The acceptability and effectiveness of eHealth interventions to support assessment and decision-making for people with dementia living in care homes: A systematic review

Introduction

Dementia is a progressive and terminal syndrome. It is the leading cause of death in the UK (Office of National Statistics, 2020) and globally (Feigin et al., 2019). By 2040, the number of people living with dementia in the UK is projected to increase by over 80% (Wittenberg et al., 2019) and a global increase of 185% by 2050 (Prince et al., 2015). Dementia is characterized by a deterioration in cognitive function, and wider brain functions, which presents as multiple complex care needs that often requires 24-h personalized care until the end of life. This care may be provided by a care home. It is estimated that 70% of care home residents in England are living with dementia, with the average life expectancy on admission to a care home of 1–2 years (British Geriatrics Society, 2020). In total, 58% of all deaths from dementia take place in care homes (Public Health England, 2016).

Assessment and management of care needs for people with dementia can often be challenging due to deteriorating verbal communication. This can cause under detection of distressing symptoms and concerns, leading to unmet needs, increasing distress and compromised quality of life (Corbett et al., 2012). Care home staffs' intrinsic familiarity with their residents means they are well-positioned to assess and identify changes in needs and requirements for care by working with external healthcare providers, such as specialist dementia or palliative care (Hendrix et al., 2003; Ellis-Smith et al., 2017).

The eHealth interventions can facilitate integration with external healthcare professionals by providing remote access to clinical expertise and assessment, and monitoring systems. eHealth is defined as “health services and information delivered or enhanced through the internet and related technologies” (Eysenbach, 2001). eHealth interventions vary widely from an electronic tablet used to video call an external professional to an electronic record to a system that collates multiple data sources to create a visualization. They have been demonstrated to support assessment and management of needs in care homes (Gillespie et al., 2019) and can be used in the care home alone, or to report assessments to external services, such as the General Practitioner (GP). eHealth interventions have been shown to improve resident outcomes, particularly in reducing hospitalisations (Gillespie et al., 2019), an outcome associated with more risk for people living with dementia (Shepherd et al., 2019). Due to the COVID-19 pandemic and subsequent restrictions around visiting in care homes, the use of eHealth interventions has increased rapidly, and recent evidence suggests that this is likely to remain once all pandemic restrictions have been eased (Warmoth et al., 2022). Therefore, it is important to understand how eHealth might impact the lives of residents, families, and staff. Currently, little is known about which components of eHealth interventions are acceptable to residents living with dementia, their families and staff and which are effective at improving outcomes. This review aimed to (1) identify the components, (2) explore the acceptability to residents with dementia, their family, and staff, and (3) consider the effectiveness of eHealth interventions to support assessment and decision-making for people living with dementia in care homes.

Methods

A mixed methods systematic review using narrative synthesis was conducted following Popay's et al. (2006) guidance (Popay et al., 2006) to identify components, explore acceptability, and consider the effectiveness of eHealth interventions to support assessment and decision-making for those living with dementia in care homes. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Supplementary material 1. PRISMA Checklist). The protocol was registered on PROSPERO (CRD42021254967).

Search strategy

The following four databases Embase, PsycINFO, MEDLINE and CINAHL were searched for studies published in English from January 2000 to July 2021. A scoping review of the literature and an Information Support specialist supported the development of the search strategy. Medical Subject Headings (MeSH) terms included dementia AND care homes AND eHealth AND assessment OR decision-making (Supplementary material 2. Search Strategy). Reference chaining and citation tracking were also used to complement the search strategy.

Eligibility criteria

Participants: Residents of a long-term care facility with a diagnosis of dementia, including within a mixed participant population. Short-term care facilities were excluded.

Intervention: eHealth interventions to support comprehensive assessment of residents and/or to improve decision-making about care and treatment. Non-digitized interventions were out of the scope of this review.

Outcome: All outcome measures relating to acceptability and effectiveness of eHealth interventions used to improve assessment and decision-making on care and treatment in care homes.

Comparator: No restrictions.

Study design: All study designs that report acceptability and effectiveness outcomes relating to assessment and decision-making surrounding care and treatment were eligible for inclusion. Non-English language studies, opinion pieces, editorials, and PhD theses were excluded.

Study selection

Identified studies were managed using the EndNote X9 reference management system. Two reviewers screened all titles and abstracts (IT and JG) with a review of a random 20% of articles by another blind reviewer (EY, JA, and CH) to assess the rigor of the eligibility criteria by reviewing consistency between reviewers. Two reviewers (IT and JG) considered all full-text articles for eligibility and discussed any uncertainty encountered. Uncertainty that could not be resolved was discussed with the wider research team.

Quality appraisal

Quality was appraised using the appropriate Critical Appraisal Skills Programme (CASP) tool (CASP Checklists, 2022), the Mixed Methods Appraisal Tool (MMAT) (Hong et al., 2018), and Joanna Briggs Institute (JBI) tool (Critical Apprasial Tools, 2005) depending on the study design. The CASP checklists were used to report on quality of RCT's, cohort, and qualitative studies. Quasi-experimental studies were assessed by the JBI tool and mixed methods, and descriptive studies were assessed using the MMAT. Quality appraisal was used to interpret the findings; therefore, no studies were excluded based on quality appraisal. All quality appraisals were completed independently by two researchers (JG and IT) with 10% checked (CJE, ND, and CH) for consistency.

Data extraction and synthesis

The data extraction template was informed by the review questions and PRISMA reporting guidance. The template included title, lead author, date of publication, country of study, aim of study, study design, eHealth intervention (type, components, and summary), methods of data collection and analysis, outcomes, implications, and limitations. Data extraction was completed by five researchers (IT, JG, EY, JA, and CH). All extracted data were checked by two researchers (IT and JG).

Quantitative and qualitative data were extracted. Quantitative data on effectiveness were too heterogeneous to pool for meta-analysis. Therefore, we conducted an integrative synthesis to produce a narrative summary (Dixon-Woods et al., 2005) of both quantitative and qualitative data categorized by acceptability or effectiveness. Findings were triangulated in the interpretation (O'Cathain et al., 2010).

Results

The search strategies yielded 1,988 results. An additional 14 articles were included from alternative sources. Following removal of duplicates, a total of 1,359 articles were screened at title and abstract, and 182 full-text articles were reviewed (Figure 1 PRISMA Flow Diagram). Twenty-six articles reporting twenty-four eHealth interventions were included in this review (summary of evidence in Figure 2).

Figure 1. PRISMA flow diagram.

Figure 2. Summary of evidence.

eHealth interventions to support assessment and decision-making for people with dementia in care homes were categorized as video consultations (n = 9) (Lyketsos et al., 2001; Weiner et al., 2003; Wakefield et al., 2004; O'Mahony et al., 2009; Catic et al., 2014; Gordon et al., 2016; Salles et al., 2017; Perri et al., 2020; Piau et al., 2020), electronic health records (EHRs; n = 5) (Daly et al., 2002; Krüger et al., 2011; Munyisia et al., 2011; Pillemer et al., 2012; Shiells et al., 2020), multicomponent interventions (constructed of more than one intervention, such as video consultations with digital assessment systems and EHRs; n = 4) (Lee et al., 2000; De Luca et al., 2016; De Vito et al., 2020; Wang et al., 2021), digital decision support tools (n = 4) (Fossum et al., 2011; Moniz-Cook et al., 2017; Mitchell et al., 2018, 2020), digital assessment tools (n = 2) (Vuorinen, 2020; Zahid et al., 2020), and personal devices (n = 2) (Qadri et al., 2009; Klein et al., 2018). Studies were categorized as observational exploring the acceptability of the intervention using quantitative (n = 2 cross-sectional; n = 2 cohort; n = 1 descriptive), qualitative (n = 5), and mixed methods (n = 3), or experimental to evaluate the effectiveness and/or acceptability of interventions (n = 5 RCTs; n = 8 quasi-experimental).

Quality appraisal

The included studies were of mixed, but overall high–moderate quality. Full-quality assessment can be found in Table 1. The CASP checklists identified strong reporting of aims, appropriate methodologies, and consideration of ethical issues. The CASP criteria identified weaknesses centered around reporting of benefit, recruitment strategies, and use of blinding. Overall, quasi-experimental studies were of good quality (77.7% met JBI criteria). The cross-sectional study was of moderate quality (50% of JBI criteria met). Mixed methods studies were of moderate quality. The reasoning for mixed methods design was often well-presented within the studies. However, interpretation of results from data was often unclear. Other common issues compromising quality included, confounding factors not considered in the data analysis, comparisons between groups not reported, and insufficient information to assess if quality criteria were adequately met. One descriptive study was assessed as high quality.

Table 1. Study characteristics, intervention components, and acceptability of eHealth interventions.

Components and acceptability

Video consultations

Video consultations were the most common eHealth intervention identified (n = 9) (Lyketsos et al., 2001; Weiner et al., 2003; Wakefield et al., 2004; O'Mahony et al., 2009; Catic et al., 2014; Gordon et al., 2016; Salles et al., 2017; Perri et al., 2020; Piau et al., 2020). Video consultations involved an external multidisciplinary team (MDT), care home staff, often residents and, sometimes, their families. Residents, and families, were not involved when consultations were used to discuss more than one resident. The main component of the consultations was to provide care home staff with remote access to MDT expertise and fostered integrated care. MDTs varied in their structure but included professionals such as medical doctors, such as psychiatrist and family physician, nurses, geriatricians, and social workers. The format of consultations varied across studies, for example, length of consultations, scheduling routes, and use of staff champions to initiate and facilitate consultations.

Five studies examined the acceptability of video consultations (Weiner et al., 2003; Wakefield et al., 2004; Salles et al., 2017; Perri et al., 2020; Piau et al., 2020). One study found that overall, families were satisfied with video consultations (86%) with palliative care teams, particularly with the technology, comfort, and privacy, but 70% would still prefer a face-to-face consultation (Perri et al., 2020). However, another study found that only 14% of residents preferred face-to-face hospital appointments, and 88% would be willing to use video consultations again to avoid traveling to the appointment (Wakefield et al., 2004).

Care home staff also demonstrated willingness to use video consultations again, and reported that they enabled timely access to palliative care specialists and enhanced provision of care (Perri et al., 2020), particularly in remote locations (Piau et al., 2020). Importantly, consultations resulted in improved knowledge for care home staff, and staff felt their work was better valued by external professionals (Piau et al., 2020). In addition, staff found that follow-up reports from external professionals were easy to interpret and of good quality (Salles et al., 2017). Care home physicians reported a slight improvement in care and no change in workload (Weiner et al., 2003). However, staff cited challenges of commitment from external professionals, and lack of time and workforce in the care home to participate in consultations (Piau et al., 2020). This hindered integrated working between the care home and external professionals.

Electronic health records

Five studies examined the use of EHRs (Daly et al., 2002; Krüger et al., 2011; Munyisia et al., 2011; Pillemer et al., 2012; Shiells et al., 2020), implemented with the intention to improve shared decision-making and increase efficiency of staff time. Common components included training for staff to use EHR (including on equipment), staff allocated specific roles, task reminders, and multiple points of access, such as at the point of care (e.g., resident's beside) and remotely (outside the care home).

Four studies included acceptability data: three for staff (Krüger et al., 2011; Munyisia et al., 2011; Shiells et al., 2020), and one study considering residents (Pillemer et al., 2012). EHRs supported staff to perform their roles better; 72% (n = 117) reported that the reminders were useful, 83% (n = 226) reported that EHRs contributed to safer use of medication (Krüger et al., 2011), and daily progress notes enabled timely updates on resident's needs (Munyisia et al., 2011). An increase in staff job satisfaction was also observed (43%, n = 117) (Krüger et al., 2011). However, frustrations arose around interoperability between services, such as the care home and hospital using different EHR systems. Staff also disliked the inability to customize EHRs to a level that is appropriate for all staff and residents with dementia to avoid input of irrelevant information (Shiells et al., 2020). Preferences on point of access differed among staff, with some preferring at the point of care, with others considering this intrusive and preferring to access the EHR at a desktop computer (Shiells et al., 2020). However, 69% (n = 297) of residents felt that staff accessing an EHR in their presence did not interfere with care, and over 70% (n = 303) felt that the EHR helped staff to manage care better with 30% (n = 131) reporting an improvement in care (Pillemer et al., 2012).

Multicomponent interventions

Four studies focused on multicomponent interventions (Lee et al., 2000; De Luca et al., 2016; De Vito et al., 2020; Wang et al., 2021). The included interventions were constructed of two or more components. Components included electronic records, care plans and alerts, staff training (including an education database), video consultations, digital platform, use of medical equipment such as x-ray scanners, and activity trackers. These interventions intended to support integrated working between decision-makers (Lee et al., 2000) and to improve management of a resident's care through monitoring (Lee et al., 2000; De Luca et al., 2016; De Vito et al., 2020; Wang et al., 2021).

Care staff liked the ability to identify patterns of behavior (De Vito et al., 2020) and interventions that provided them with tangible evidence that confirmed their beliefs about a resident's symptoms and concerns to discuss with external professionals (Wang et al., 2021). In one study, a digital platform collated location data alongside qualitative contextual data input by staff to display resident routines over time which were shared with external professionals (Wang et al., 2021).

For me, since I am not in the ward myself, I normally talk with the caregivers [care home staff]; it is good to see how often he [the resident] is in stress (from the collated data). [Psychologist] (Wang et al., 2021)

Family and staff both appreciated the adaptability of these interventions, including the ability to amend previously entered data (Lee et al., 2000). No studies examined the acceptability of multicomponent interventions for residents. However, staff reported that residents with dementia showed no discomfort when using activity trackers (De Vito et al., 2020), and became more familiar and comfortable with video consultations with external professionals with repeated use (Lee et al., 2000).

Digital decision support tools

Four studies explored decision support tools to enhance communication in advance care planning (Fossum et al., 2011; Moniz-Cook et al., 2017; Mitchell et al., 2018, 2020). Common components included collaborative working with a dementia care therapist and Advance Care Planning (ACP) specialists, ability to populate clinical information (either from integration with EHRs or within itself), training on use readily available and a designated member of staff to initiate and facilitate use.

One study examined the acceptability of digital decision support tools, focusing on family members. Family members watched video vignettes to support advance care planning on care options available to people with advanced dementia. Family members found the videos useful (68%, n = 144), and 97% (n = 205) of them would recommend the videos to others (Mitchell et al., 2018).

Digital assessment tools

Two studies examined digital assessment tools. One study compared a paper and digital app version of the Pain Assessment Checklist for Seniors with Limited Ability to Communicate (PACSLAC-II) tool (Zahid et al., 2020). The app was designed to be a literal interpretation of the paper version with the addition of collating and graphically displaying the results over time. Staff found the app version of the tool to be faster and easier to access and store data. The tool provided care staff with a common language and evidence of change in resident condition to other disciplines, but some staff felt their observations were ignored by external colleagues (Zahid et al., 2020).

Like I said, we look after these people, we're here more often with these people than we are with our own families. So, we know these people inside and out and so when we say that there's an issue or this person's off or they look like they're having a lot more pain, trust us….the doctor's only here once a week and he spends not very much time with these people and he comes in and he does his two minute assessment and says, ‘they look fine today, no let's hold off.' Really, now we have to go another seven whole days of more documentation for him to say, ‘well, I really don't know, we'll bump them up a little bit.' So, you know what I'm saying, it's the frustration of not being heard. [care staff] (Feigin et al., 2019)

Vuorinen (2020) evaluated the use of the nationwide mandated, web-based International Resident Assessment Instrument for Long-Term Care Facilities (interRAI-LTCF) to assess older adults' health and care needs. Use of the interRAI-LTCF provided staff with a comprehensive and multidisciplinary history of a resident, with information shared across care facilities, enhancing identification of change in a resident's condition (Vuorinen, 2020).

Personal devices

Personal devices were small, computer-like devices that enabled staff to access EHRs or assessments at the point of care. Two studies explored the use of personal devices. One study (Klein et al., 2018) described components as: a screening tool, web dashboard that included an education section, production of recommendations for care and feedback on which interventions to employ, and availability of the tool on multiple formats, such as the web and mobile apps. Both studies found that care home staff were receptive to using personal devices that removed time-wasting paperwork increasing time to address residents' needs (Qadri et al., 2009; Klein et al., 2018). Staff particularly liked the ability to identify patterns and factors associated with distressing symptoms and challenging behavior (Klein et al., 2018) and learning about better ways to care for their residents (Qadri et al., 2009).

Evidence of effectiveness

Fifteen included studies considered the evidence of effectiveness of eHealth interventions (Table 2). Twelve studies reported resident outcomes (Lee et al., 2000; Daly et al., 2002; O'Mahony et al., 2009; Fossum et al., 2011; Krüger et al., 2011; Pillemer et al., 2012; Catic et al., 2014; De Luca et al., 2016; Gordon et al., 2016; Moniz-Cook et al., 2017; Mitchell et al., 2018, 2020), one study reported on family outcomes (Mitchell et al., 2018), four studies reported staff outcomes (O'Mahony et al., 2009; Moniz-Cook et al., 2017; Perri et al., 2020; Zahid et al., 2020), five studies evaluated outcomes of service delivery (Lyketsos et al., 2001; Daly et al., 2002; Catic et al., 2014; De Luca et al., 2016; Mitchell et al., 2020), and one study reported on economic evaluation (Moniz-Cook et al., 2017).

Table 2. Evidence of effectiveness of eHealth interventions by outcome type.

Resident outcomes

The eHealth interventions were shown to improve monitoring of resident outcomes which led to changes in prescribing. Studies of eHealth interventions using EHRs and video consultations demonstrated improved outcomes for residents, with those in the intervention groups less likely to be prescribed antipsychotic medications (33 vs. 21.5%, p = 0.015, 95% CI: 2.3–20.6) compared with internal controls (Krüger et al., 2011). EHRs with clinical care reminders led to increased use of warfarin (p = 0.013, 95% CI 1.6–12.1) and monitoring of residents' weight (p < 0.001, 95% CI: 47.5–64.5) (Krüger et al., 2011).

Video consultations also improved resident outcomes over time, although some specific improvements were not detailed (Lee et al., 2000; O'Mahony et al., 2009; Catic et al., 2014). Educational video consultations with an MDT led to a reduction in physical restraint (odds ratio, OR = 0.25, p = 0.05) and in urinary tract infections (OR = 0.77, p = 0.01) compared to matched controls (Gordon et al., 2016). Residents were also less likely to report time wasted at appointments when assessed by professionals in video consultations (p = 0.001) compared to those participating in face-to-face consultations (O'Mahony et al., 2009). One multicomponent intervention comprising 59 participants, that included video consultations, demonstrated significant reductions in depression (p < 0.01), mood (p < 0.05), blood pressure (p < 0.001), and heart rate (p < 0.05) and increase in quality of life (p < 0.001) compared to standard care controls (De Luca et al., 2016).

Mitchell et al. (2018) found that introducing an ACP decision support tool could support ACP for people with advanced dementia (N = 402). Residents whose family members watched an ACP video were more likely to have advance directives for no-tube feeding and documented goals-of-care discussions than residents whose family members who participated in usual ACP practices. However, the intervention did not result in a change in the overall proportion of Do Not Hospitalize directives or burdensome treatments (Mitchell et al., 2018, 2020). Do Not Hospitalize directives were only increased in the intervention group when family members preferred comfort care and when combined with no-tube feeding directives (72.2 vs. 52.8%, a OR, 2.68; 95% CI, 2.68–5.85) (Mitchell et al., 2018).

Family outcomes

One study found that ACP decision support tools did not change the proportion of family members preferring comfort care compared to those who participated in usual ACP practices (Mitchell et al., 2018).

Staff outcomes

The eHealth interventions were shown to improve care home staff knowledge, confidence and wellbeing. Video consultations with MDTs led to improved knowledge (p = 0.03) (O'Mahony et al., 2009) and confidence to deliver palliative care in this way (p = 0.002) (Perri et al., 2020). In addition, a reduction in paperwork due to digitized assessment tools resulted in lower levels of stress and burnout for staff (Zahid et al., 2020).

Service delivery outcomes

Three interventions that included video consultations with MDTs showed evidence of effectiveness at reducing the number of admissions to hospital in intervention groups (X² = 3.96, p < 0.05) (Lyketsos et al., 2001; Catic et al., 2014; De Luca et al., 2016), whereas decision support tools did not have any effect on hospital transfers or hospice enrolment (Mitchell et al., 2020).

An electronic health record that included a computerized care plan to support nurses to regularly monitor residents lead to significantly more nursing interventions (p = 0.001) and activities (p = 0.007) (Daly et al., 2002).

Economic outcomes

A decision support tool with staff development intervention was shown to cost £331 less than usual care. However, this was not a significant difference (Moniz-Cook et al., 2017). No other studies included economic evaluations.

Discussion

Twenty-six studies were identified evaluating the acceptability and/or effectiveness of eHealth interventions to support assessment and decision-making for people living with dementia in care homes. Seventeen studies reported acceptability data, and fifteen reported effectiveness data. The quality of studies was mixed but mostly moderate to high. There was heterogeneity across all aspects of included studies, from the interventions to outcomes evaluated. The studies also varied in their purpose of using the eHealth intervention, from increasing staff productivity to managing symptoms and improving care, including palliative care. Although some studies showed evidence of effectiveness, most studies had mixed or no effect on the stated outcomes. Only one study considered economic evaluation with focus on cost of an eHealth intervention compared with usual care and showed inconclusive findings. No studies considered cost-effectiveness of the eHealth interventions.

Findings from this review indicate that eHealth interventions that include a video consultation component were most likely to be acceptable to staff and residents. Video consultations suggested effectiveness in outcomes such as reducing use of physical restraint by 75% (Gordon et al., 2016) and hospitalisations (Lyketsos et al., 2001; Catic et al., 2014), which may reduce stress and increase comfort by enabling the person with dementia to remain in their usual place of care. A recent study found that hospitalisations increase steeply in the last year of life for people with dementia (Yorganci et al., 2022); hence, it is vital to utilize interventions to reduce or avoid hospitalisations. Residents with dementia were often able to participate in video consultations and showed satisfaction in the method of consultation and reduction in time wasted at appointments (O'Mahony et al., 2009). Resident outcomes of optimal prescribing of medications improved through use of video consultations compared with matched controls (Gordon et al., 2016). Residents' families were often invited to participate in video consultations. This increased feelings of being respected and trusting relationships (Perri et al., 2020). Video consultations significantly improved staff outcomes around knowledge and confidence. These findings corroborate findings from our related review on implementation of eHealth in care homes (Gillam et al., 2022). This identified that successful implementation requires staff training to increase knowledge, in turn improving staff and resident outcomes.

It is likely that video consultations were most acceptable to staff and residents as they facilitated integrated working with external professionals. Similar findings are reported from research on case-conferencing for people with dementia (Phillips et al., 2013). For staff, video consultations provided a dedicated space for ongoing, practical support and training with external professionals to manage residents' often multiple and complex care needs (Davies et al., 2011; Rivett et al., 2019). This ongoing supportive integration with external professionals provided opportunities for development akin to training which, when sustained, can build staff expertise and confidence (Rivett et al., 2019; Dowling et al., 2020). A workforce that is well-educated and supported provides better quality of care, including toward the end of life (Froggatt, 2000). Furthermore, eHealth interventions were acceptable to staff when they provided them with a common language and evidence of their intrinsic knowledge about a resident's condition to communicate with external professionals. For example, multicomponent interventions were preferred by care home staff when they produced a good visual representation or report of residents' condition overtime and shared with external professionals in video consultations. When visual representations of data are well-produced and interpreted, they contribute to the intervention's success by communicating data to all parties effectively and succinctly. This common language improved confidence, enabling staff to feel empowered and that their care was valued by external professionals. Empowerment was strengthened through video consultations that provide the opportunity for clarification of roles and shared decision-making with key professionals (Phillips et al., 2013). Feeling dismissed by and lack of commitment from external professionals was cited as a challenge to using an eHealth intervention in this review. This failure to recognize care home staff expertise is a known barrier to integrated working (Davies et al., 2011).

This review found evidence of positive outcomes from eHealth interventions that were supported by a structural level of integration between care homes and external professionals. Empowering care home staff is enhanced through investment in infrastructure, specifically around adequate resource and enabling positive leadership (Laschinger et al., 2013) as an individual's desire to participate in integrated working is often insufficient alone to improve outcomes (Goodman et al., 2016). For example, a nationwide mandate to complete eHealth intervention provided staff with a comprehensive, multidisciplinary history of the resident, enabling better care (Vuorinen, 2020). The Enhanced Care in Care Homes framework in England advocates for the use of eHealth interventions and integrated, multidisciplinary care, particularly with a mental health specialist, to support management of care for people with dementia (NHS England, 2016). In addition, the European Association of Palliative Care advocate for a multidisciplinary approach and utility of eHealth interventions as aspects of core competencies required by nursing homes (Gamondi et al., 2013a,b). These initiatives may work toward improving equity of provision of eHealth interventions by ensuring core components around integrated working are embedded in care homes at a structural level, such as access to specialists. With the increase in the use of eHealth interventions in care homes due to the COVID-19 pandemic, it is important that access is equitable for all (Warmoth et al., 2022).

This review found little evidence concerning resident and family acceptability of eHealth interventions to support assessment and decision-making and effectiveness on family outcomes. Although many of the eHealth interventions included the resident in their activity, this review found five studies that considered acceptability for residents', with only three studies that consulted with residents directly, and only one that considered the views of family members. Two studies in this review found that residents with dementia appreciated video consultations as they reduced time spent traveling to appointments (Wakefield et al., 2004; O'Mahony et al., 2009). People with dementia value participating in decision-making about their care (Daly et al., 2018) and play an important role in the development of eHealth interventions to support their care (Span et al., 2013). Where ability to participate is limited or compromised, researchers should seek solutions to enable people with dementia to participate, this might include seeking a personal proxy. Solutions have been offered in the MORECare_Capacity Statement (Evans et al., 2020). It is particularly important that residents with dementia participate in the development of eHealth interventions as the unprecedented uptake in use of eHealth interventions during caused by the COVID-19 pandemic and after is likely to remain (Shepherd et al., 2019).

Limitations

The review has demonstrated the acceptability and potential of eHealth interventions to enhance assessment and decision-making for residents with dementia in care homes and improve outcomes. However, the review has limitations. We adopted a broad inclusion criteria of effectiveness data, thereby including uncontrolled studies due to the limited number of controlled trials in this emergent field of eHealth. We recognize that the inclusion of uncontrolled studies may have introduced some biases in the findings. In addition, the review was limited by the heterogeneity of the studies included meaning we were unable to perform any meta-analyses to draw strong conclusions and limited this review to an integrative synthesis and narrative summary of the evidence. We wish to acknowledge that all, except one, studies were conducted in the Americas or Europe, and all were conducted in high-income countries. This leads to a gap in knowledge about acceptability and effectiveness of eHealth interventions for people with dementia in care homes in other cultures. We propose that future research explores the acceptability and effectiveness of eHealth in low- and middle-income countries and non-Western cultures. Finally, gray literature was not included in this review leaving potential for publication bias. Gray literature was reviewed and excluded due to limited relevant data available. This may have led to exclusion of some relevant data.

Conclusions

Findings from this review suggest that eHealth interventions are overall acceptable for staff and have potential to improve outcomes. Most evidence was found for video consultations. Interventions with a video consultation component were shown to be effective at improving resident and staff outcomes. Video consultations with external MDTs were particularly well-received by staff to strengthen knowledge and confidence through regular, supportive, and practical training opportunities. EHRs, digital assessment tools, and personal devices support consistent assessment and monitoring of symptoms over time to identify patterns and improve care and outcomes. Multicomponent interventions build on the work of EHRs by providing enhanced data collection methods, contributing to a detailed assessment, and monitoring. The digitisation of assessment and decision-making tools provides an efficient way of working with a common language for care home staff to communicate with external professionals. Commitment from care home staff can support implementation, but structural level commitment, through supportive infrastructure, and commitment from external professionals is also required to ensure equity of provision to eHealth interventions and access to external professionals. It is important that future research explores the acceptability of eHealth interventions for residents with dementia and their families, how eHealth might affect family outcomes, and if eHealth is a cost-effective way of improving outcomes for residents with dementia. Further work should also focus on eHealth interventions for residents with dementia in low- and middle-income countries.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

IT, JG, ND, CE-S, and CJE designed the study. IT, JG, and CH contributed to the data screening, extraction, and analysis. VV reviewed the evidence on effectiveness. IT wrote the manuscript. All authors contributed to the revisions and approved the final manuscript.

Funding

The programme EMBED-Care – Empowering better end-of-life dementia care was funded by the Economic and Social Research Council (ESRC)/National Institute for Health and Care Research (NIHR), Dementia Initiative 2018 (Grant reference number ES/S010327/1), EMBED-Care is a joint study between University College London (UCL) and King's College London (KCL). IT was funded by NIHR Pre-Doctoral Fellowship (NIHR301985). CJE was funded by a Health Education England/NIHR Senior Clinical Lectureship (ICA-SCL-2015-01-001). ND was supported by a fellowship from the Alzheimer's Society, United Kingdom (Grant Number AS-JF-16b-012). The EMBED-Care programme was supported by the NIHR Applied Research Collaborations for South London, and Kent, Surrey, and Sussex.

Acknowledgments

The authors would like to thank Adam Garside, an information support specialist at King's College London, who helped with the development of the search strategy. The authors would also like to thank Jestofunmi Aworinde and Emel Yorganci for initial data screening and extraction.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Author disclaimer

The views expressed were those of the authors and not necessarily those of the ESRC, NIHR, or the Department of Health and Social Care.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frdem.2022.977561/full#supplementary-material

References