Digital technologies to help people with asthma take their medication as prescribed

Background to the question

Asthma is one of the most common long-term conditions worldwide. There are effective medicines available to treat symptoms, such as inhalers containing steroids. However, for best effect, maintenance medication need to be taken as prescribed. Many people do not take their medication, due to busy schedules and the belief that medication is only needed short-term. This is known as 'non-adherence', which can lead to more symptoms and attacks. Non-adherence is a major health problem; achieving adherence is very important to prevent attacks and reduce the risk of death. In healthcare there is increasing use of digital interventions such as mobile phones, text messages, and 'smart' inhalers that can feed back information about medication-taking. However, there is limited evidence on whether these technologies work to improve asthma medication-taking or improve symptoms.

This review aimed to find out whether digital technologies really work to improve asthma medication-taking, and whether this improved adherence leads to improvements in asthma symptoms and other benefits.

Study characteristics

We found 40 studies including more than 15,000 adults and children with asthma. Studies ranged from about 2 weeks to 24 months' duration, so we cannot say whether these methods are effective in the long term (a long period of years). We searched multiple information sources to identify relevant studies. This review is current as of June 2020. Looking at the data, we aimed to find out whether digital technologies helped people with asthma to take their medication as prescribed, and whether people who used the technology had better asthma control, and fewer asthma attacks, than those who did not use the technology.

Key results

People with asthma who were given the digital technology to support asthma medication-taking were better at taking their medication as prescribed compared to people who did not get the technology; 15% more people (likely to be somewhere between 8% and 22%) took their medication as prescribed when they received the digital technology, compared to those who did not (who took their medication on average 45% of the amount prescribed). Importantly, people who got the digital technology had much better asthma control and half the risk of asthma attacks (likely somewhere between 32% and 91%), which has direct benefits for reducing the risk of asthma-related deaths. We saw improvements in quality of life and lung function, but the effect on lung function was small and may be of limited clinical relevance. No improvements were seen in unscheduled healthcare visits. There was not enough information to tell us about the effect of digital technologies on time off work or school or the cost-benefits, nor whether there are any harms. Technologies were generally acceptable to patients. Certain types of technologies such as 'smart' inhalers and text messages seemed to be better for improving medication-taking than other technology types, although the small number of studies means we cannot be certain that these technologies definitely work better than others.

Quality of the information

There is some uncertainty about our results because the studies were quite different from each other. These differences mean that we cannot be completely sure what the real benefit is, as the benefits may be due to other factors not directly related to the technology - for example, being involved in a study can improve medication-taking. Sometimes the studies did not give us enough information for us to include them with the other studies to work out their effectiveness. We had concerns about a quarter of the studies where people did not finish the study, and we were uncertain whether studies reported everything they measured.

Key message

The studies we found suggest that digital technologies may help people with asthma take their medication better, improve their asthma control, and potentially halve their risk of asthma attacks, compared with people who did not get the technology. Certain types of digital technologies, such as text-message interventions, may work better than others. However, we have some uncertainties about the quality of the information reported in some studies, and the small number of studies for the different technology types, which means we cannot be 100% certain of their benefits.

Authors' conclusions: 

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.

Read the full abstract...

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.

Search strategy: 

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.

Selection criteria: 

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.

Data collection and analysis: 

We used standard methodological procedures for data collection. We used GRADE to assess quantitative outcomes where data were available.

Main results: 

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 to 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 = 0.001), with better adherence shown with electronic monitoring devices (EMDs) (23 percentage points over control, 95% CI 10.84 to 34.16; seven studies), and with short message services (SMS) (12 percentage points over control, 95% CI 6.22 to 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 to 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 to 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% to 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 to 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.