Digital interventions to improve adherence to maintenance medication in asthma

Abstract

Asthma is a common, chronic respiratory disease, usually characterised by chronic airway inflammation, affecting 1%–18% of the population.1 Inhaled Corticosteroids (ICS) are the recommended preventer medication for symptom control and reduction of exacerbations.2, 3 Poor compliance with maintenance treatment is noted in approximately 50% of patients1 and is a major contributor to uncontrolled asthma.3 A range of digital interventions to improve adherence and self-management have been developed.4 This Cochrane Review aims to determine if digital technologies lead to improved asthma maintenance-treatment adherence (ICS) and eventually improving asthma symptoms and other benefits.5 This is an abstract of the Cochrane review ‘Digital interventions to improve adherence to maintenance medication in asthma’, published in the Cochrane Database of Systematic Reviews 2022, Issue 6, Art. No.: CD013030. DOI: 10.1002/14651858.CD013030.pub2 (see www.cochranelibrary.com for information). Cochrane reviews are regularly updated as new evidence emerges and in response to feedback, and the Cochrane Library should be consulted for the most recent version of the review. Asthma is the most common chronic lung condition worldwide, affecting 334 million adults and children globally. Despite the availability of effective treatment, such as inhaled corticosteroids (ICS), adherence to maintenance medication remains suboptimal. Poor ICS adherence leads to increased asthma symptoms, exacerbations, hospitalisations, and healthcare utilisation. Importantly, suboptimal use of asthma medication is a key contributor to asthma deaths. The impact of digital interventions on adherence and asthma outcomes is unknown. To determine the effectiveness of digital interventions for improving adherence to maintenance treatments in asthma. We identified trials from the Cochrane Airways Trials Register, which contains studies identified through multiple electronic searches and handsearches of other sources. We also searched trial registries and reference lists of primary studies. We conducted the most recent searches on 1 June 2020, with no restrictions on language of publication. A further search was run in October 2021, but studies were not fully incorporated. We included randomised controlled trials (RCTs) including cluster- and quasi-randomised trials of any duration in any setting, comparing a digital adherence intervention with a non-digital adherence intervention or usual care. We included adults and children with a clinical diagnosis of asthma, receiving maintenance treatment. We used standard methodological procedures for data collection. We used GRADE to assess quantitative outcomes where data were available. We included 40 parallel randomised controlled trials (RCTs) involving adults and children with asthma (n = 15,207), of which eight are ongoing studies. Of the included studies, 30 contributed data to at least one meta-analysis. The total number of participants ranged from 18 to 8517 (median 339). Intervention length ranged from two to 104 weeks. Most studies (n = 29) reported adherence to maintenance medication as their primary outcome; other outcomes such as asthma control and quality of life were also commonly reported. Studies had low or unclear risk of selection bias but high risk of performance and detection biases due to inability to blind the participants, personnel, or outcome assessors. A quarter of the studies had high risk of attrition bias and selective outcome reporting. We examined the effect of digital interventions using meta-analysis for the following outcomes: adherence (16 studies); asthma control (16 studies); asthma exacerbations (six studies); unscheduled healthcare utilisation (four studies); lung function (seven studies); and quality of life (10 studies). Pooled results showed that patients receiving digital interventions may have increased adherence (mean difference of 14.66 percentage points, 95% confidence interval (CI) 7.74–21.57; low-certainty evidence); this is likely to be clinically significant in those with poor baseline medication adherence. Subgroup analysis by type of intervention was significant (p = .001), with better adherence shown with electronic monitoring devices (EMDs) (23 percentage points over control, 95% CI 10.84–34.16; seven studies), and with short message services (SMS) (12 percentage points over control, 95% CI 6.22–18.03; four studies). No significant subgroup differences were seen for interventions having an in-person component versus fully digital interventions, adherence feedback, one or multiple digital components to the intervention, or participant age. Digital interventions were likely to improve asthma control (standardised mean difference (SMD) 0.31 higher, 95% CI 0.17–0.44; moderate-certainty evidence) – a small but likely clinically significant effect. They may reduce asthma exacerbations (risk ratio 0.53, 95% CI 0.32–0.91; low-certainty evidence). Digital interventions may result in a slight change in unscheduled healthcare utilisation, although some studies reported no or a worsened effect. School or work absence data could not be included for meta-analysis due to the heterogeneity in reporting and the low number of studies. They may result in little or no difference in lung function (forced expiratory volume in one second (FEV1): there was an improvement of 3.58% predicted FEV1, 95% CI 1.00%–6.17%; moderate-certainty evidence); however, this is unlikely to be clinically significant as the FEV1 change is below 12%. Digital interventions likely increase quality of life (SMD 0.26 higher, 95% CI 0.07–0.45; moderate-certainty evidence); however, this is a small effect that may not be clinically significant. Acceptability data showed positive attitudes towards digital interventions. There were no data on cost-effectiveness or adverse events. Our confidence in the evidence was reduced by risk of bias and inconsistency. Overall, digital interventions may result in a large increase in adherence (low-certainty evidence). There is moderate-certainty evidence that digital adherence interventions likely improve asthma control to a degree that is clinically significant, and likely increase quality of life, but there is little or no improvement in lung function. The review found low-certainty evidence that digital interventions may reduce asthma exacerbations. Subgroup analyses show that EMDs may improve adherence by 23% and SMS interventions by 12%, and interventions with an in-person element and adherence feedback may have greater benefits for asthma control and adherence, respectively. Future studies should include percentage adherence as a routine outcome measure to enable comparison between studies and meta-analysis, and use validated questionnaires to assess adherence and outcomes. Overall, the findings of this Review suggest that digital interventions can be effective in improving the primary outcomes: maintenance medication adherence, asthma control, and exacerbations. Efficacy for the secondary outcomes (unscheduled health utilisation, time off school, lung function, quality of life) was either not shown or of limited clinical relevance. Digital tools may support treatment adherence; however, there are limitations. For example, Electronic Monitoring devices (EMDs) can be used with inhalation devices and pill bottles to record doses dispensed,5 but they cannot ensure correct inhalation technique or actual medication-taking.3, 6 Several Novel EMDs, for example Hailie-Smart-Inhaler, are in development to assess both inhalation and actuation.7 With regard to the different electronic interventions, the reported outcomes were not consistent across studies, likely due to variation in study populations and the range of interventions evaluated (Table 1). EMDs were found to be the most effective digital intervention for improving adherence, followed by SMS messages (Figure 1). The website-based interventions had no significant effect on adherence but interestingly noted to be the most effective in improving asthma control as assessed by standardised patient questionnaires, followed by SMS messages.5 A broad range of digital interventions have been considered here, and this sub-group analysis is important when deciding what to recommend in clinic. This subgroup found to have the largest improvement in adherence compared to control The NHS spends approximately £1 billion a year on asthma, with 90% of this attributed to asthma medications.7 Evaluating the cost-effectiveness of digital interventions was a planned outcome of this Review, but the included studies did not comment on this. A cost-effectiveness analysis based on improvements in asthma exacerbations could be considered. Cost-effectiveness analysis is pertinent as prescribing EMDs over standard inhaler devices will add to prescribing costs, both in the increased cost of individual medication units and via the intended effect of increased medication usage by the patient. The NICE Medtech Innovation Briefing (MIB) on SmartInhaler (published in 2017), reports a cost of 100£ per unit (exclusive of VAT), plus £14.17 per month for each healthcare professional logging into the cloud-based data.6 SMS-based interventions are more affordable, assuming subjects own a mobile phone with a reminder function. The increased cost of digital interventions should prompt consideration about which patients warrant them. It may be reasonable to reserve these for patients who have troublesome symptoms despite standard therapy, along with evidence of poor adherence. In patients with reasonable adherence it is important to re-evaluate the diagnosis, as asthma is often incorrectly diagnosed.8 In these cases changing treatment approach will be more beneficial than escalating asthma therapy. Most of the studies included in the Review were conducted in high-income countries. Barriers faced by racial/ethnic minority groups or those of low socioeconomic status and poor health literacy3 need to be considered, and future research on applying these interventions considering Health Equity is needed. There is some suggestion in the review that interventions with an in-person component (i.e. a healthcare professional or a trained peer involved in the intervention either at the point of introduction of the digital intervention or on an ongoing basis),5 had a greater effect on adherence than digital interventions alone, suggesting support offered by healthcare services can potentially potentiate the effect of the intervention. The analysis also suggests that providing adherence feedback to the subjects increases the effect on asthma symptom control. This review supports the potential of digital interventions in improving asthma management. However, to make such interventions successful in real life, further data around cost-effectiveness would be useful, along with a more patient specific approach, considering the pre-existing barriers to medication adherence, the level of familiarity with technology and the acceptability of the proposed intervention. Dr Konstantina Papadopoulou wrote the first draft of this commentary. Both authors were involved in the planning, and in the subsequent editing and revision of this article. The authors would like to thank Dr Robert Boyle for his guidance in preparing the manuscript. The authors have no conflicts of interest to declare.

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