Dataset Information

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis.

ABSTRACT: BACKGROUND:Electronic health (eHealth) tools are increasingly being applied in health care. They are expected to improve access to health care, quality of health care, and health outcomes. Although the advantages of using these tools in health care are well described, it is unknown to what extent eHealth tools are effective when used by vulnerable population groups, such as the elderly, people with low socioeconomic status, single parents, minorities, or immigrants. OBJECTIVE:This study aimed to examine whether the design and implementation characteristics of eHealth tools contribute to better use of these tools among vulnerable groups. METHODS:In this systematic review, we assessed the design and implementation characteristics of eHealth tools that are used by vulnerable groups. In the meta-analysis, we used the adherence rate as an effect size measure. The adherence rate is defined as the number of people who are repetitive users (ie, use the eHealth tool more than once). We also performed a meta-regression analysis to examine how different design and implementation characteristics influenced the adherence rate. RESULTS:Currently, eHealth tools are continuously used by vulnerable groups but to a small extent. eHealth tools that use multimodal content (such as videos) and have the possibility for direct communication with providers show improved adherence among vulnerable groups. CONCLUSIONS:eHealth tools that use multimodal content and provide the possibility for direct communication with providers have a higher adherence among vulnerable groups. However, most of the eHealth tools are not embedded within the health care system. They are usually focused on specific problems, such as diabetes or obesity. Hence, they do not provide comprehensive services for patients. This limits the use of eHealth tools as a replacement for existing health care services.

SUBMITTER: Arsenijevic J

PROVIDER: S-EPMC7055852 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis.

Arsenijevic Jelena J Tummers Lars L Bosma Niels N

Journal of medical Internet research 20200206 2

<h4>Background</h4>Electronic health (eHealth) tools are increasingly being applied in health care. They are expected to improve access to health care, quality of health care, and health outcomes. Although the advantages of using these tools in health care are well described, it is unknown to what extent eHealth tools are effective when used by vulnerable population groups, such as the elderly, people with low socioeconomic status, single parents, minorities, or immigrants.<h4>Objective</h4>This ...[more]

PMID: 32027311

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Project description:ObjectivesThe objective of this review was to assess the benefit of using electronic, mobile and telehealth tools for vulnerable patients with chronic disease and explore the mechanisms by which these impact patient self-efficacy and self-management.DesignWe searched MEDLINE, all evidence-based medicine, CINAHL, Embase and PsychINFO covering the period 2009 to 2018 for electronic, mobile or telehealth interventions. Quality was assessed according to rigour and relevance. Those studies providing a richer description ('thick') were synthesised using a realist matrix.Setting and participantsStudies of any design conducted in community-based primary care involving adults with one or more diagnosed chronic health condition and vulnerability due to demographic, geographic, economic and/or cultural characteristics.ResultsEighteen trials were identified targeting a range of chronic conditions and vulnerabilities. The data provided limited insight into the mechanisms underpinning these interventions, most of which sought to persuade vulnerable patients into believing they could self-manage their conditions through improved symptom monitoring, education and support and goal setting. Patients were relatively passive in the interaction, and the level of patient response attributed to their intrinsic level of motivation. Health literacy, which may be confounded with motivation, was only measured in one study, and eHealth literacy was not assessed.ConclusionsResearch incorporating these tools with vulnerable groups is not comprehensive. Apart from intrinsic motivation, health literacy may also influence the reaction of vulnerable groups to technology. Social persuasion was the main way interventions sought to achieve better self-management. Efforts to engage patients by healthcare providers were lower than expected. Use of social networks or other eHealth mechanisms to link patients and provide opportunities for vicarious experience could be further explored in relation to vulnerable groups. Future research could also assess health and eHealth literacy and differentiate the specific needs for vulnerable groups when implementing health technologies.

Project description:BackgroundElectronic health (eHealth) has the potential to improve health outcomes. However, eHealth systems need to match the eHealth literacy needs of users to be equitably adopted. Socially disadvantaged groups have lower access and skills to use technologies and are at risk of being digitally marginalized, leading to the potential widening of health disparities.ObjectiveThis systematic review aims to explore the role of eHealth literacy and user involvement in developing eHealth interventions targeted at socially disadvantaged groups.MethodsA systematic search was conducted across 10 databases for eHealth interventions targeted at older adults, ethnic minority groups, low-income groups, low-literacy groups, and rural communities. The eHealth Literacy Framework was used to examine the eHealth literacy components of reviewed interventions. The results were analyzed using narrative synthesis.ResultsA total of 51 studies reporting on the results of 48 interventions were evaluated. Most studies were targeted at older adults and ethnic minorities, with only 2 studies focusing on low-literacy groups. eHealth literacy was not considered in the development of any of the studies, and no eHealth literacy assessment was conducted. User involvement in designing interventions was limited, and eHealth intervention developmental frameworks were rarely used. Strategies to assist users in engaging with technical systems were seldom included in the interventions, and accessibility features were limited. The results of the included studies also provided inconclusive evidence on the effectiveness of eHealth interventions.ConclusionsThe findings highlight that eHealth literacy is generally overlooked in developing eHealth interventions targeted at socially disadvantaged groups, whereas evidence about the effectiveness of such interventions is limited. To ensure equal access and inclusiveness in the age of eHealth, eHealth literacy of disadvantaged groups needs to be addressed to help avoid a digital divide. This will assist the realization of recent technological advancements and, importantly, improve health equity.

Project description:ObjectivesTo identify barriers that are common and unique to six selected vulnerable groups: low socioeconomic status; Indigenous; mental illness and substance abuse; homeless; prisoners; and at-risk youth.DesignA systematic review was carried out to identify the perceived barriers to smoking cessation within six vulnerable groups.Data sourcesMEDLINE, EMBASE, CINAHL and PsycInfo were searched using keywords and MeSH terms from each database's inception published prior to March 2014.Study selectionStudies that provided either qualitative or quantitative (ie, longitudinal, cross-sectional or cohort surveys) descriptions of self-reported perceived barriers to quitting smoking in one of the six aforementioned vulnerable groups were included.Data extractionTwo authors independently assessed studies for inclusion and extracted data.Results65 eligible papers were identified: 24 with low socioeconomic groups, 16 with Indigenous groups, 18 involving people with a mental illness, 3 with homeless groups, 2 involving prisoners and 1 involving at-risk youth. One study identified was carried out with participants who were homeless and addicted to alcohol and/or other drugs. Barriers common to all vulnerable groups included: smoking for stress management, lack of support from health and other service providers, and the high prevalence and acceptability of smoking in vulnerable communities. Unique barriers were identified for people with a mental illness (eg, maintenance of mental health), Indigenous groups (eg, cultural and historical norms), prisoners (eg, living conditions), people who are homeless (eg, competing priorities) and at-risk youth (eg, high accessibility of tobacco).ConclusionsVulnerable groups experience common barriers to smoking cessation, in addition to barriers that are unique to specific vulnerable groups. Individual-level, community-level and social network-level interventions are priority areas for future smoking cessation interventions within vulnerable groups.Trial registration numberA protocol for this review has been registered with PROSPERO International Prospective Register of Systematic Reviews (Identifier: CRD42013005761).

Project description:BackgroundThe recent, rapid development of digital technologies offers new possibilities for more efficient implementation of electronic health record (EHR) and personal health record (PHR) systems. A growing volume of healthcare data has been the hallmark of this digital transformation. The large healthcare datasets' complexity and their dynamic nature pose various challenges related to processing, analysis, storage, security, privacy, data exchange, and usability.Materials and methodsWe performed a systematic review of systematic reviews to assess technological progress in EHR and PHR systems. We searched MEDLINE, Cochrane, Web of Science, and Scopus for systematic literature reviews on technological advancements that support EHR and PHR systems published between January 1, 2010, and October 06, 2020.ResultsThe searches resulted in a total of 2,448 hits. Of these, we finally selected 23 systematic reviews. Most of the included papers dealt with information extraction tools and natural language processing technology (n = 10), followed by studies that assessed the use of blockchain technology in healthcare (n = 8). Other areas of digital technology research included EHR and PHR systems in austere settings (n = 1), de-identification methods (n = 1), visualization techniques (n = 1), communication tools within EHR and PHR systems (n = 1), and methodologies for defining Clinical Information Models that promoted EHRs and PHRs interoperability (n = 1).ConclusionsTechnological advancements can improve the efficiency in the implementation of EHR and PHR systems in numerous ways. Natural language processing techniques, either rule-based, machine-learning, or deep learning-based, can extract information from clinical narratives and other unstructured data locked in EHRs and PHRs, allowing secondary research (i.e., phenotyping). Moreover, EHRs and PHRs are expected to be the primary beneficiaries of the blockchain technology implementation on Health Information Systems. Governance regulations, lack of trust, poor scalability, security, privacy, low performance, and high cost remain the most critical challenges for implementing these technologies.

Project description:BACKGROUND:Generative participatory design (PD) may help in developing electronic health (eHealth) interventions. PD is characterized by the involvement of all stakeholders in creative activities. This is different from the traditional user-centered design, where users are less involved. When looking at PD from a research through design perspective, it is important to summarize the reasons for choosing a certain form of generative PD to further develop its methodology. However, the scientific literature is currently unclear about which forms of PD are used to develop eHealth and which arguments are used to substantiate the decision to use a certain form of generative PD. OBJECTIVE:This study aimed to explore the reporting and substantiation of generative PD methodologies in empirical eHealth studies published in scientific journals to further develop PD methodology in the field of eHealth. METHODS:A systematic literature review following the Cochrane guidelines was conducted in several databases (EMBASE, MEDLINE Ovid, Web of Science, and CINAHL EBSCOhost). Data were extracted on the recruitment and management of stakeholders, the use of tools, and the use of outcome measures. RESULTS:Of the 3131 studies initially identified, 69 were selected for qualitative synthesis. The reporting was very variable, depending to a large extent on whether the study stated that reporting on the PD process was a major aim. The different levels of reporting and substantiation of the choices of a recruitment strategy, stakeholder management, and tools and outcome measures are presented. Only a few authors explicitly used arguments directly related to PD guiding principles such as democratic, mutual learning, tacit and latent knowledge, and collective creativity. Even though PD principles were not always explicitly discussed in the method descriptions of the studies, they were implicitly present, mostly in the descriptions of the use of PD tools. The arguments used to substantiate the choices made in stakeholder management, PD tools, and the type of outcome measures adopted point to the involvement of PD principles. CONCLUSIONS:Studies that have used a PD research methodology to develop eHealth primarily substantiate the choice of tools made and much less the use of stakeholders and outcome measures.

Project description:BACKGROUND:Electronic health (eHealth) is increasingly used for self-management and service delivery of HIV-related diseases. With the publication of studies increasingly focusing on antiretroviral therapy (ART) adherence, this makes it possible to quantitatively and systematically assess the effectiveness and feasibility of eHealth interventions. OBJECTIVE:The purpose of this review was to explore the effectiveness of eHealth interventions on improving ART adherence in people living with HIV. The effects of different intervention characteristics, participant characteristics, and study characteristics were also assessed. METHODS:We systematically searched MEDLINE (via PubMed), EMBASE, the Cochrane Central Register of Controlled Trials, and 3 conference abstract databases using search terms related to HIV, ART, adherence, and eHealth interventions. We independently screened the studies, extracted the data, and assessed the study quality and then compared the information in pairs. Articles published in English that used randomized controlled trials to assess eHealth interventions to improve ART adherence of people living with HIV were identified. We extracted the data including study characteristics, participant characteristics, intervention characteristics, and outcome measures. The Cochrane risk-of-bias tool was used to assess the risk of bias and study overall quality. Odds ratios, Cohen d, and their 95% CIs were estimated using random-effects models. We also performed multiple subgroup analyses and sensitivity analyses to define any sources of heterogeneity. RESULTS:Among 3941 articles identified, a total of 19 studies (including 21 trials) met the inclusion criteria. We found 8 trials from high-income countries and 13 trials from low- and middle-income countries. Furthermore, at baseline, the health status of participants in 14 trials was healthy. Of the trials included, 7 of 21 used personality content, 12 of 21 used a 2-way communication strategy, and 7 of 21 used medical content. In the pooled analysis of 3937 participants (mean age: 35 years; 47.16%, 1857/3937 females), eHealth interventions significantly improved the ART adherence of people living with HIV (pooled Cohen d=0.25; 95% CI 0.05 to 0.46; P=.01). The interventions were also correlated with improved biochemical outcomes reported by 11 trials (pooled Cohen d=0.25; 95% CI 0.11 to 0.38; P<.001). The effect was sensitive to sample size (Q=5.56; P=.02) and study duration (Q=8.89; P=.003), but it could not be explained by other moderators. The primary meta-analysis result was stable in the 3 sensitivity analyses. CONCLUSIONS:Some of the eHealth interventions may be used as an effective method to increase the ART adherence of people living with HIV. Considering that most of the trials included a small sample size and were conducted for a short duration, these results should be interpreted with caution. Future studies need to determine the features of eHealth interventions to better improve ART adherence along with long-term effectiveness of interventions, effectiveness of real-time adherence monitoring, enhancement of study design, and influences on biochemical outcomes.

Project description:IntroductionElectronic adherence monitoring (EAM) is increasingly used to improve adherence. However, there is limited evidence on the effect of EAM in across chronic conditions and on patient acceptability. We aimed to assess the effect of EAM on adherence and clinical outcomes, across all ages and all chronic conditions, and examine acceptability in this systematic review and meta-analysis.MethodsA systematic search of Ovid MEDLINE, EMBASE, Social Work Abstracts, PsycINFO, International Pharmaceutical Abstracts and CINAHL databases was performed from database inception to December 31, 2020. Randomised controlled trials (RCTs) that evaluated the effect of EAM on medication adherence as part of an adherence intervention in chronic conditions were included. Study characteristics, differences in adherence and clinical outcomes between intervention and control were extracted from each study. Estimates were pooled using random-effects meta-analysis, and presented as mean differences, standardised mean differences (SMD) or risk ratios depending on the data. Differences by study-level characteristics were estimated using subgroup meta-analysis to identify intervention characteristics associated with improved adherence. Effects on adherence and clinical outcomes which could not be meta-analysed, and patient acceptability, were synthesised narratively. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guideline was followed, and Risk of bias (RoB) assessed using the Cochrane Collaboration's RoB tool for RCTs. The review is registered with PROSPERO CRD42017084231.FindingsOur search identified 365 studies, of which 47 studies involving 6194 patients were included. Data from 27 studies (n = 2584) were extracted for the adherence outcome. The intervention group (n = 1267) had significantly better adherence compared to control (n = 1317), (SMD = 0.93, CI:0.69 to 1.17, p<0.0001) with high heterogeneity across studies (I2 = 86%). There was a significant difference in effect according to intervention complexity (p = 0.01); EAM only improved adherence when used with a reminder and/or health provider support. Clinical outcomes were measured in 38/47 (81%) of studies; of these data from 14 studies were included in a meta-analysis of clinical outcomes for HIV, hypertension and asthma. In total, 13/47 (28%) studies assessed acceptability; patient perceptions were mixed.InterpretationPatients receiving an EAM intervention had significantly better adherence than those who did not, but improved adherence did not consistently translate into clinical benefits. Acceptability data were mixed. Further research measuring effects on clinical outcomes and patient acceptability are needed.

Dataset Information

Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis.

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Adherence to Electronic Health Tools Among Vulnerable Groups: Systematic Literature Review and Meta-Analysis.

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