BACKGROUND: 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.
OBJECTIVES: To determine the effectiveness of digital interventions for improving adherence to maintenance treatments in asthma.
SEARCH METHODS: 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.
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.
BACKGROUND: Mobile technology interventions (MTI) are becoming increasingly popular in the management of chronic health behaviors. Most MTI allow individuals to monitor medication use, record symptoms, or store and activate disease-management action plans. Therefore, MTI may have the potential to improve low adherence to medication and action plans for individuals with asthma, which is associated with poor clinical outcomes.
OBJECTIVE: A systematic review and meta-analysis were conducted to evaluate the efficacy of MTI on clinical outcomes as well as adherence in individuals with asthma. As the use of evidence-based behavior change techniques (BCT) has been shown to improve intervention effects, we also conducted exploratory analyses to determine the role of BCT and engagement with MTI as moderators of MTI efficacy.
METHODS: We searched electronic databases for randomized controlled trials up until June 2016. Random effect models were used to assess the effect of MTI on clinical outcomes as well as adherence to preventer medication or symptom monitoring. Mixed effects models assessed whether the features of the MTI (ie, use of BCT) and how often a person engaged with MTI moderated the effects of MTI.
RESULTS: The literature search located 11 studies meeting the inclusion criteria, with 9 providing satisfactory data for meta-analysis. Compared with standard treatment, MTI had moderate to large effect sizes (Hedges g) on medication adherence and clinical outcomes. MTI had no additional effects on adherence or clinical outcomes when compared with paper-based monitoring. No moderator effects were found, and the number of studies was small. A narrative review of the two studies, which are not included in the meta-analysis, found similar results.
CONCLUSIONS: This review indicated the efficacy of MTI for self-management in individuals with asthma and also indicated that MTI appears to be as efficacious as paper-based monitoring. This review also suggested a need for robust studies to examine the effects of BCT use and engagement on MTI efficacy to inform the evidence base for MTI in individuals with asthma.
IMPORTANCE: Adherence to long-term therapies in chronic disease is poor. Traditional interventions to improve adherence are complex and not widely effective. Mobile telephone text messaging may be a scalable means to support medication adherence.
OBJECTIVES: To conduct a meta-analysis of randomized clinical trials to assess the effect of mobile telephone text messaging on medication adherence in chronic disease.
DATA SOURCES: MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, PsycINFO, and CINAHL (from database inception to January 15, 2015), as well as reference lists of the articles identified. The data were analyzed in March 2015.
STUDY SELECTION: Randomized clinical trials evaluating a mobile telephone text message intervention to promote medication adherence in adults with chronic disease.
DATA EXTRACTION: Two authors independently extracted information on study characteristics, text message characteristics, and outcome measures as per the predefined protocol.
MAIN OUTCOMES AND MEASURES: Odds ratios and pooled data were calculated using random-effects models. Risk of bias and study quality were assessed as per Cochrane guidelines. Disagreement was resolved by consensus.
RESULTS: Sixteen randomized clinical trials were included, with 5 of 16 using personalization, 8 of 16 using 2-way communication, and 8 of 16 using a daily text message frequency. The median intervention duration was 12 weeks, and self-report was the most commonly used method to assess medication adherence. In the pooled analysis of 2742 patients (median age, 39 years and 50.3% [1380 of 2742] female), text messaging significantly improved medication adherence (odds ratio, 2.11; 95% CI, 1.52-2.93; P < .001). The effect was not sensitive to study characteristics (intervention duration or type of disease) or text message characteristics (personalization, 2-way communication, or daily text message frequency). In a sensitivity analysis, our findings remained robust to change in inclusion criteria based on study quality (odds ratio, 1.67; 95% CI, 1.21-2.29; P = .002). There was moderate heterogeneity (I2 = 62%) across clinical trials. After adjustment for publication bias, the point estimate was reduced but remained positive for an intervention effect (odds ratio, 1.68; 95% CI, 1.18-2.39).
CONCLUSIONS AND RELEVANCE: Mobile phone text messaging approximately doubles the odds of medication adherence. This increase translates into adherence rates improving from 50% (assuming this baseline rate in patients with chronic disease) to 67.8%, or an absolute increase of 17.8%. While promising, these results should be interpreted with caution given the short duration of trials and reliance on self-reported medication adherence measures. Future studies need to determine the features of text message interventions that improve success, as well as appropriate patient populations, sustained effects, and influences on clinical outcomes.
Context: Medication non-adherence is a commonly observed problem in the self-administration of treatment, regardless of the disease type. Text messaging reminders, as electronic reminders, provide an opportunity to improve medication adherence. In this study, we aimed to provide evidence addressing the question of whether text message reminders were effective in improving patients’ adherence to medication. Evidence Acquisition: We carried out a systematic literature search, using the five electronic bibliographic databases: PubMed, Embase, PsycINFO, CINAHL, and the Cochrane central register of controlled trials. Studies were included on the basis of whether they examined the benefits and effects of short-message service (SMS) interventions on medication adherence. Results: The results of this systematic review indicated that text messaging interventions have improved patients’ medication adherence rate (85%, 29.34). Included in the review, those who had problems with adherence, or those whom text messaging was most helpful had HIV, asthma, diabetes, schizophrenia and heart disease (73.5%). The period of intervention varied from 1 week to 14 months. The most common study design was randomized controlled trials (RCTs) (66%) carried out in the developed countries. Conclusions: This study demonstrated the potential of mobile phone text messaging for medication non-adherence problem solving.
BACKGROUND: Chronic diseases have emerged as a serious threat for health, as well as for global development. They endenger considerably increased health care costs and diminish the productivity of the adult population group and, therefore, create a burden on health, as well as on the global economy. As the management of chronic diseases involves long-term care, often lifelong patient adherence is the key for better health outcomes. We carried out a systematic literature review on the impact of mobile health interventions -mobile phone texts and/or voice messages- in high, middle and low income countries to ascertain the impact on patients' adherence to medical advice, as well as the impact on health outcomes in cases of chronic diseases.
METHODS: The review identified fourteen related studies following the defined inclusion and exclusion criteria, in PubMed, Cochrane Library, the Library of Congress, and Web Sciences. All the interventions were critically analysed according to the study design, sample size, duration, tools used, and the statistical methods used for analysing the primary data. Impacts of the different interventions on outcomes of interest were also analysed.
RESULTS: The findings showed evidence of improved adherence, as well as health outcomes in disease management, using mobile Short Message Systems and/or Voice Calls. Significant improvement has been found on adherence with taking medicine, following diet and physical activity advice, as well as improvement in clinical parameters like HbA1c, blood glucose, blood cholesterol and control of blood pressure and asthma.
CONCLUSIONS: Though studies showed positive impacts on adherence and health outcomes, three caveats should be considered, (i) there was no clear understanding of the processes through which interventions worked; (ii) none of the studies showed cost data for the m-health interventions and (iii) only short term impacts were captured, it remains unclear whether the effects are sustained. More research is needed in these three areas before drawing concrete conclusions and making suggestions to policy makers for further decision and implementation.
Abstract Background: The effectiveness of telemedicine for the management of chronic diseases is unclear. This study examined the effectiveness of telemedicine in relieving asthma symptoms. Materials and Methods: A systematic review of the Medline, Cochrane, EMBASE, and Google Scholar databases was conducted until December 31, 2013 using the following key words: "asthma," "telemedicine," "telehealth," "e-health," "mobile health," "Internet," "telecommunication," "telemanagement," "remote," and "short message service." Inclusion criteria were randomized controlled trial, a diagnosis of asthma, the majority of the patients were ≥18 years of age, and intervention involved any format of telemedicine. A meta-analysis of eligible studies was conducted with the primary outcome being change of asthma symptoms. Results: Of 813 articles identified, 11 were included in the qualitative synthesis, and 6 were included in the meta-analysis. Among the 11 studies, there were 1,460 patients in the intervention groups and 1,349 in the control groups, and the total numbers of participants ranged from 12 to 481 in the intervention groups and from 12 to 487 in the control groups. The mean age of patients ranged in the intervention groups from 34.4 to 54.6 years and in the control groups from 30.7 to 56.4 years. The treatment duration ranged from 0.5 to 12 months. The meta-analysis of six eligible studies revealed no significant difference in asthma symptom score change between the telemedicine and control groups (pooled Hedges's g=0.34, 95% confidence interval=-0.05 to 0.74, Z=1.69, p=0.090). Conclusions: Telemedicine interventions do not appear to improve asthma function scores, but other benefits may be present.
BACKGROUND: Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management.
OBJECTIVE: We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers.
METHODS: We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users.
RESULTS: In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%).
CONCLUSIONS: There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.
AIMS: Adherence to medication is a major problem that affects 50-60% of chronically ill patients. As mobile phone use spreads rapidly, a new model of remote health delivery via mobile phone - mHealth - is increasingly used. The objective of this study is to provide a comprehensive overview of how mHealth can be used to improve adherence to medication.
METHODS: A systematic literature review was conducted using four databases (CINAHL, PubMed, Scopus and PsycARTICLES). Eligible articles available on March 2014 had to be written in English or Spanish and have a comparative design. Articles were reviewed by two authors independently. A Cochrane Collaboration tool was used to assess the studies based on their internal validity.
RESULTS: Of the 1504 articles found, 20 fulfilled the inclusion criteria [13 randomised clinical trials (RCT), one quasi-RCT, one non-randomised parallel group study and five studies with a pre-post design]. Nearly all the trials were conducted in high-income countries (80.0%). Articles were categorised depending on the target population into three different groups: (i) HIV-infected patients, n = 5; (ii) patients with other chronic diseases (asthma, coronary heart disease, diabetes mellitus, hypertension, infectious diseases, transplant recipients and psoriasis), n = 11; and (iii) healthy individuals, n = 4. Adherence improved in four of the studies on HIV-infected patients, in eight of the studies on patients with other chronic diseases, and in 1 study performed in healthy individuals. All studies reported sending SMS as medication reminders, healthy lifestyle reminders, or both. Only one trial (HIV-infected patients) had a low risk of bias.
CONCLUSIONS: Our results showed mixed evidence regarding the benefits of interventions because of the variety of the study designs and the results found. Nevertheless, the interventions do seem to have been beneficial, as 65% of the studies had positive outcomes. Therefore, more high-quality studies should be conducted.
We conducted a meta-analysis of randomized controlled trials (RCTs) up to January 2014 which evaluated the effects of electronic reminders on patient adherence to medication in chronic disease care. A random-effects model was used to pool the outcome data. Subgroup analyses were performed to examine a set of moderators. Data from 20 studies, representing 22 RCTs, were synthesized. Thirteen trials utilized short message service (SMS) reminders, three used pager reminders and six employed electronic alarm device-triggered reminders. The meta-analysis showed that the use of electronic reminders was associated with a significant, yet small, improvement in patient adherence to medication (pooled Cohen’s d = 0.29, 95% confidence interval 0.18, 0.41). The effect was sensitive to sample size, type of disease and intervention duration. The frequency and type of electronic reminders appeared to have no moderating effect on medication adherence. The use of electronic reminders seems to be a simple and potentially effective way of improving patient adherence to chronic medication. Future research should concern the optimum strategies for the design and implementation of electronic reminders, with which the effectiveness of the reminders is likely to be augmented. (PsycINFO Database Record (c) 2016 APA, all rights reserved)
BACKGROUND: A growing body of research has employed mobile technologies and geographic information systems (GIS) for enhancing health care and health information systems, but there is yet a lack of studies of how these two types of systems are integrated together into the information infrastructure of an organization so as to provide a basis for data analysis and decision support. Integration of data and technical systems across the organization is necessary for efficient large-scale implementation.
OBJECTIVE: The aim of this paper is to identify how mobile technologies and GIS applications have been used, independently as well as in combination, for improving health care.
METHODS: The electronic databases PubMed, BioMed Central, Wiley Online Library, Scopus, Science Direct, and Web of Science were searched to retrieve English language articles published in international academic journals after 2005. Only articles addressing the use of mobile or GIS technologies and that met a prespecified keyword strategy were selected for review.
RESULTS: A total of 271 articles were selected, among which 220 concerned mobile technologies and 51 GIS. Most articles concern developed countries (198/271, 73.1%), and in particular the United States (81/271, 29.9%), United Kingdom (31/271, 11.4%), and Canada (14/271, 5.2%). Applications of mobile technologies can be categorized by six themes: treatment and disease management, data collection and disease surveillance, health support systems, health promotion and disease prevention, communication between patients and health care providers or among providers, and medical education. GIS applications can be categorized by four themes: disease surveillance, health support systems, health promotion and disease prevention, and communication to or between health care providers. Mobile applications typically focus on using text messaging (short message service, SMS) for communication between patients and health care providers, most prominently reminders and advice to patients. These applications generally have modest benefits and may be appropriate for implementation. Integration of health data using GIS technology also exhibit modest benefits such as improved understanding of the interplay of psychological, social, environmental, area-level, and sociodemographic influences on physical activity. The studies evaluated showed promising results in helping patients treating different illnesses and managing their condition effectively. However, most studies use small sample sizes and short intervention periods, which means limited clinical or statistical significance.
CONCLUSIONS: A vast majority of the papers report positive results, including retention rate, benefits for patients, and economic gains for the health care provider. However, implementation issues are little discussed, which means the reasons for the scarcity of large-scale implementations, which might be expected given the overwhelmingly positive results, are yet unclear. There is also little combination between GIS and mobile technologies. In order for health care processes to be effective they must integrate different kinds of existing technologies and data. Further research and development is necessary to provide integration and better understand implementation issues.
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.
OBJECTIVES:
To determine the effectiveness of digital interventions for improving adherence to maintenance treatments in asthma.
SEARCH METHODS:
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.
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.
