseases (n = 3, 10%), and cardiovascular disease (n = 1, 3%). 14 studies showed effective results: 9 in diabetes management, 2 in lung function, and 3 in mental health. Significantly positive outcomes were reported in 8 interventions (n = 8, 47%) from 17 studies assessing glucose concentration, one intervention assessing physical activity, 2 interventions (n = 2, 67%) from 3 studies assessing lung function parameters, and 3 mental health interventions assessing N-back performance, medication adherence, and number of hospitalizations. Divergent features were adopted in 14 interventions with significantly positive outcomes, such as personalized goal setting (n = 10, 71%), motivational feedback (n = 5, 36%), and alerts for health professionals (n = 3, 21%). The most significant found challenges in the development and evaluation of mHealth interventions include the design of studies with high quality, the construction of robust interventions in combination with health professional inputs, and the identification of tools and methods to improve patient adherence. Conclusions: This review found mixed evidence regarding the health benefits of mHealth interventions for patients living with chronic diseases. Further rigorous studies are needed to assess the outcomes of personalized mHealth interventions toward the optimal management of chronic diseases.

Volterrani, Maurizio et al (2019) [Review] Remote Monitoring and Telemedicine[49]

Telemedicine and remote monitoring represent more than the communication of health data via a ‘remote connection’. Modern systems can be stand-alone and can be equipped with the ability to acquire and summarize data in order to inform the patient, carer or health care giver. The information can be held locally or be shared with a health care centre. Contemporary telemedicine and telemonitoring solutions have shifted their focus, trying to work on a system which is ubiquitous, efficient and sustainable. Along with devices that collect and elaborate data, a new generation of plug and play sensors has also come to life, which with standardization can lower management costs and make introduction into practice more feasible. Multiple trials (TIM-HF, TEN-HMS and BEAT.HF) have reported varying outcomes, depending on the monitoring system and the background health care process. A special mention is necessary for home tele-rehabilitation programmes for patients with heart failure. Despite the progress obstacles remain, including adequate training, data ownership and handling and applicability to larger populations. This article will review contemporary advances in this area.

Bertoncello, Chiara et al (2018) [Review] How Does It Work? Factors Involved in Telemedicine Home-Interventions Effectiveness: A Review of Reviews[50]

Introduction: Definitive evidence of the effectiveness and cost-effectiveness of telemedicine home-interventions for the management of chronic diseases is still lacking. This study examines whether and how published reviews consider and discuss the influence on outcomes of different factors, including: setting, target, and intensity of intervention; patient engagement; the perspective of patients, caregivers and health professionals; the organizational model; patient education and support. Included reviews were also assessed in terms of economic and ethical issues. Methods: Two search algorithms were developed to scan PubMed for reviews published between 2000 and 2015, about ICT-based interventions for the management of hypertension, diabetes, heart failure, asthma, chronic obstructive pulmonary disease, or for the care of elderly patients. Based on our inclusion criteria, 25 reviews were selected for analysis. Results: None of the included reviews covered all the above-mentioned factors. They mostly considered target (44%) and intervention intensity (24%). Setting, ethical issues, patient engagement, and caregiver perspective were the most neglected factors. Only 4 reviews (16%) considered at least 4 of the 11 factors, the maximum number of factors considered in a review is 5. Conclusions: Factors that may be involved in ICT-based interventions, affecting their effectiveness or cost-effectiveness, are not enough studied in the literature. This research suggests to consider mostly the role of each one, comparing not only disease-related outcomes, but also patients and healthcare organizations outcomes, and patient engagement, in order to understand how interventions work.

Greenhalgh, Trisha et al (2018) [Mixed-Methods Study] Real-World Implementation of Video Outpatient Consultations at Macro, Meso, and Micro Levels: Mixed-Method Study[51]

Background: There is much interest in virtual consultations using video technology. Randomized controlled trials have shown video consultations to be acceptable, safe, and effective in selected conditions and circumstances. However, this model has rarely been mainstreamed and sustained in real-world settings. Objective: The study sought to 1. define good practice and inform implementation of video outpatient consultations; and 2. generate transferable knowledge about challenges to scaling up and routinizing this service model. Methods: A multilevel, mixed-method study of Skype video consultations (micro level) was embedded in an organizational case study (meso level), taking account of national context and wider influences (macro level). The study followed the introduction of video outpatient consultations in three clinical services diabetes, diabetes antenatal, and cancer surgery in a National Health Service trust covering three hospitals in London. Data sources included 36 national-level stakeholders [exploratory and semistructured interviews], longitudinal organizational ethnography [300 hours of observations; 24 staff interviews], 30 videotaped remote consultations, 17 audiotaped face-to-face consultations, and national and local documents. Qualitative data, analyzed using sociotechnical change theories, addressed staff and patient experience and organizational and system drivers. Quantitative data, analyzed via descriptive statistics, included uptake of video consultations by staff and patients and microcategorization of different kinds of talk using the Roter interaction analysis system. Results: When clinical, technical, and practical preconditions were met, video consultations appeared safe and were popular with some patients and staff. Compared with face-to-face consultations for similar conditions, video consultations were very slightly shorter, patients did slightly more talking, and both parties sometimes needed to make explicit things that typically remained implicit in a traditional encounter. Video consultations appeared to work better when the clinician and patient already knew and trusted each other. Some clinicians used Skype adaptively to respond to patient requests for ad hoc encounters in a way that appeared to strengthen supported self-management. The reality of establishing video outpatient services in a busy and financially stretched acute hospital setting proved more complex and time-consuming than originally anticipated. By the end of this study, between 2% and 22% of consultations were being undertaken remotely by participating clinicians. In the remainder, clinicians chose not to participate, or video consultations were considered impractical, technically unachievable, or clinically inadvisable. Technical challenges were typically minor but potentially prohibitive. Conclusions: Video outpatient consultations appear safe, effective, and convenient for patients in situations where participating clinicians judge them clinically appropriate, but such situations are a fraction of the overall clinic workload. As with other technological innovations, some clinicians will adopt readily, whereas others will need incentives and support. There are complex challenges to embedding video consultation services within routine practice in organizations that are hesitant to change, especially in times of austerity.

Orozco-Beltran, Domingo et al (2017) [Quasi-Experimental Study] Telemedicine in Primary Care for Patients With Chronic Conditions: The ValCrònic Quasi-Experimental Study[52]

Background: The increase of chronic diseases prevalence has created the need to adapt care models and to provide greater home supervision. Objective: The objective of our study was to evaluate the impact of telemonitoring on patients with long-term conditions at high risk for rehospitalization or an emergency department visit, in terms of target disease control: diabetes, hypertension, heart failure, and chronic obstructive pulmonary disease. Methods: We conducted a quasi-experimental study with a before-and-after analysis to assess the effectiveness of the ValCrònic program after 1 year of primary care monitoring. The study included high-risk patients with 1 or more of the following conditions: diabetes, high blood pressure, heart failure, and chronic obstructive pulmonary disease. We assessed risk according to the Community Assessment Risk Screen. Participants used an electronic device to self-report relevant health information, which was then automatically entered into their eHealth record for consultation. Results: The total sample size was 521 patients. Compared with the preintervention year, there were significant reductions in weight (82.3 kg before vs 80.1 kg after; P=.001) and in the proportion of people with high systolic (≥140 mmHg; 190, 36.5% vs 170, 32.6%; P=.001) and diastolic (≥90 mmHg; 72, 13.8% vs 40, 7.7%; P=.01) blood pressures, and hemoglobin A1c ≥8% (186, 35.7% vs 104, 20.0%; P=.001). There was also a decrease in the proportion of participants who used emergency services in primary care (68, 13.1% vs 33, 6.3%; P<.001) and in hospital (98, 18.8% vs 67, 12.8%; P<.001). Similarly, fewer participants required hospital admission due to an emergency (105, 20.2% vs 71, 13.6%; P<.001) or disease exacerbation (55, 10.5% vs 42, 8.1%; P<.001). Conclusions: The ValCrònic telemonitoring program in patients at high risk for rehospitalization or an emergency department visit appears to be useful to improve target disease control and to reduce the use of resources.

Matthew-Maich, Nancy et al (2016) [Scoping Review] Designing, Implementing, and Evaluating Mobile Health Technologies for Managing Chronic Conditions in Older Adults: A Scoping Review[53]

Background: The current landscape of a rapidly aging population accompanied by multiple chronic conditions presents numerous challenges to optimally support the complex needs of this group. Mobile health technologies have shown promise in supporting older persons to manage chronic conditions; however, there remains a dearth of evidence-informed guidance to develop such innovations. Objectives: The purpose of this study was to conduct a scoping review of current practices and recommendations for designing, implementing, and evaluating mHealth technologies to support the management of chronic conditions in community-dwelling older adults. Methods: A scoping review methodology was used to map the relevant literature published between January 2005 and March 2015. In addition, hand searches of reference lists and a key journal were completed. Inclusion criteria were research and nonresearch papers focused on mHealth technologies designed for use by community-living older adults with at least one chronic condition, or health care providers or informal caregivers providing care in the home and community setting. Two reviewers independently identified articles for review and extracted data. Results: We identified 42 articles that met the inclusion criteria. Of these, described innovations focused on older adults with specific chronic conditions (n=17), chronic conditions in general (n=6), or older adults in general or those receiving homecare services (n=18). Most of the mHealth solutions described were designed for use by both patients and health care providers or health care providers only. Thematic categories identified included the following: 1. practices and considerations when designing mHealth technologies; 2. factors that support/hinder feasibility, acceptability, and usability of mHealth technologies; and 3. approaches or methods for evaluating mHealth technologies. Conclusions: There is limited yet increasing use of mHealth technologies in home health care for older adults. A user-centered, collaborative, interdisciplinary approach to enhance feasibility, acceptability, and usability of mHealth innovations is imperative. Creating teams with the required pools of expertise and insight regarding needs is critical. The cyclical, iterative process of developing mHealth innovations needs to be viewed as a whole with supportive theoretical frameworks. Many barriers to implementation and sustainability have limited the number of successful, evidence-based mHealth solutions beyond the pilot or feasibility stage. The science of implementation of mHealth technologies in home-based care for older adults and self-management of chronic conditions are important areas for further research. Additionally, changing needs as cohorts and technologies advance are important considerations. Lessons learned from the data and important implications for practice, policy, and research are discussed to inform the future development of innovations.

Rojahn, Katherine et al (2016) Remote Monitoring of Chronic Diseases: A Landscape Assessment of Policies in Four European Countries[54]

Background: Remote monitoring (RM) is defined as the surveillance of device-transmitted outpatient data. RM is expected to enable better management of chronic diseases. The objective of this research was to identify public policies concerning RM in four European countries. Methods: Searches of the medical literature, the Internet, and Ministry of Health websites for the UK, Germany, Italy, and Spain were performed in order to identify RM policies for chronic diseases, including end stage renal disease (ESRD), chronic pulmonary obstructive disease (COPD), diabetes, heart failure, and hypertension. Searches were first performed in Q1 2014 and updated in Q4 2015. In addition, in depth interviews were conducted with payers/policymakers in each country. Information was obtained on existing policies, disease areas and RM services covered and level of reimbursement other incentives such as quality indicators, past/current assessments of RM technologies, diseases perceived to benefit most from RM, and concerns about RM. Results: Policies on RM and/or telemedicine were identified in all four countries. Pilot projects (mostly in diabetes, COPD, and/or heart failure) existed or were planned in most countries. Perceived value of RM was moderate to high, with the highest rating given for heart failure. Interviewees expressed concerns about sharing of medical information, and the need for capital investment. Patients recently discharged from hospital, and patients living remotely, or with serious and/or complicated diseases, were believed to be the most likely to benefit from RM. Formal reimbursement is scarce, but more commonly available for patients with heart failure. Conclusions: In the four European countries surveyed, RM has attracted considerable interest for its potential to increase the efficiency of healthcare for chronic diseases. Although rare at this moment, incentives to use RM technology are likely to increase in the near future as the body of evidence of clinical and/or economic benefit grows. Conflict of interest statement: Competing Interests: The company selected by Baxter to conduct the study was Double Helix. Baxter Healthcare provided honoraria to TA and KIJ, as employees of Double Helix. TA and KIJ were involved in study conduct, data collection, analysis, and reporting as articulated in the ‘author contributions’ section. Baxter Healthcare has no ownership or legal relationship with Double Helix other than the contract for this study. The respective commercial affiliations of the authors does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials, with the exception of the primary research data as described in Data Availability section.

Wildevuur, Sabine E. et al (2015) [Scoping Review] Information and communication technology-enabled person-centered care for the “big five” chronic conditions: scoping review[55]

Background: Person-centered information and communication technology (ICT) could encourage patients to take an active part in their health care and decision-making process, and make it possible for patients to interact directly with health care providers and services about their personal health concerns. Yet, little is known about which ICT interventions dedicated to person-centered care (PCC) and connected-care interactions have been studied, especially for shared care management of chronic diseases. The aim of this research is to investigate the extent, range, and nature of these research activities and identify research gaps in the evidence base of health studies regarding the “big 5” chronic diseases: diabetes mellitus, cardiovascular disease, chronic respiratory disease, cancer, and stroke. Objective: The objective of this paper was to review the literature and to scope the field with respect to 2 questions: 1. which ICT interventions have been used to support patients and health care professionals in PCC management of the big 5 chronic diseases? ; and 2. what is the impact of these interventions, such as on health-related quality of life and cost efficiency? Methods: This research adopted a scoping review method. Three electronic medical databases were accessed: PubMed, EMBASE, and Cochrane Library. The research reviewed studies published between January 1989 and December 2013. In 5 stages of systematic scanning and reviewing, relevant studies were identified, selected, and charted. Then we collated, summarized, and reported the results. Results: From the initial 9380 search results, we identified 350 studies that qualified for inclusion: diabetes mellitus (n=103), cardiovascular disease (n=89), chronic respiratory disease (n=73), cancer (n=67), and stroke (n=18). Persons with one of these chronic conditions used ICT primarily for self-measurement of the body, when interacting with health care providers, with the highest rates of use seen in chronic respiratory (63%, 46/73) and cardiovascular (53%, 47/89) diseases. We found 60 relevant studies (17.1%, 60/350) on person-centered shared management ICT, primarily using telemedicine systems as personalized ICT. The highest impact measured related to the increase in empowerment (15.4%, 54/350). Health-related quality of life accounted for 8%. The highest impact connected to health professionals was an increase in clinical outcome (11.7%, 41/350). The impacts on organization outcomes were decrease in hospitalization (12.3%, 43/350) and increase of cost efficiency (10.9%, 38/350). Conclusions: This scoping review outlined ICT-enabled PCC in chronic disease management. Persons with a chronic disease could benefit from an ICT-enabled PCC approach, but ICT-PCC also yields organizational paybacks. It could lead to an increase in health care usage, as reported in some studies. Few interventions could be regarded as “fully” addressing PCC. This review will be especially helpful to those deciding on areas where further development of research or implementation of ICT-enabled PCC may be warranted.


[34] Lee JA, Choi M, Lee SA, Jiang N.Effective behavioral intervention strategies using mobile health applications for chronic
disease management: a systematic review. BMC Med Inform Decis Mak. 2018;181.:12. Published 2018 Feb 20.
doi:10.1186/s12911-018-0591-0

[35] Sprogis SK, Currey J, Considine J. Patient acceptability of wearable vital sign monitoring technologies in the acute care
setting: A systematic review. J Clin Nurs. 2019;28(15-16):2732‐2744. doi:10.1111/jocn.14893

[36] Adamse C, Dekker-Van Weering MG, van Etten-Jamaludin FS, Stuiver MM. The effectiveness of exercise-based telemedicine
on pain, physical activity and quality of life in the treatment of chronic pain: A systematic review. J Telemed Telecare.
2018;248.:511‐526. doi:10.1177/1357633X17716576

[37] Albahri OS, Albahri AS, Mohammed KIet al Systematic Review of Real-time Remote Health Monitoring System in Triage and
Priority-Based Sensor Technology: Taxonomy, Open Challenges, Motivation and Recommendations. J Med Syst.2018;425.:80.
Published 2018 Mar 22. doi:10.1007/s10916-018-0943-4

[38] Baig MM, GholamHosseini H, Moqeem AA, Mirza F, Lindén M. A Systematic Review of Wearable Patient Monitoring Systems
-Current Challenges and Opportunities for Clinical Adoption. J Med Syst. 2017;417.:115. doi:10.1007/s10916-017-0760-1

[39] Vegesna A, Tran M, Angelaccio M, Arcona S. Remote Patient Monitoring via Non-Invasive Digital Technologies: A Systematic
Review. Telemed J E Health. 2017;231.:3‐17. doi:10.1089/tmj.2016.0051

[40] Stephani V, Opoku D, Quentin W. A systematic review of randomized controlled trials of mHealth interventions against noncommunicable diseases in developing countries. BMC Public Health. 2016;16:572. Published 2016 Jul 15. doi:10.1186/s12889-016-3226-3

[41] Bashi N, Fatehi F, Mosadeghi-Nik M, Askari MS, Karunanithi M. Digital health interventions for chronic diseases: a scoping
review of evaluation frameworks. BMJ Health Care Inform. 2020;271.:e100066. doi:10.1136/bmjhci-2019-100066

[42] Bradway M, Gabarron E, Johansen M et al Methods and Measures Used to Evaluate Patient-Operated Mobile Health
Interventions: Scoping Literature Review. JMIR Mhealth Uhealth. 2020;84.:e16814. Published 2020 Apr 30. doi:10.2196/16814

[43] O’Cathail M, Sivanandan MA, Diver C, Patel P, Christian J. The Use of Patient-Facing Teleconsultations in the National Health
Service: Scoping Review. JMIR Med Inform.2020;83.:e15380. Published 2020 Mar 16. doi:10.2196/15380

[44] Seljelid B, Varsi C, Solberg Nes L, Stenehjem AE, Bollerslev J, Børøsund E. Content and system development of a digital
patient-provider communication tool to support shared decision making in chronic health care: InvolveMe. BMC Med Inform
Decis Mak. 2020;201.:46. Published 2020 Mar 4. doi:10.1186/s12911-020-1065-8

[45] Bonacaro A, Rubbi I, Sookhoo D. The use of wearable devices in preventing hospital readmission and in improving the quality
of life of chronic patients in the homecare Setting: A Narrative Literature Review. L’uso dei dispositivi indossabili nella
prevenzione dei ripetuti ricoveri ospedalieri e nel miglioramento della qualità della vita dei pazienti cronici a domicilio. Una
revisione narrativa della letteratura. Prof Inferm.2019;722.:143‐151.

[46] Madrigal L, Escoffery C. Electronic Health Behaviors Among US Adults With Chronic Disease: Cross-Sectional Survey. J Med
Internet Res.2019;213.:e11240. Published 2019 Mar 5. doi:10.2196/11240

[47] Maramba I, Chatterjee A, Newman C. Methods of usability testing in the development of eHealth applications: A scoping review. Int J Med Inform. 2019;126:95‐104. doi:10.1016/j.ijmedinf.2019.03.018

[48] Triantafyllidis A, Kondylakis H, Votis K, Tzovaras D, Maglaveras N, Rahimi K. Features, outcomes, and challenges in mobile
health interventions for patients living with chronic diseases: A review of systematic reviews. Int J Med Inform.
2019;132:103984. doi:10.1016/j.ijmedinf.2019.103984

[49] Volterrani M, Sposato B. Remote monitoring and telemedicine. Eur Heart J Suppl.2019;21(Suppl M):M54‐M56. doi:10.1093/eurheartj/suz266

[50] Bertoncello C, Colucci M, Baldovin T, Buja A, Baldo V. How does it work? Factors involved in telemedicine homeinterventions effectiveness: A review of reviews. PLoS One. 2018;13(11):e0207332. Published 2018 Nov 15.
doi:10.1371/journal.pone.0207332

[51] Greenhalgh T, Shaw S, Wherton J et al Real-World Implementation of Video Outpatient Consultations at Macro, Meso, and
Micro Levels: Mixed-Method Study. J Med Internet Res. 2018;204.:e150. Published 2018 Apr 17. doi:10.2196/jmir.9897

[52] Orozco-Beltran D, Sánchez-Molla M, Sanchez JJ, Mira JJ; ValCrònic Research Group. Telemedicine in Primary Care for
Patients With Chronic Conditions: The ValCrònic Quasi-Experimental Study. J Med Internet Res. 2017;19(12):e400. Published
2017 Dec 15. doi:10.2196/jmir.7677

[53] Matthew-Maich N, Harris L, Ploeg J et al Designing, Implementing, and Evaluating Mobile Health Technologies for Managing
Chronic Conditions in Older Adults: A Scoping Review. JMIR Mhealth Uhealth. 2016;42.:e29. Published 2016 Jun 9. doi:10.2196/mhealth.5127

[54] Rojahn K, Laplante S, Sloand J et al Remote Monitoring of Chronic Diseases: A Landscape Assessment of Policies in Four
European Countries. PLoS One. 2016;115.:e0155738. Published 2016 May 19. doi:10.1371/journal.pone.0155738

[55] Wildevuur SE, Simonse LW. Information and communication technology-enabled person-centered care for the “big five”
chronic conditions: scoping review. J Med Internet Res. 2015;173.:e77. Published 2015 Mar 27. doi:10.2196/jmir.3687