Digital technologies for monitoring and improving treatment adherence in children and adolescents with asthma: A scoping review of randomised controlled trials
1Centre for Health Technology, School of Nursing and Midwifery, University of Plymouth, Plymouth, PL4 6DT, UK
2Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, W6 8RP, UK
*Corresponding author: Edward Meinert, MA, MSc, MBA, MPA, PhD, University of Plymouth, Centre for Health Technology, Faculty of Health, 6 Kirkby Place, Room 2, Plymouth, PL4 6DT, United Kingdom, Phone: +44 1752 600600, Email: edward.meinert@plymouth.ac.ukAbstract
Background
Inadequate paediatric asthma care has resulted in potentially avoidable unplanned hospital admissions and morbidity. A wide variety of digital technologies have been developed to help monitor and support treatment adherence for children and adolescents with asthma. However, existing reviews need to be updated and expanded to provide an overview of the current state of research around these technologies and how they are being integrated into existing healthcare services and care pathways.
Objective
The purpose of this scoping review is to provide an overview of the current research landscape and knowledge gaps regarding the use of digital technologies to support the care of children and adolescents with asthma.
Methods
The review was structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) and Population, Intervention, Comparator, Outcome, and Study (PICOS) frameworks. Five databases (PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, EMBASE, and PsycINFO) were systematically searched for studies published in English from 2014 on. One reviewer screened references, selected studies for inclusion based on the eligibility criteria, and extracted the data, which were synthesised in a descriptive analysis.
Results
A wide variety in study characteristics - including the number and age of participants, study duration, and type of digital intervention - was identified. There was mixed evidence for the effectiveness of the interventions; 6 of the 9 studies that evaluated treatment adherence found improvements, but the evidence was inconsistent for asthma control (4/9 found no evidence of effectiveness, and only one found significant evidence) and health outcome variables (4/7 found no evidence of effectiveness). The 5 studies that examined patient perceptions and assessments of acceptability and usability had generally positive findings.
Conclusions
Despite the range of different digital interventions being developed to support the monitoring and treatment adherence of children and adolescents with asthma, there is limited evidence to suggest that they achieve their range of intended outcomes. Stronger evidence of their effectiveness at achieving their specific aims is needed, as this will support decisions and research about their cost-effectiveness and how these technologies can best integrate with existing clinical care pathways. This research is necessary to determine which interventions are worth supporting and adopting in the clinical care pathways.
Article notes
Competing Interest Statement
The authors have declared no competing interest.
Clinical Protocols
Funding Statement
This research was supported by the Centre for Health Technology at the University of Plymouth.
Introduction
Background
Globally, and in the UK, asthma is the most common chronic illness affecting children [1–3] and can have serious health consequences. It is one of the key causes of urgent hospital admissions and morbidity in children [3,4]. This is a particularly urgent problem in the UK: out of all the Organisation for Economic Co-operation and Development (OECD) countries, the UK has the third highest risk of death due to paediatric asthma [3]. Asthma-related hospital admissions contribute to the economic burden on the UK healthcare system [5]. It has been estimated that up to two thirds of asthma-related hospital admissions could potentially be avoided through improvements to preventative care systems [4]. The variation of mortality across countries suggests that many of the negative outcomes of childhood asthma - for patients and healthcare systems - are potentially avoidable [4,5]. National reviews have supported the need to improve the management of paediatric healthcare in the UK, stating that the care provided for children and young people with asthma was insufficient [6].
A large, and growing, number of digital technologies have been developed to help support the care and self-management of people with asthma [7–9]. Previous systematic reviews have found that digital interventions can help support asthma health management, particularly by improving medication adherence [10,11]. However, other reviews have identified mixed results in terms of effectiveness (depending on the outcome examined) [9] and app quality [8]. Reviews have also identified limitations in the literature such as inadequate descriptions of the digital interventions, a lack of economic analyses, and small sample sizes [10,12].
To be effective, patients need to be willing to use these digital interventions. While digital interventions have been shown to be generally acceptable to the wider population [11], special consideration is needed when evaluating digital interventions for children and young people. Adolescents are a particularly challenging group to treat, as they are at risk of not attending appointments and falling through a gap if there is not an adequate transition from paediatric to adult healthcare services [2]. Poor health literacy and self-management skills also affect adolescents’ adherence and health outcomes [2]. Attitudes towards electronic monitoring devices were found to be mixed in adolescents, depending on how they perceived the intervention. Among those who viewed asthma as a serious threat, the monitoring device was viewed as reassuring. However, many adolescents were suspicious of the device, reporting concerns that it would get them in trouble if they didn’t not adhere properly to their medication and beliefs that their healthcare providers did not trust them to take the medication [13]. This demonstrates the need to examine digital interventions tailored specifically at children and young people, as their needs and responses to the interventions may not be the same as the general population.
Rationale
There are several systematic reviews that examined various topics related to digital interventions for asthma management. However, none of the reviews provide a comprehensive and current overview of the field. Some of these reviews examine a general population, including both children and adults [9,11,12], while those reviews that limit the scope to children and young people focus on particular technologies or outcomes [10,14,15]. Additionally, no reviews were found that examined how the technologies are integrated into current clinical care pathways for children and adolescents with asthma.
A comprehensive review of systematic reviews was conducted that captured a large number of outcomes, including cost effectiveness [12]. However, this review was published in 2014, and given the rapid evolution of digital technology [16], the state of the field has changed since the review was conducted; for instance, electronic inhaler monitoring is a relatively new development [17,18], with smart inhalers only recently becoming commercially available [19]. Unni et al.’s review [9] did analyse studies of children and adults separately, but only 16 studies concerning children were included. The review does include a wide range of outcomes - adherence, health outcomes, and user perceptions - but only PubMed and EMBASE databases were searched for the study, which raises the concern that some relevant studies might have been missed [9].
Other systematic reviews have focused specifically on children and young people. However, they limited the scope either with respect to outcome (e.g. a focus on treatment adherence [14]) or type of digital technology (e.g. only mobile apps [10] or smart devices [15]). Several searches of keywords (“asthma” and “child” OR “paediatric” OR “pediatric” and “digital OR technology OR mHealth OR eHealth”) on PROSPERO only identified one relevant registration, which was planned, but not executed, by academics associated with the current research team [20].
Beyond supporting patients’ self-management of their asthma, digital technologies can bridge an information gap that affects the quality of asthma care. By collecting data about symptoms, medication adherence, and other relevant factors, digital technologies can provide healthcare professionals with a large body of information that enables them to personalise asthma care plans and focus on preventative measures [21]. A small study of American physicians found that, while they recognized the potential benefits of integrating digital technologies in asthma care for adolescents, they also noted a number of barriers and concerns [22]. However, more research is needed to understand how digital interventions are currently integrating with healthcare services [21].
Given the extent and variety of the literature on technological interventions to support asthma care in children and young people, there is a need for a scoping review to provide an overview of the state of the literature and to identify knowledge gaps [23]. An overview of the different types of digital technologies and the different ways they are being integrated with healthcare systems will help to inform the development of effective, technologically-enhanced care pathways for children with asthma.
Objectives and Research Questions
The primary objectives of the scoping review were to assess and summarize the current state of the literature on digital technology-supported asthma care for young people and to identify any gaps. Three research questions were developed to focus the review:
- How is research on technologically-supported asthma pathways being designed and conducted?
- What is known about their effectiveness of digital technologies to support treatment adherence and remote symptom monitoring in children and adolescents?
- What is the state of knowledge about integrating technology into clinical care pathways for paediatric asthma?
Methods
The review was structured following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR; Appendix A) [24] and the search strategy was developed using the Population, Intervention, Comparator, Outcome, and Studies (PICOS) framework (see Table 1). A preliminary review of the literature was used to extract MeSH terms and keywords for the search. The search was performed in five databases using the University of Plymouth’s search tool Primo - PubMed, the Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, EMBASE, and PsycINFO - with slightly adjusted search terms to fit the specific structure of each database (see Appendix B). The search terms were grouped into four themes - asthma, asthma management, children, and digital technology - that were joined with the structure: asthma (MeSH OR Keywords) AND asthma management (MeSH OR Keywords) AND children (MeSH OR Keywords) AND digital technology (MeSH OR Keywords). A complete record of the specific search terms and strings used for each database and the number of references returned is provided in Appendix B. The database searches were completed on 30 December 2020, except for the CENTRAL database, which was searched on 31 December 2020.
Inclusion criteria
The review included studies that evaluate digital technologies that aim to support the monitoring or treatment adherence of children and adolescents with asthma. Digital technologies included, but were not limited to, mobile or web applications, smart devices, and other phone or internet-based interventions. Initially, randomised controlled trials (RCTs), quantitative, qualitative, cohort, and case study types were eligible for inclusion. Given the number of studies identified, only RCTs were included in the review.
Exclusion criteria
Studies of patients over the age of 18 were excluded, there were three exceptions that reached full-text review and had both child and adult participants that were included in the review. Studies that were published before 2014 were excluded because, due to the rapid evolution of digital technology [16], earlier studies do not necessarily reflect the current state of the field. Studies that merely describe an intervention without evaluating it were excluded. Studies that are published in languages other than English were also excluded, as the review team did not have the necessary resources to assess them.
Screening and Article Selection
References were exported to the citation management software EndNote X9 for storage and duplicate removal. Due to the large number of references returned, an initial screening was conducted by inputting keywords relating to the inclusion and exclusion criteria into the EndNote X9 search function. This was done in several stages, due to the limitation of the number of search criteria that could be specified at once (see Appendix C for details). Searches of keywords to exclude were based on common features of irrelevant studies that were identified in a manual search. The remaining titles and abstracts were screened by the reviewer (with articles excluded with reasons), and final eligibility was determined by full-text reviews of the remaining references.
Data Extraction
Outcomes were extracted by the reviewer from a full-text review of all of the included articles into a table structured according to the three research questions (see Appendix D). Key outcomes were pre-determined based on a preliminary review of the literature; however, because of the expected variety of reported outcomes, relevant outcomes that were not pre-specified in the PICOS or data extractions tables were also considered for inclusion in the final review.
Data Analysis and Synthesis
The data extracted from the studies about the key outcomes listed in Table 2 were assessed using a descriptive analysis and summarised to provide an overview of the state of the literature. For the outcomes relating to effectiveness, the number of studies that found strong evidence of effectiveness was compared to the number of studies that assessed that outcome to provide a synthesis of the state of the evidence for that outcome. Implications of the findings were examined in the discussion.
Results
Included Studies
6,314 articles were retrieved from the search of the five databases (see Appendix B). 1,029 duplicates were removed by the EndNote X9 software, and a further 5,193 were screened out using keyword searches in EndNote (see Appendix C). The titles and abstracts of 92 studies were screened and articles were excluded with reasons. Of these articles, 25 were selected for the full-text review, and 20 were selected for inclusion in the review. Six of the references referred to one study and were either conference abstracts or did not include the final results of the randomised controlled trial. The paper with published results of the RCT of that study was identified and included [25]. The reasons for exclusion in the full-text review stage are detailed in Figure 1.
Study Characteristics
All of the studies included in the review were randomised controlled trials (RCTs), and were limited to those that included monitoring or adherence functions and aims. Despite these restrictions to the scope of the review, the included studies had a wide variety of study durations, sample sizes, age ranges, and types of digital intervention. Over a third of the references identified as eligible during title and abstract screening only had abstracts available (7/20) [26– 32]. They were included in the analysis, using whatever data was provided; two of the abstracts only presented interim results [26,27]. Four studies were analysed by nine separate articles and abstracts: the ADolescent Adherence Patient Tool (ADAPT) study [25,33,34], a study comparing web-ACT and FENO monitoring with standard care [35,36], a study of inhaler electronic monitoring devices (EMDs) with audiovisual reminders [37,38], and a study of a real-time medication monitoring (RTMM) device with SMS reminders [28,39].
There was a wide range in study durations, from 3 weeks [40] to 24 months [41], with the most common length of follow-up being 6 or 12 months (n=4 [25,31,33,34,37,38,42] and n=3 studies [27,28,35,36,39] for each). There was also a large variety of numbers of participants included in the 15 studies, ranging from 22 [30] to almost 1200 [41], with an average of approximately 230 participants and a median of 209 [28,39].
There were no distinctive categories of ages that emerged from the studies. Of the 15 distinct studies, only two used the same age range (4-11 years old [28,39,43]). Three studies included adult participants as well as child or adolescent participants [26,29,42]. The youngest participants included in a study were 3 years old [41]. Of the studies that focused on participants under 18, the span of ages eligible for inclusion in each study ranged from 6 years (ages 12-17 [40]) to 15 years (ages 4-18 [35,36]).
4 studies took place across multiple centres [26,28,32,35,36,39], and most of the rest were associated with large medical centres [40–43] or clinics [27,31]. The remaining 5 studies recruited from or were associated with a hospital emergency department [37,38], community pharmacies [25,33,34], Howard University [29], and impoverished, rural school districts [44]. One study did not specify the healthcare setting of the study [30].
Types of Digital Interventions
Several different types of digital interventions for monitoring and/or improving medication adherence were examined in the studies included in this review. The most common type of intervention, evaluated by a third of the studies (5/15), was EMDs. However, these EMDs all varied on their features, which included: audiovisual reminders [37,38], text messages [28,39], alarms [27], and app or online sources that could be synced to provide personal feedback [26,27], educational content [26], reminders [31], and capture adherence data [31].
Apps were another common intervention evaluated; three studies specifically evaluated 3 different app-based interventions. These included the ADolescent Adherence Patient Tool (ADAPT) app that connects adolescents to their community pharmacist through a desktop application and enables them to monitor symptoms and adherence, chat with peers and their pharmacist, watch short educational movies, and set medication alarms [25,33,34]. Another app, CHANGE Asthma, was developed for children by five pediatricians and modified based on feedback from a pilot of 24 caregivers. It uses short videos and games and an asthma action plan to improve asthma knowledge and control [43]. The third app evaluated (AsthmaWin) also included an asthma action plan, but focused more on monitoring symptoms and medication adherence [29].
Other types of interventions evaluated included web-based monitoring programs [35,36] (one of which was a component of a Virtual Asthma Clinic [32]), a speech recognition automated telephone program to improve medication adherence [41], text message medication reminders [42], a website and text-based reminder system (MyMediHealth) [40], a remote directly observed therapy (R-DOT) tool to improve inhaler use and adherence [30], and a school-based educational telemedicine intervention that provided interactive video sessions for children, caregivers, and school nurses [44].
Evidence of Effectiveness
A number of different outcome measures were used by the studies to evaluate the interventions, but results about effectiveness were inconsistent. Outcome with the highest proportion of studies finding a significant, positive effect was for improving medication adherence. The reported effectiveness of interventions and improving asthma control and health outcomes was very mixed. Patient feedback regarding acceptability and usability was generally high.
Treatment or Medication Adherence
9 studies evaluated the effectiveness of their intervention at improving treatment or medication adherence. Two thirds (6/9) reported significantly higher adherence in the intervention group compared to the control group [25,28,31,37,39–41]. Of the remaining three studies, two reported higher adherence in the intervention group compared to the control group, but no analysis of significance was provided [27,44]. The final study, which evaluated a SMS reminder system, found a decline in adherence over the intervention and control periods in both groups [42].
3 of the 6 studies that found a significant difference in adherence between groups evaluated EMDs [28,31,37,39]. The others evaluated the speech recognition automated telephone program [41], the website and text-based reminder system (MyMediHealth) [40], and the ADAPT app [25].
Only one study each evaluated the effectiveness of improving inhaler use and symptom monitoring, both of which found improvements. Shields et al. found that R-DOT improved inhaler technique equally in immediate and delayed intervention groups [30]. Perry et al. found significantly higher self-reports of peak flow meter use in the intervention group compared to the control group [44].
Asthma Control and Healthcare Visits
There were very mixed results in the nine studies that evaluated asthma control as an outcome. Four of the nine studies found either no effect of the intervention on asthma control [25,26,39] or no significant difference between groups [43]. However, Real et al. did find an significant positive association between degree of app use and asthma control [43].
Another four studies reported improved asthma control in the intervention group compared to the control group [27,29,30,32], although only one of these studies demonstrated statistical significance [32]. The final study found that asthma control could be maintained after a clinically relevant reduction in inhaled corticosteroids in the web-based monitoring condition [35,36].
Only two studies evaluated the effect of the intervention on healthcare visits, but neither found any differences [32,41].
Health and Quality of Life Outcomes
The overall effect of digital interventions on health outcomes is also unclear. Four of the seven studies that evaluated health outcomes (such as quality of life or symptom free days) found no significant improvement [25,28,35,36,39,44]. However, the other three studies reported significant improvements in self-reported quality of life [40], asthma morbidity scores [37], and number of symptom free days [32].
Patient Perceptions, Acceptability, and Usability
Cost-effectiveness
Only one study (two articles) explicitly assessed cost-effectiveness [28,39]. The authors found that costs were higher in the intervention group, and although this difference was not statistically significant [39], the technology was deemed not cost-effective because it was not associated with significant improvements in health outcomes [28].
Integration with clinical care pathways
Most of the studies included in the review (9/15, or 11 of the 20 articles) did not explicitly discuss how the digital intervention they were evaluating was integrated with clinical care pathways [27–31,37–40,42,43]. There were few studies that described sending data from the interventions back to physicians to update the patients’ health records or inform care, although this potential would likely be feasible for many of them. For the few that did, integration of the intervention with the healthcare system was generally reported positively.
Even among those that did describe a specific link between the intervention and the healthcare system, the specific details about integration were not a primary focus of the paper. For instance, some of the studies that monitored symptoms or adherence produced treatment advice based on data analysis from the system algorithms [35,36], sent physicians warnings if a patient was out of a certain threshold [26]. The Virtual Asthma Clinic, which also sent feedback to physicians if a patient’s asthma control scores were low, was found to be successful at increasing asthma control and symptom-free days and was proposed by the authors as a partial replacement for outpatient visits [32]. Details of how these systems were integrated with the healthcare system were not described.
One study whose intervention was significantly integrated with the healthcare system was the ADAPT app study [25,33,34]. One of the aims of the intervention was to increase collaboration and communication between adolescents and pharmacists because of the increasing role of pharmacists as healthcare providers in the Netherlands [25]. Pharmacists involved in the intervention reported valuing the improved contact with patients and found the intervention satisfactory, useful in fulfilling their role, and not time-consuming [34]. This was in contrast to the perceptions of pharmacists who did not participate in the intervention, who identified time constraints as a barrier to the use of mHealth [34]. However, a barrier was identified because the ADAPT app’s ‘stand-alone’ desktop interface for pharmacists was not integrated with the pharmacy’s general information system [34]. This study highlights the potential value of deliberate and considered efforts to integrate new digital health technologies for asthma management with existing health systems.
The speech recognition telemedicine intervention was another study that demonstrated integration with the healthcare system: the telemedicine system was integrated with the hospital’s electronic health record (EHR; EpicCare) to provide personalised calls to patients and is compatible with all standard EHR systems [41].
The attempt of one study [44] to involve primary care providers in the intervention was not successful. Treatment prompts with medication recommendations based on caregiver reports and guidelines were provided to the participants’ primary care providers. These were found to be ineffective; of the 141 prompts sent out for individual participants, the request for feedback received a response from only one primary care provider [44].
Discussion
Summary of Findings
There was a lot of variety in the studies examined in this review; study duration ranged from 3 weeks to 2 years, the number of participants ranged from 22 of 1187, and - although the review was focused on children and adolescents - there was a wide range of ages studied, with no distinct age groups emerging from the studies. There were also several different types of digital interventions analysed in the RCTs, with electronic monitoring devices and mobile apps the most common. However, the integration of these technologies with existing clinical care pathways and health systems was not extensively discussed in the majority of studies.
The review found inconsistent evidence for the effectiveness of the digital technologies at achieving their various aims. The most support was found for the effectiveness of the interventions at improving treatment or medication adherence (6/9 studies found evidence of effectiveness). The results of studies assessing the impact of the intervention on asthma control and health outcomes were mixed, with some studies reporting positive effects and others no significant effect. Across the studies, evaluations of patient perceptions, acceptability, and usability were generally positive.
Limitations
One limitation of this review is that the screening, article selection, and data analysis were only conducted by one researcher. Although the PRISMA-ScR framework was used to ensure the review performed and reported the necessary components of a scoping review, the lack of validation from another, independent reviewer means that there is a greater potential for bias to have been introduced in the selection or analysis of the studies.
Given time constraints when conducting the analysis, the data was extracted according to research questions (see Appendix D), with data for specific outcomes being identified from that table. In addition, a risk of bias assessment was not performed on the studies. While this is not a standard requirement for scoping reviews, it is a limitation of the study, as it would have contributed to the assessment of the first research question by providing an analysis of the quality of the research being conducted on technologically-supported asthma pathways.
Another limitation is that the research questions and aims were adjusted after the search had been performed. They were changed before any screening or selection took place, but may have resulted in relevant articles being missed because the search terms were established for a slightly different scope. Because of time limitations, no hand searches of the references of reviews retrieved in the initial search were performed, which also could have resulted in eligible articles being overlooked.
Meaning and Future Research
The large number of studies identified in the initial search and the variety of technological interventions to support paediatric asthma care demonstrate the broad scope of this research area. This review identified few strong trends with regards to how technologically-supported asthma pathways for children and young people are being researched. A theoretical framework for determining what ages to study or how to stratify children and young people into age groups might be useful for future research by enabling meta-analyses to be conducted. Currently, there is no consensus in the literature on how to group children of various ages for research.
This review found that there are a wide variety of different digital interventions being explored. However, strong evidence of their effectiveness at achieving various aims is still lacking. Notably, there was almost no consideration of the cost-effectiveness of the intervention in the studies examined. This will be a key area for future evaluations of these technologies to consider, so that limited healthcare resources can be deployed to create the greatest value [45].
Another key area for future research will be around the integration of these digital solutions into clinical pathways. As with cost-effectiveness, this review found that the majority of studies did not explicitly consider or evaluate how the technology they were examining would interact with existing health systems. The potential benefit of integrating patient-reported data with patients’ health records to inform care plans and pathways is likely feasible for many of the technologies assessed but was not examined as a key outcome of the technology. Acceptability and usability data likewise focused primarily on patient users. Understanding how these technologies can best support and interact with existing clinical pathways could help to inform their design, improvement, and sustainable adoption.
Conclusion
The purpose of this scoping review was to examine and summarise the state of the literature on technologically-enhanced asthma care pathways for children and young people. A large body of research is ongoing in this area and spans a wide range of technologies and ages. Although there was some evidence found for their effectiveness - particularly for improving treatment and medication adherence - further research is needed to establish the effectiveness of the interventions at improving asthma control and other health outcomes. There was little research that described or assessed the integration of these technologies with existing clinical care pathways or the cost-effectiveness of the interventions. These are key areas for future research to examine so that the value for patients and healthcare systems of the variety of digital technologies currently being developed can be comprehensively evaluated and compared.
Data Availability
This is a review of secondary literature and all data is accessible via public databases.
Funding
This research was supported by the Centre for Health Technology at the University of Plymouth.
Appendix Group
Appendices
PRISMA-ScR Checklist
Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist