Dataset Information

Enabling Guidelines for the Adoption of eHealth Solutions: Scoping Review.

ABSTRACT:

Background

Globally, public health care is under increasing pressure, an economic burden currently amplified by the COVID-19 outbreak. With the recognition that universal health coverage improves the health of a population and reduces health inequalities, universal health coverage has been acknowledged as a priority goal. To meet the global needs in a population with increased chronic illness and longer life expectancy, the health care system is in dire need of new, emerging technologies. eHealth solutions as a method of delivery may have an impact on quality of care and health care costs. As such, it is important to study methods previously used to avoid suboptimal implementation and promote general guidelines to further develop eHealth solutions.

Objective

This study aims to explore and thematically categorize a selected representation of early phase studies on eHealth technologies, focusing on papers that are under development or undergoing testing. Further, we want to assess enablers and barriers in terms of usability, scaling, and data management of eHealth implementation. The aim of this study to explore early development phase and feasibility studies was an intentional effort to provide applicable guidelines for evaluation at different stages of implementation.

Methods

A structured search was performed in PubMed, MEDLINE, and Cochrane to identify and provide insight in current eHealth technology and methodology under development and gain insight in the future potential of eHealth technologies.

Results

In total, 27 articles were included in this review. The clinical studies were categorized thematically by illness comparing 4 technology types deemed relevant: apps/web-based technology, sensor technology, virtual reality, and television. All eHealth assessment and implementation studies were categorized by their focus point: usability, scaling, or data management. Studies assessing the effect of eHealth were divided into feasibility studies, qualitative studies, and heuristic assessments. Studies focusing on usability (16/27) mainly addressed user involvement and learning curve in the adoption of eHealth, while the majority of scaling studies (6/27) focused on strategic and organizational aspects of upscaling eHealth solutions. Studies focusing on data management (5/27) addressed data processing and data sensitivity in adoption and diffusion of eHealth. Efficient processing of data in a secure manner, as well as user involvement and feedback, both throughout small studies and during upscaling, were the important enablers considered for successful implementation of eHealth.

Conclusions

eHealth interventions have considerable potential to improve lifestyle changes and adherence to treatment recommendations. To promote efficient implementation and scaling, user involvement to promote user-friendliness, secure and adaptable data management, and strategical considerations needs to be addressed early in the development process. eHealth should be assessed during its development into health services. The wide variation in interventions and methodology makes comparison of the results challenging and calls for standardization of methods.

SUBMITTER: Stome LN

PROVIDER: S-EPMC8122291 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND:Dyadic psychosocial interventions have been found beneficial both for people coping with mental or physical health conditions as well as their family members and friends who provide them with support. Delivering these interventions via electronic health (eHealth) may help increase their scalability. OBJECTIVE:This scoping review aimed to provide the first comprehensive overview of dyadic eHealth interventions for individuals of all ages affected by mental or physical illness and their family members or friends who support them. The goal was to understand how dyadic eHealth interventions have been used and to highlight areas of research needed to advance dyadic eHealth intervention development and dissemination. METHODS:A comprehensive electronic literature search of PubMed, EMBASE, Cochrane, Cumulative Index to Nursing and Allied Health Literature, and PsycINFO was conducted for articles published in the English language through March 2019. Eligible records described a psychosocial eHealth intervention that intervened with both care recipients and their support person. RESULTS:A total of 7113 records were reviewed of which 101 met eligibility criteria. There were 52 unique dyadic eHealth interventions identified, which were tested across 73 different trials. Of the unique interventions, 33 were conducted among dyads of children and their supporting parent, 1 was conducted with an adolescent-young adult care recipient population, and the remaining 18 were conducted among adult dyads. Interventions targeting pediatric dyads most commonly addressed a mental health condition (n=10); interventions targeting adult dyads most commonly addressed cancer (n=9). More than three-fourths of interventions (n=40) required some human support from research staff or clinicians. Most studies (n=64) specified one or more primary outcomes for care recipients, whereas less than one-fourth (n=22) specified primary outcomes for support persons. Where specified, primary outcomes were most commonly self-reported psychosocial or health factors for both care recipients (n=43) and support persons (n=18). Results of the dyadic eHealth intervention tended to be positive for care recipients, but evidence of effects for support persons was limited because of few studies specifying primary outcomes for supporters. Trials of dyadic eHealth interventions were most commonly randomized controlled trials (RCTs; n=44), and RCTs most commonly compared the dyadic eHealth intervention to usual care alone (n=22). CONCLUSIONS:This first comprehensive review of dyadic eHealth interventions demonstrates that there is substantial, diverse, and growing literature supporting this interventional approach. However, several significant gaps were identified. Few studies were designed to evaluate the unique effects of dyadic interventions relative to individual interventions. There was also limited assessment and reporting of outcomes for support persons, and there were no interventions meeting our eligibility criteria specifically targeting the needs of older adult dyads. Findings highlight areas of research opportunities for developing dyadic eHealth interventions for novel populations and for increasing access to dyadic care.

Project description:BackgroundeHealth is the use of information and communication technologies to enable and improve health and health care services. It is crucial that medical students receive adequate training in eHealth as they will work in clinical environments that are increasingly being enabled by technology. This trend is especially accelerated by the COVID-19 pandemic as it complicates traditional face-to-face medical consultations and highlights the need for innovative approaches in health care.ObjectiveThis review aims to evaluate the extent and nature of the existing literature on medical student training in eHealth. In detail, it aims to examine what this education consists of, the barriers, enhancing factors, and propositions for improving the medical curriculum. This review focuses primarily on some key technologies such as mobile health (mHealth), the internet of things (IoT), telehealth, and artificial intelligence (AI).MethodsSearches were performed on 4 databases, and articles were selected based on the eligibility criteria. Studies had to be related to the training of medical students in eHealth. The eligibility criteria were studies published since 2014, from a peer-reviewed journal, and written in either English or French. A grid was used to extract and chart data.ResultsThe search resulted in 25 articles. The most studied aspect was mHealth. eHealth as a broad concept, the IoT, AI, and programming were least covered. A total of 52% (13/25) of all studies contained an intervention, mostly regarding mHealth, electronic health records, web-based medical resources, and programming. The findings included various barriers, enhancing factors, and propositions for improving the medical curriculum.ConclusionsTrends have emerged regarding the suboptimal present state of eHealth training and barriers, enhancing factors, and propositions for optimal training. We recommend that additional studies be conducted on the following themes: barriers, enhancing factors, propositions for optimal training, competencies that medical students should acquire, learning outcomes from eHealth training, and patient care outcomes from this training. Additional studies should be conducted on eHealth and each of its aspects, especially on the IoT, AI, programming, and eHealth as a broad concept. Training in eHealth is critical to medical practice in clinical environments that are increasingly being enabled by technology. The need for innovative approaches in health care during the COVID-19 pandemic further highlights the relevance of this training.

Project description:ObjectiveeHealth-mediated interventions have been proposed as one option to support self-management in those with musculoskeletal disorders (MSDs). This scoping review aimed to chart the evidence regarding eHealth modalities, musculoskeletal diagnosis, and outcomes of eHealth-mediated self-management support interventions in persons with MSDs and identify any gaps within the literature.MethodsSix electronic databases (MEDLINE, CINAHL, PsycINFO, Embase, Scopus, and the Cochrane Database of Systematic Reviews), 7 grey literature sources (eg, OpenGrey), and reference and citation lists of included studies were searched from database inception to July 2020. Published studies of adult participants with a MSD utilizing an eHealth intervention to support self-management were included. Studies were limited to those published in English. Two reviewers independently screened all studies. Data were extracted by 1 reviewer and reviewed by another reviewer.ResultsAfter screening 3377 titles and abstracts followed by 176 full texts, 87 studies fulfilled the eligibility criteria. The majority were published in the last 5 years (n = 48; 55%), with almost one-third originating in the United States (n = 28; 32%). The most common eHealth modality type was internet based (n = 22; 35%), with almost one-half (n = 41; 47%) of the included studies involving participants with widespread musculoskeletal symptoms. The most commonly reported outcomes were related to body functions (ie, pain intensity) (n = 67; 45%), closely followed by activities and participation (ie, function) (n = 65; 44%), with environmental factors (ie, health care utilization) the least commonly reported (n = 17; 20%).ConclusionsThere is considerable variation within the eHealth-mediated self-management support intervention literature. Research is needed on the role of eHealth-mediated self-management support interventions across a broad range of MSDs to guide clinical practice.ImpactThis scoping review has identified gaps in the literature relating to specific eHealth modalities, musculoskeletal diagnoses, and health care utilization data, which should guide future research.

Project description:BackgroundAccessibility is acknowledged as a key to inclusion in the Convention of Rights for People with Disabilities. An inaccessible design can result in exclusion from eHealth and cause disability among people who have impairments.ObjectiveThis scoping literature review aimed to investigate how eHealth services have been developed and evaluated regarding accessibility for people with impairments.MethodsIn line with Arksey and O'Malley's framework for scoping studies and using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR), we conducted a search in 4 databases (PubMed, Scopus, IEEE, and Web of Science) in October 2020 and an update of the search in June 2022. The search strategy was structured according to the PICO model as follows: Population/Problem, digital accessibility for users with impairment; Intervention, health care delivered by any digital solution; Comparison, not applicable; Outcome, use of and adherence to (1) Web Content Accessibility Guidelines (WCAG), (2) other accessibility guidelines, and (3) other means, for designing or evaluating accessibility in eHealth services. A Boolean search was conducted by combining terms related to accessibility and eHealth. All authors participated in screening abstracts according to the eligibility criteria. Each publication, containing a potentially relevant abstract, was read (full text) and assessed for eligibility by 2 authors independently and pairwise. Publications deemed eligible were read by all authors and discussed for consensus.ResultsA total of 8643 publications were identified. After abstract screening, 131 publications remained for full-text reading. Of those, 116 publications were excluded as they did not meet the eligibility criteria. Fifteen publications involving studies of 12 eHealth services were included in the study. Of the 15 publications, 2 provided a definition of accessibility, 5 provided an explanation of accessibility, and 8 did not provide any explanation. Five publications used the WCAG to evaluate accessibility when developing eHealth services. One publication used International Organization for Standardization (ISO) 29138, ISO 2941, and ISO/International Electrotechnical Commission (IEC) 30071-1 standards together with the Spanish Association for Standardization (UNE) 139803 standard. Eleven publications used other means to address accessibility, including text-level grading; literature review about accessibility; user tests, focus groups, interviews, and design workshops with target groups of patients, relatives, and health care professionals; and comparative analysis of existing technical solutions to provide information about useful requirements.ConclusionsAlthough a clear definition of accessibility can enhance operationalization and thus measurability when evaluating accessibility in eHealth services, accessibility was insufficiently defined in most of the included studies. Further, accessibility guidelines and standards were used to a very limited extent in the development and evaluation of eHealth services. Guidelines for developing complex interventions that include guidance for accessibility are motivated to ensure that accessibility will be considered systematically in eHealth services.

Project description:BackgroundDigital health interventions (DHIs) are increasingly being adopted globally to address various public health issues. DHIs can be categorized according to four main types of technology: mobile based, web based, telehealth, and electronic health records. In 2006, Norman and Skinner introduced the eHealth literacy model, encompassing six domains of skills and abilities (basic, health, information, scientific, media, and computer) needed to effectively understand, process, and act on health-related information. Little is known about whether these domains are assessed or accounted for in DHIs.ObjectiveThis study aims to explore how DHIs assess and evaluate the eHealth literacy model, describe which health conditions are addressed, and which technologies are used.MethodsWe conducted a scoping review of the literature on DHIs, based on randomized controlled trial design and reporting the assessment of any domain of the eHealth literacy model. MEDLINE, CINAHL, Embase, and Cochrane Library were searched. A duplicate selection and data extraction process was performed; we charted the results according to the country of origin, health condition, technology used, and eHealth literacy domain.ResultsWe identified 131 unique DHIs conducted in 26 different countries between 2001 and 2020. Most DHIs were conducted in English-speaking countries (n=81, 61.8%), delivered via the web (n=68, 51.9%), and addressed issues related to noncommunicable diseases (n=57, 43.5%) or mental health (n=26, 19.8%). None of the interventions assessed all six domains of the eHealth literacy model. Most studies focused on the domain of health literacy (n=96, 73.2%), followed by digital (n=19, 14.5%), basic and media (n=4, 3%), and information and scientific literacy (n=1, 0.7%). Of the 131 studies, 7 (5.3%) studies covered both health and digital literacy.ConclusionsAlthough many selected DHIs assessed health or digital literacy, no studies comprehensively evaluated all domains of the eHealth literacy model; this evidence might be overlooking important factors that can mediate or moderate the effects of these interventions. Future DHIs should comprehensively assess the eHealth literacy model while developing or evaluating interventions to understand how and why interventions can be effective.

Project description:BackgroundSuicide is a leading cause of death among youth and a prominent concern for school mental health providers. Indeed, schools play a key role in suicide prevention, including participating in risk assessments with students expressing suicidal ideation. In the context of the COVID-19 pandemic, many schools now need to offer mental health services, including suicide risk assessment, via eHealth platforms. Post pandemic, the use of eHealth risk assessments will support more accessible services for youth living in rural and remote areas. However, as the remote environment is a new context for many schools, guidance is needed on best practices for eHealth suicide risk assessment among youth.ObjectiveThis study aims to conduct a rapid, systematic scoping review to explore promising practices for conducting school-based suicide risk assessment among youth via eHealth (ie, information technologies that allow for remote communication).MethodsThis review included peer-reviewed articles and gray literature published in English between 2000 and 2020. Although we did not find studies that specifically explored promising practices for school-based suicide risk assessment among youth via eHealth platforms, we found 12 peer-reviewed articles and 23 gray literature documents that contained relevant information addressing our broader study purpose; thus, these 35 sources were included in this review.ResultsWe identified five key recommendation themes for school-based suicide risk assessment among youth via eHealth platforms in the 12 peer-reviewed studies. These included accessibility, consent procedures, session logistics, safety planning, and internet privacy. Specific recommendation themes from the 23 gray literature documents substantially overlapped with and enhanced three of the themes identified in the peer-reviewed literature-consent procedures, session logistics, and safety planning. In addition, based on findings from the gray literature, we expanded the accessibility theme to a broader theme termed youth engagement, which included information on accessibility and building rapport, establishing a therapeutic space, and helping youth prepare for remote sessions. Finally, a new theme was identified in the gray literature findings, specifically concerning school mental health professional boundaries. A second key difference between the gray and peer-reviewed literature was the former's focus on issues of equity and access and how technology can reinforce existing inequalities.ConclusionsFor school mental health providers in need of guidance, we believe that these six recommendation themes (ie, youth engagement, school mental health professional boundaries, consent procedures, session logistics, safety planning, and internet privacy) represent the most promising directions for school-based suicide risk assessment among youth using eHealth tools. However, suicide risk assessment among youth via eHealth platforms in school settings represents a critical research gap. On the basis of the findings of this review, we provide specific recommendations for future research, including the need to focus on the needs of diverse youth.

Project description:BackgroundThe methods with which prediction models are usually developed mean that neither the parameters nor the predictions should be interpreted causally. For many applications, this is perfectly acceptable. However, when prediction models are used to support decision making, there is often a need for predicting outcomes under hypothetical interventions.AimsWe aimed to identify published methods for developing and validating prediction models that enable risk estimation of outcomes under hypothetical interventions, utilizing causal inference. We aimed to identify the main methodological approaches, their underlying assumptions, targeted estimands, and potential pitfalls and challenges with using the method. Finally, we aimed to highlight unresolved methodological challenges.MethodsWe systematically reviewed literature published by December 2019, considering papers in the health domain that used causal considerations to enable prediction models to be used for predictions under hypothetical interventions. We included both methodologies proposed in statistical/machine learning literature and methodologies used in applied studies.ResultsWe identified 4919 papers through database searches and a further 115 papers through manual searches. Of these, 87 papers were retained for full-text screening, of which 13 were selected for inclusion. We found papers from both the statistical and the machine learning literature. Most of the identified methods for causal inference from observational data were based on marginal structural models and g-estimation.ConclusionsThere exist two broad methodological approaches for allowing prediction under hypothetical intervention into clinical prediction models: (1) enriching prediction models derived from observational studies with estimated causal effects from clinical trials and meta-analyses and (2) estimating prediction models and causal effects directly from observational data. These methods require extending to dynamic treatment regimes, and consideration of multiple interventions to operationalise a clinical decision support system. Techniques for validating 'causal prediction models' are still in their infancy.

Project description:BackgroundAn increasing number of patients expect and want to play a greater role in their treatment and care decisions. This emphasizes the need to adopt collaborative health care practices, which implies collaboration among interprofessional health care teams and patients, their families, caregivers, and communities. In recent years, digital health technologies that support self-care and collaboration between the community and health care providers (ie, participatory health technologies) have received increasing attention. However, knowledge regarding the features of such technologies that support effective patient-professional partnerships is still limited.ObjectiveThis study aimed to map and assess published studies on participatory health technologies intended to support partnerships among patients, caregivers, and health care professionals in chronic care, focusing specifically on identifying the main features of these technologies.MethodsA scoping review covering scientific publications in English between January 2008 and December 2020 was performed. We searched PubMed and Web of Science databases. Peer-reviewed qualitative, quantitative, and mixed methods studies that evaluated digital health technologies for patient-professional partnerships in chronic care settings were included. The data were charted and analyzed thematically. The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist was used.ResultsThis review included 32 studies, reported in 34 papers. The topic of participatory health technologies experienced a slightly increasing trend across publication years, with most papers originating from the United States and Norway. Diabetes and cardiovascular diseases were the most common conditions addressed. Of the 32 studies, 12 (38%) evaluated the influence of participatory health technologies on partnerships, mostly with positive outcomes, although we also identified how partnership relationships and the nature of collaborative work could be challenged when the roles and expectations between users were unclear. Six common features of participatory health technologies were identified: patient-professional communication, self-monitoring, tailored self-care support, self-care education, care planning, and community forums for peer-to-peer interactions.ConclusionsOur findings emphasize the importance of clarifying mutual expectations and carefully considering the implications that the introduction of participatory health technologies may have on the work of patients and health care professionals, both individually and in collaboration. A knowledge gap remains regarding the use of participatory health technologies to effectively support patient-professional partnerships in chronic care management.