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Impact of eHealth on medication adherence among patients with asthma: A systematic review and meta-analysis

Open ArchivePublished:February 14, 2019DOI:https://doi.org/10.1016/j.rmed.2019.02.011

      Highlights

      • eHealth is effective in promoting adherence to inhaled corticosteroids.
      • Telehealth and mHealth are acceptable to patients.
      • Timing of text messages should be adjusted to suit target population.

      Abstract

      Background

      Asthma is an important public health issue in the United States. eHealth technology offers a potential solution to asthma treatment adherence, but the relative effect of various types of eHealth interventions has not been systematically studied.

      Objectives

      To systematically review the effectiveness of eHealth in improving adherence to inhaled corticosteroids (ICS) among patients with persistent asthma, as well as the satisfaction of patients undergoing eHealth interventions.

      Methods

      Literature searches were conducted in five databases in August 2018. Included studies were randomized controlled trials comparing eHealth interventions versus usual care in improving adherence among patients prescribed ICS for persistent asthma. Quantitative synthesis was performed using a random effects model.

      Results

      Eighty records were identified after removal of duplicates. Fifteen trials were eligible for qualitative synthesis. Included trials utilized: social media (n = 1), electronic health records (n = 1), telehealth (n = 6), and mHealth (n = 7). Twelve trials were eligible for quantitative synthesis. Results show a small but significant overall effect of eHealth interventions on adherence to ICS (Standardized Mean Difference (SMD) = 0.41, 95%CI = 0.02–0.79). Among the different types of eHealth interventions, a significant improvement in adherence was observed for mHealth interventions compared to usual care in a pooled analysis of 4 trials (SMD = 0.96, 95%CI = 0.28–1.64). However, there was considerable heterogeneity among studies. Patient satisfaction was evaluated in 5 trials comparing telehealth (n = 2) and mHealth (n = 3) with usual care. Participants found the interventions to be helpful and satisfactory.

      Conclusion

      eHealth interventions, especially mHealth interventions, are effective and acceptable in improving patient adherence to ICS.

      Keywords

      1. Introduction

      Asthma is a significant public health issue in the United States. As of 2016, asthma was prevalent in almost 8% of the entire population, with over 46% having experienced at least one asthma exacerbation within the past year [
      • Centers for Disease Control and Prevention
      CDC - Asthma - Table 4-1 Current Asthma Prevalence Percents by Age.
      ]. In fact, although asthma-related mortality has decreased since the 1990's, the prevalence of asthma has continued to increase since 1980 [
      • Healthy People 2020
      Respiratory Diseases.
      ]. The high prevalence of asthma alone leads to a significant burden on the healthcare system, with over $80 billion in annual healthcare expenditures [
      • Nurmagambetov T.
      • Kuwahara R.
      • Garbe P.
      The economic burden of asthma in the United States, 2008–2013.
      ], 1.6 million asthma-related emergency department visits in 2013, and 10.5 million visits to primary care providers in 2012 [
      • Centers for Disease Control and Prevention
      CDC - Asthma - Most Recent Asthma Data.
      ]. The social impact of this disease is significant as well, often leading to missed school and work days [
      • Healthy People 2020
      Respiratory Diseases.
      ]. This burden is greater among certain populations who are disproportionately affected by asthma, including children, women, African Americans, and those with lower household income [
      • Healthy People 2020
      Respiratory Diseases.
      ]. Methods to decrease the financial and social burdens of asthma, including improving adherence to asthma medications, thus become vitally important.
      Treatment adherence is generally low among patients with asthma [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ]. In fact, some studies show that adherence is less than 50% in children [
      • Milgrom H.
      • Bender B.
      • Ackerson L.
      • Bowry P.
      • Smith B.
      • Rand C.
      Noncompliance and treatment failure in children with asthma.
      ] and as low as 30% in adults [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ,
      • Bateman E.D.
      • Hurd S.S.
      • Barnes P.J.
      • Bousquet J.
      • Drazen J.M.
      • FitzGerald M.
      • Gibson P.
      • Ohta K.
      • O'Byrne P.
      • Pedersen S.E.
      • Pizzichini E.
      • Sullivan S.D.
      • Wenzel S.E.
      • Zar H.J.
      Global strategy for asthma management and prevention: GINA executive summary.
      ,
      • Bender B.G.
      • Bender S.E.
      Patient-identified barriers to asthma treatment adherence: responses to interviews, focus groups, and questionnaires.
      ,
      • Rand C.S.
      • Wise R.A.
      Measuring adherence to asthma medication regimens.
      ]. This low adherence may be due in part to misinformation or confusion regarding complicated treatment regimens [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ,
      • Chan P.W.
      • DeBruyne J.A.
      Parental concern towards the use of inhaled therapy in children with chronic asthma.
      ]. Treatment for persistent asthma generally involves a short-acting inhaled bronchodilator (such as albuterol) to ameliorate symptoms during acute exacerbations, plus a daily maintenance medication including an inhaled corticosteroid (ICS) [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ]. The twice-daily dosing of many ICS treatments may pose a burden to some patients who struggle to remember to take their medications [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ,
      • Bender B.G.
      • Bender S.E.
      Patient-identified barriers to asthma treatment adherence: responses to interviews, focus groups, and questionnaires.
      ]. Additional barriers such as high prescription cost, taste of medication, and uncertainty about the safety of inhaled corticosteroids may contribute to poor adherence to inhaled asthma medications [
      • Bender B.G.
      • Bender S.E.
      Patient-identified barriers to asthma treatment adherence: responses to interviews, focus groups, and questionnaires.
      ,
      • Lycett H.
      • Wildman E.
      • Raebel E.M.
      • Sherlock J.P.
      • Kenny T.
      • Chan A.H.Y.
      Treatment perceptions in patients with asthma: synthesis of factors influencing adherence.
      ]. Poor medication adherence is concerning, since it is shown to increase risk of asthma exacerbations [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ], leading to higher mortality [
      • Harrison B.
      • Stephenson P.
      • Mohan G.
      • Nasser S.
      An ongoing confidential enquiry into asthma deaths in the eastern region of the UK, 2001-2003.
      ], greater financial burden for the patient and health system [
      • Bender B.G.
      • Rand C.
      Medication non-adherence and asthma treatment cost.
      ], as well as decreased quality of life [
      • Engelkes M.
      • Janssens H.M.
      • de Jongste J.C.
      • Sturkenboom M.C.
      • Verhamme K.M.
      Medication adherence and the risk of severe asthma exacerbations: a systematic review.
      ,
      • Cote I.
      • Farris K.
      • Feeny D.
      Is adherence to drug treatment correlated with health-related quality of life?.
      ]. Indeed, non-adherence costs the US approximately $300 billion in healthcare expenditures each year [
      • Bender B.G.
      • Rand C.
      Medication non-adherence and asthma treatment cost.
      ]. Thus, strategies to overcome barriers to inhaled asthma medication adherence are critical.
      New eHealth technologies offer potential solutions for improving adherence to inhaled asthma medications. The World Health Organization (WHO) broadly defines eHealth as the use of information and communication technologies (ICT) for health, including patient treatment, research, education of healthcare professionals, and public health monitoring [
      • Toney B.
      • Goff D.A.
      • Weber R.J.
      Social media as a leadership tool for pharmacists.
      ]. A variety of technological domains fall under this “eHealth” umbrella, most notably: 1) mHealth, exemplified by clinical interventions supported by mobile devices; 2) telehealth, which often entails the use of telephonic or electronic technology to facilitate long-distance healthcare or education; 3) social media, often incorporating an interactive web-based platform; and 4) use of electronic health records (EHRs) to inform patient care [
      • Toney B.
      • Goff D.A.
      • Weber R.J.
      Social media as a leadership tool for pharmacists.
      ,
      • Bender B.G.
      • Apter A.
      • Bogen D.K.
      • Dickinson P.
      • Fisher L.
      • Wamboldt F.S.
      • Westfall J.M.
      Test of an interactive voice response intervention to improve adherence to controller medications in adults with asthma.
      ,
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ,
      • Chatkin J.M.
      • Blanco D.C.
      • Scaglia N.
      • Wagner M.B.
      • Fritscher C.C.
      Impact of a low-cost and simple intervention in enhancing treatment adherence in a Brazilian asthma sample.
      ,
      • Young H.N.
      • Havican S.N.
      • Griesbach S.
      • Thorpe J.M.
      • Chewning B.A.
      • Sorkness C.A.
      Patient and phaRmacist telephonic encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study.
      ]. Studies show that eHealth interventions are cost-effective for patients and providers, and improve patient outcomes, medication use, access to care, and quality of life [
      • Elbert N.J.
      • van Os-Medendorp H.
      • van Renselaar W.
      • Ekeland A.G.
      • Hakkaart-van Roijen L.
      • Raat H.
      • Nijsten T.E.C.
      • Pasmans S.G.M.A.
      Effectiveness and cost-effectiveness of eHealth interventions in somatic diseases: a systematic review of systematic reviews and meta-analyses.
      ,
      • Jennett P.A.
      • Hall L.A.
      • Hailey D.
      • Ohinmaa A.
      • Anderson C.
      • Thomas R.
      • Young B.
      • Lorenzetti D.
      • Scott R.E.
      The socio-economic impact of telehealth: a systematic review.
      ,
      • Morrison D.
      • Wyke S.
      • Agur K.
      • Cameron E.J.
      • Docking R.I.
      • MacKenzie A.M.
      • McConnachie A.
      • Raghuvir V.
      • Thomson N.C.
      • Mair F.S.
      Digital asthma self-management interventions: a systematic review.
      ,
      • Eland-de Kok P.
      • van Os-Medendorp H.
      • Vergouwe-Meijer A.
      • Bruijnzeel-Koomen C.
      • Ros W.
      A systematic review of the effects of e-health on chronically ill patients.
      ,
      • Linn A.J.
      • Vervloet M.
      • van Dijk L.
      • Smit E.G.
      • Van Weert J.C.M.
      Effects of eHealth interventions on medication adherence: a systematic review of the literature.
      ,
      • Tran N.
      • Coffman J.M.
      • Sumino K.
      • Cabana M.D.
      Patient reminder systems and asthma medication adherence: a systematic review.
      ,
      • Miller L.
      • Schüz B.
      • Walters J.
      • Walters E.H.
      Mobile technology interventions for asthma self-management: systematic review and meta-analysis.
      ]. For example, one meta-analysis found that electronic reminders may increase patient adherence to ICS by as much as 19% [
      • Normansell R.
      • Kew K.M.
      • Stovold E.
      Interventions to improve adherence to inhaled steroids for asthma.
      ]. Additionally, interventions using interactive voice response (IVR) technology [
      • Bender B.G.
      • Apter A.
      • Bogen D.K.
      • Dickinson P.
      • Fisher L.
      • Wamboldt F.S.
      • Westfall J.M.
      Test of an interactive voice response intervention to improve adherence to controller medications in adults with asthma.
      ] and provider notifications via EHR [
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • Walsh M.
      • Enberg R.
      • Lanfear D.E.
      • Pladevall M.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
      ] showed 32% and 35.7% increases in patient adherence to ICS, respectively. However, with such a broad range of eHealth technologies available, it is unclear which type of intervention is most effective in promoting behavior change, specifically medication adherence. Existing reviews focus on subsets of eHealth interventions versus usual care [
      • Miller L.
      • Schuz B.
      • Walters J.
      • Walters E.H.
      Mobile technology interventions for asthma self-management: systematic review and meta-analysis.
      ,
      • Tran N.
      • Coffman J.M.
      • Sumino K.
      • Cabana M.D.
      Patient reminder systems and asthma medication adherence: a systematic review.
      ], while the effectiveness of eHealth in its entirety has not been systematically evaluated. Furthermore, little research exists exploring patient preferences for type of eHealth intervention. Limited evidence suggests that patients prefer “push” reminders and methods that provide personalized feedback [
      • Nijland N.
      • van Gemert-Pijnen J.E.W.C.
      • Kelders S.M.
      • Brandenburg B.J.
      • Seydel E.R.
      Factors influencing the use of a web-based application for supporting the self-care of patients with type 2 diabetes: a longitudinal study.
      ]. Additional information on the usefulness and acceptability of particular eHealth interventions is needed to aid the translation of ICT and eHealth technologies into clinical practice and potentially improve health outcomes for patients. Therefore, the purpose of this study was to: 1) assess the overall effectiveness of eHealth interventions on patient adherence to ICS; 2) assess and categorize the types of eHealth technology in use; and 3) evaluate the satisfaction of patients using eHealth tools.

      2. Materials and methods

      We conducted a systematic review and meta-analysis in order to characterize the types of eHealth interventions most commonly found in the literature, as well their relative effectiveness on patient adherence to inhaled corticosteroids. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) guideline was utilized [
      • Moher D.
      • Liberati A.
      • Tetzlaff J.
      • DG A.
      Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
      ].

      2.1 Data sources and search strategy

      Literature searches were conducted in PubMed, CINAHL, Academic Search Premier, PsycINFO, and the International Pharmaceutical Abstracts (IPA) databases from each database inception until August 28, 2018. Additional articles were identified by hand-searching the reference list of included studies and from clinicaltrials.gov. A comprehensive search strategy was developed with the guidance of a librarian specializing in pharmacy and medicine at the primary author's institution (Table 1). All study citations were exported to reference management software for identification of duplicates and screening according to the PRISMA guideline.
      Table 1Search strategy.
      No.ConceptStrategy
      1eHealth“telemedicine” [mesh] OR telemedicine [tiab] OR telemonitoring [tiab] OR mhealth [tiab] OR ehealth[tiab] OR “m health” [tiab] OR “mobile health” [tiab] OR smartphone[tiab] OR “smart phone” [tiab] OR “smartphone” [mesh] OR “Cell phones” [tiab] OR “Cell phones” [mesh] OR “phone based” [tiab] OR “mobile based” [tiab] OR “phone app” [tiab] OR “mobile app” [tiab] OR “smartphone app” [tiab] OR “Mobile Applications” [Mesh] OR “Mobile Applications"[tiab]
      2Medication Adherence“Medication adherence” [mesh] OR “Medication adherence” [tiab] OR (“Patient Compliance” [mesh] AND (Drugs OR medication)) OR “Drug Adherence” [tiab] OR “Drug Persistence” [tiab] OR “Medication Persistence” [tiab] OR “Medication nonadherence” [tiab] OR “Medication Noncompliance” [tiab]
      3Asthma(“Asthma"[Mesh]) OR “Asthma*"[tiab]
      41, 2 and 3

      2.2 Eligibility criteria

      Studies were eligible for inclusion if they utilized eHealth interventions such as smartphone applications, text messaging, pagers or web technologies to promote adherence to inhaled corticosteroids among patients with asthma. The World Health Organization (WHO) definition of eHealth, “The use of information and communication technology for health” was used in determining whether an intervention utilized eHealth or not [
      • World Health Organization
      eHealth.
      ]. Adherence was defined as the extent to which a person's medication taking behavior corresponds with agreed upon recommendations from a health care provider [
      • Sabaté E.
      Adherence to Long-Term Therapies: Evidence for Action.
      ]. Only randomized clinical trials (RCTs) were eligible for inclusion. Unpublished studies reported at clinicaltrials.gov were also eligible for inclusion to prevent publication bias. Studies were excluded if the content was not written in English or medication adherence was not the primary outcome.

      2.3 Study selection

      Two independent reviewers (RJ and LH) screened study titles, abstracts, and full text while applying pre-defined inclusion and exclusion criteria. Fig. 1 shows how potential studies were added or excluded from qualitative synthesis. Studies that reported mean adherence to ICS as well as the corresponding standard deviation for the treatment and control groups were included in the quantitative synthesis. RJ and LH reviewed all excluded items to determine whether they met the criteria for exclusion. Disagreements were resolved via discourse and consensus.
      Fig. 1
      Fig. 1Study Identification and Selection Process. Flow of information through the different stages of the systematic review and meta-analysis according to PRISMA guidelines.

      2.4 Data extraction

      A semi-structured form for data extraction was developed consisting of the following fields— authors, year of publication, setting, country, participant age range, sample size, experimental arm versus control arm, study duration, study intervention, medication adherence measurement, and results. For quantitative analysis, the mean adherence, standard deviation, and number of study participants were also extracted. Emails were sent to authors to obtain additional information such as mean adherence and standard deviations whenever needed.

      2.5 Quality assessment

      The risk of bias in each study was analyzed using the Cochrane collaborations’ risk of bias assessment tool [
      • Higgins J.P.T.
      • Altman D.G.
      • Gøtzsche P.C.
      • Jüni P.
      • Moher D.
      • Oxman A.D.
      • Savović J.
      • Schulz K.F.
      • Weeks L.
      • Sterne J.A.C.
      The Cochrane Collaboration's tool for assessing risk of bias in randomised trials.
      ]. All the included studies were assessed for risk of bias by two independent reviewers. A consensus meeting was then held to resolve discrepancies and to arrive at a final risk of bias assessment summary (Fig. 2). Based on consensus between the two reviewers, studies were rated as “unclear” for other potential sources of bias if self-report was utilized in measuring adherence. Allocation concealment was also rated as “unclear” if there were uncertainties regarding the use of opaque envelopes.
      Fig. 2
      Fig. 2Risk of Bias of Included Studies. “Other bias” included method of medication adherence measurement. (Print color). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

      2.6 Meta-analysis

      Meta-analyses were performed using the Review Manager Software 5.3 Copenhagen (The Nordic Cochrane Center, the Cochrane Collaboration, 2014) for a comparison of eHealth interventions versus usual care or control. Standardized mean difference (SMD) was chosen as the summary statistic because of the variation in adherence measures among the studies included in the quantitative synthesis. The SMD was computed by dividing the difference between the post-intervention mean adherence in the treatment and control groups by the pooled standard deviation [
      • Higgins J.P.T.
      • S G.
      The standardized mean difference: Cochrane Handbook for Systematic.
      ]. The post intervention mean adherence was used rather than change in adherence scores because the latter was not available in majority of the studies [
      • Cramer H.
      • Chung V.C.H.
      Meta-analysis in systematic reviews of complementary and integrative medicine trials.
      ]. A positive value of SMD indicates a more favorable outcome for the treatment group compared to the control. Standard errors were converted to standard deviation by multiplying with the square root of sample size in cases where the authors reported standard errors. In cases where neither standard deviation nor standard error was reported and the authors did not respond to email requests, values were imputed from similar studies as recommended by existing evidence [
      • Furukawa T.A.
      • Barbui C.
      • Cipriani A.
      • Brambilla P.
      • Watanabe N.
      Imputing missing standard deviations in meta-analyses can provide accurate results.
      ]. Due to anticipated heterogeneity based on variability in how adherence was measured, subgroup analyses were performed according to the method of adherence measurement. Separate meta-analyses were also performed for the different types of eHealth intervention, with sub-group analyses based on the type of adherence measurement. In cases of studies utilizing both objective measures and self-report to measure adherence, results from the objective measure were included in the meta-analysis. Sensitivity analyses to detect the effects of targeting physicians versus patients and of including a study conducted in a pediatric setting were performed. A random effects model was used to pull the results from eligible studies. Effect sizes were weighted using the inverse variance method, while heterogeneity was tested for and quantified using chi-square and I2-statistics, respectively.

      3. Results

      3.1 Study selection and characteristics

      A comprehensive search of the literature yielded 89 records after duplicates were removed. After screening titles and abstracts, 25 records were eligible for full text review. Of these, 15 published articles were eligible for inclusion in the qualitative synthesis (Table 2). The study selection process is outlined in Fig. 1. The included studies provided 15 e-health treatment vs. control comparisons, with a total of 13,907 participants. One study was conducted in Brazil, an upper middle-income country while the remaining 14 studies were conducted in developed countries including the US, UK, Denmark, New Zealand, and Taiwan. Sample size varied from 26 to 8,517, while participants’ ages ranged from 3 to 65 years. Overall, studies utilized four categories of eHealth interventions to promote adherence to ICS: 1) social media (n = 1); 2) electronic health records (n = 1); 3) mHealth (n = 6); and 3) telehealth (n = 7).
      Table 2Summary of study characteristics.
      Author (year)eHealth CategorySetting, CountryPopulationDurationTrial vs Control ArmMedication Adherence MeasurementResults
      Bender et al. (2010)
      Included in quantitative synthesis.
      , [
      • Bender B.G.
      • Apter A.
      • Bogen D.K.
      • Dickinson P.
      • Fisher L.
      • Wamboldt F.S.
      • Westfall J.M.
      Test of an interactive voice response intervention to improve adherence to controller medications in adults with asthma.
      ]
      TelehealthTertiary care center, USAAges: 18–65,

      Sample size: 50.
      10 weeksInteractive voice response (IVR) calls vs usual careElectronic monitoring (One of Metered-Dose Inhaler Log, Doser-Clinical Trials Version, or Diskus Adherence Monitor)IVR intervention improved adherence by 32%.

      IVR arm: 64.5%,

      Control arm: 49.1% (p = 0.003).
      Bender et al. (2015)
      Included in quantitative synthesis.
      [
      • Bender B.G.
      • Cvietusa P.J.
      • Goodrich G.K.
      • Lowe R.
      • Nuanes H.A.
      • Rand C.
      • Shetterly S.
      • Tacinas C.
      • Vollmer W.M.
      • Wagner N.
      • Wamboldt F.S.
      • Xu S.
      • Magid D.J.
      Pragmatic trial of health care technologies to improve adherence to pediatric asthma treatment: a randomized clinical trial.
      ]
      TelehealthMultiple settings including 18 primary care and 2 specialty care, USAAges: 3–12,

      Sample size: 1,187.
      24 monthsComputerized speech recognition (SR) vs usual carePharmacy refillSR intervention improved adherence by 25.4%.

      SR arm: 44.5%,

      Control arm: 35.5% (p < 0.001).
      Chan et al. (2015)
      Included in quantitative synthesis.
      [
      • Chan A.H.
      • Stewart A.W.
      • Harrison J.
      • Camargo Jr., C.A.
      • Black P.N.
      • Mitchell E.A.
      The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial.
      ]
      mHealthEmergency care, New ZealandAges: 6–15,

      Sample size: 220.
      6 monthsAudiovisual reminders (AVR) vs usual careElectronic monitoring (Smartinhaler Tracker; Nexus6)AVR intervention improved adherence.

      AVR arm: 84%,

      Control arm: 30%
      Chatkin et al. (2006)
      Included in quantitative synthesis.
      [
      • Chatkin J.M.
      • Blanco D.C.
      • Scaglia N.
      • Wagner M.B.
      • Fritscher C.C.
      Impact of a low-cost and simple intervention in enhancing treatment adherence in a Brazilian asthma sample.
      ]
      TelehealthMultiple settings, BrazilAges: 12 or older,

      Sample size: 271.
      3 monthsTelephone calls vs usual careElectronic monitoring (Diskus dose recordings)There was a significant difference between the adherence rate in the treatment group compared to the control (p < 0.001).
      Charles et al. (2007)
      Included in quantitative synthesis.
      [
      • Charles T.
      • Quinn D.
      • Weatherall M.
      • Aldington S.
      • Beasley R.
      • Holt S.
      An audiovisual reminder function improves adherence with inhaled corticosteroid therapy in asthma.
      ]
      mHealthClinical trial facility, New Zealand.Ages: 12–65,

      Sample size: 110.
      6 monthsAudiovisual reminders (AVR) vs usual careElectronic monitoring (Smartinhaler monitoring device)AVR intervention improved adherence by 18%.

      AVR arm: 88%,

      Control arm: 66% (p < 0.0001).
      Chen et al. (2010)
      Included in quantitative synthesis.
      [
      • Chen S.-Y.
      • Sheu S.
      • Chang C.-S.
      • Wang T.-H.
      • Huang M.-S.
      The effects of the self-efficacy method on adult asthmatic patient self-care behavior.
      ]
      TelehealthChest Clinic, TaiwanAges: 20 and older,

      Sample size: 60.
      10 monthsDVD plus self-efficacy booklet and support group vs usual careSelf-reportThere were significant improvements in adherence between the treatment and control groups (p = 0.008).
      Gustafson et al. (2012)
      Included in quantitative synthesis.
      [
      • Gustafson D.
      • Wise M.
      • Bhattacharya A.
      • Pulvermacher A.
      • Shanovich K.
      • Phillips B.
      • Lehman E.
      • Chinchilli V.
      • Hawkins R.
      • Kim J.S.
      The effects of combining Web-based eHealth with telephone nurse case management for pediatric asthma control: a randomized controlled trial.
      ]
      TelehealthAsthma clinics, USAAges 4–12,

      Sample size: 301.
      12 monthsPhone-based plus web-based health education (eHealth) vs usual carePharmacy refill, self-reportThere was no significant difference between treatment and control groups.
      Johnson et al. (2016)
      Included in quantitative synthesis.
      [
      • Johnson K.B.
      • Patterson B.L.
      • Ho Y.X.
      • Chen Q.X.
      • Mulvaney S.A.
      • et al.
      The feasibility of text reminders to improve medication adherence in adolescents with asthma.
      ]
      mHealthPediatric outpatient setting, USAAges: 12–17,

      Sample size: 89.
      3 weeksPersonal health application vs usual careSelf-reportThere were improvements in adherence between the treatment and control groups (p = 0.016).
      Kolmodin et al. (2016) [
      • Kolmodin MacDonell K.
      • Naar S.
      • Gibson-Scipio W.
      • Lam P.
      • Secord E.
      The Detroit young adult asthma project: pilot of a technology-based medication adherence intervention for African-American emerging adults.
      ]
      mHealthOutpatient setting, USAAges: 18–29,

      Sample size: 49.
      3 monthsA computerized intervention authoring software (CIAS) with motivational interviewing vs controlSelf-reportThere was no significant improvement in adherence between the treatment and control groups (p = 0.9).
      Koufopoulos et al. (2016)
      Included in quantitative synthesis.
      [
      • Koufopoulos J.T.
      • Conner M.T.
      • Gardner P.H.
      • Kellar I.
      A web-based and mobile health social support intervention to promote adherence to inhaled asthma medications: randomized controlled trial.
      ]
      Social MediaOutpatient care, UKAges: 18 and older,

      Sample size: 103
      9 weeksOnline community vs usual careSelf-reportThere was no significant improvement between the treatment and control groups (p = 0.92)
      Petrie et al. (2012)
      Included in quantitative synthesis.
      [
      • Petrie K.J.
      • Perry K.
      • Broadbent E.
      • Weinman J.
      A text message programme designed to modify patients' illness and treatment beliefs improves self-reported adherence to asthma preventer medication.
      ]
      mHealthOutpatient setting, New ZealandAges: 16–45,

      Sample size: 216.
      9 monthsText message group vs usual careSelf-reportThere was a significant improvement between the treatment (43.2%) and control groups (57.8%) at p = 0.003.
      Strandbygaard et al. (2010)
      Included in quantitative synthesis.
      [
      • Strandbygaard U.
      • Thomsen S.F.
      • Backer V.
      A daily SMS reminder increases adherence to asthma treatment: a three-month follow-up study.
      ]
      mHealthOutpatient setting, DenmarkAges: 18–45,

      Sample size: 26.
      12 weeksText message vs usual careElectronic monitoring (Diskus dose recordings)There was a significant improvement between the treatment (95%) and control groups (17.8%) at p = 0.019.
      Vollmer et al. (2011)
      Included in quantitative synthesis.
      [
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ]
      TelehealthHealth maintenance organization, USAAges: 18 and older,

      Sample size: 8,517.
      18 monthsInteractive voice recognition (IVR) vs usual carePharmacy refillThere was a significant improvement between treatment and control groups (change = 0.02).
      Williams et al. (2010)
      Included in quantitative synthesis.
      [
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • Walsh M.
      • Enberg R.
      • Lanfear D.E.
      • Pladevall M.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
      ]
      EHRPrimary care settings, USAAges: 5–56,

      Sample size: 2,698.
      12 monthsPatient medication adherence feedback vs no feedbackPharmacy refillThere was no significant improvement between the treatment (21.3%) and control group (23.3%) at p = 0.553.
      Young et al. (2012) [
      • Young H.N.
      • Havican S.N.
      • Griesbach S.
      • Thorpe J.M.
      • Chewning B.A.
      • Sorkness C.A.
      Patient and phaRmacist telephonic encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study.
      ]
      TelehealthOutpatient setting, USAAges: 19 and older,

      Sample size: 98
      3 monthsTelepharmacy vs usual careSelf-reportThere was no significant difference between intervention and control groups (p = 0.07).
      a Included in quantitative synthesis.
      Of the 15 studies included in the qualitative synthesis, 12 studies were quantitatively analyzed. Of the three excluded studies, one study did not report the mean adherence and standard deviation of the intervention and control groups post intervention [
      • Young H.N.
      • Havican S.N.
      • Griesbach S.
      • Thorpe J.M.
      • Chewning B.A.
      • Sorkness C.A.
      Patient and phaRmacist telephonic encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study.
      ]. Another reported only the difference in proportion of adherent individuals as a result of the intervention [
      • Chatkin J.M.
      • Blanco D.C.
      • Scaglia N.
      • Wagner M.B.
      • Fritscher C.C.
      Impact of a low-cost and simple intervention in enhancing treatment adherence in a Brazilian asthma sample.
      ]. The last excluded study utilized both a dichotomous measure of adherence (yes/no) and ecological momentary assessment requested only at baseline and at the endpoint [
      • Kolmodin MacDonell K.
      • Naar S.
      • Gibson-Scipio W.
      • Lam P.
      • Secord E.
      The Detroit young adult asthma project: pilot of a technology-based medication adherence intervention for African-American emerging adults.
      ]. Regarding studies included in the quantitative synthesis, adherence to ICS was measured via electronic monitoring in four of these studies [
      • Bender B.G.
      • Apter A.
      • Bogen D.K.
      • Dickinson P.
      • Fisher L.
      • Wamboldt F.S.
      • Westfall J.M.
      Test of an interactive voice response intervention to improve adherence to controller medications in adults with asthma.
      ,
      • Chan A.H.
      • Stewart A.W.
      • Harrison J.
      • Camargo Jr., C.A.
      • Black P.N.
      • Mitchell E.A.
      The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial.
      ,
      • Strandbygaard U.
      • Thomsen S.F.
      • Backer V.
      A daily SMS reminder increases adherence to asthma treatment: a three-month follow-up study.
      ,
      • Charles T.
      • Quinn D.
      • Weatherall M.
      • Aldington S.
      • Beasley R.
      • Holt S.
      An audiovisual reminder function improves adherence with inhaled corticosteroid therapy in asthma.
      ], pharmacy refill data in three studies [
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ,
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • Walsh M.
      • Enberg R.
      • Lanfear D.E.
      • Pladevall M.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
      ,
      • Bender B.G.
      • Cvietusa P.J.
      • Goodrich G.K.
      • Lowe R.
      • Nuanes H.A.
      • Rand C.
      • Shetterly S.
      • Tacinas C.
      • Vollmer W.M.
      • Wagner N.
      • Wamboldt F.S.
      • Xu S.
      • Magid D.J.
      Pragmatic trial of health care technologies to improve adherence to pediatric asthma treatment: a randomized clinical trial.
      ], and self-report in four studies [
      • Chen S.-Y.
      • Sheu S.
      • Chang C.-S.
      • Wang T.-H.
      • Huang M.-S.
      The effects of the self-efficacy method on adult asthmatic patient self-care behavior.
      ,
      • Johnson K.B.
      • Patterson B.L.
      • Ho Y.X.
      • Chen Q.X.
      • Mulvaney S.A.
      • et al.
      The feasibility of text reminders to improve medication adherence in adolescents with asthma.
      ,
      • Koufopoulos J.T.
      • Conner M.T.
      • Gardner P.H.
      • Kellar I.
      A web-based and mobile health social support intervention to promote adherence to inhaled asthma medications: randomized controlled trial.
      ,
      • Petrie K.J.
      • Perry K.
      • Broadbent E.
      • Weinman J.
      A text message programme designed to modify patients' illness and treatment beliefs improves self-reported adherence to asthma preventer medication.
      ]. One trial used both pharmacy refill data and self-report [
      • Gustafson D.
      • Wise M.
      • Bhattacharya A.
      • Pulvermacher A.
      • Shanovich K.
      • Phillips B.
      • Lehman E.
      • Chinchilli V.
      • Hawkins R.
      • Kim J.S.
      The effects of combining Web-based eHealth with telephone nurse case management for pediatric asthma control: a randomized controlled trial.
      ]. In terms of types of eHealth interventions, five studies included in the quantitative analysis utilized mHealth, five used telehealth, one used EHR technology, and one used social media. There was a high level of agreement of 75.5%, between authors evaluating the quality of included studies.

      3.2 Risk of bias

      A total of seven studies were judged to be at high risk of bias in at least one domain (Fig. 2). Reporting bias, attrition bias, and performance bias were low in more than half of the included studies (Fig. 3). However, it was largely unclear whether selection and detection bias may have impacted the results in more than half of the studies. This was due to insufficient information about allocation concealment and random sequence generation.
      Fig. 3
      Fig. 3Risk of Bias of Included Studies Presented as Percentages. “Other bias” included method of medication adherence measurement. (Print color). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

      3.3 Efficacy of eHealth interventions

      The following sections present the efficacy of eHealth interventions both qualitatively and quantitatively, where applicable. First the efficacy of eHealth interventions overall (an aggregate of all intervention types) compared to control is examined. Then, eHealth is broken down into 4 categories or types and the efficacy of mHealth, telehealth, EHR, and social media interventions are analyzed specifically.

      3.4 eHealth interventions overall

      The comparison of eHealth interventions (all categories) across all measures of adherence versus control yielded a small but significant effect (SMD = 0.41, 95%CI = 0.02–0.79) (Fig. 4). Heterogeneity between the studies was high (I2 = 98%) and the subgroup difference was significant (χ2 = 8.46, df = 2, p = 0.01). The result of the subgroup analysis (based on type of adherence measure) indicated that the overall effect of eHealth was significant in studies utilizing electronic monitoring (SMD = 1.19, 95%CI = 0.49–1.89) in adherence measurement but insignificant in those utilizing pharmacy refill data (SMD = −0.13, 95%CI = −0.70 – 0.44) and self-report (SMD = 0.25, 95%CI = −0.10 – 0.60). Despite having a significant improvement in adherence, heterogeneity was high in the group of studies utilizing electronic monitoring (χ2 = 23.65, df = 3, p < 0.001, I2 = 87%). We conducted a sensitivity analysis by removing a study which was conducted in a pediatric setting [
      • Chan A.H.
      • Stewart A.W.
      • Harrison J.
      • Camargo Jr., C.A.
      • Black P.N.
      • Mitchell E.A.
      The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial.
      ]. The studies became homogeneous (χ2 = 0.39, df = 2, p = 0.82, I2 = 0%), and the effect size decreased from SMD = 1.19 (95%CI = 0.49–1.89) to SMD = 0.91 (95%CI = 0.58–1.23).
      Fig. 4
      Fig. 4eHealth Interventions Overall. A forest plot of eHealth interventions versus control for adherence to ICS.*.
      *SMD between 0.3 and 0.5 is considered to be a clinically important difference.
      Another sensitivity analysis removing a study with an intervention targeted at physicians rather than patients (Williams 2010) impacted the overall effect of eHealth interventions and heterogeneity. The effect size increased from SMD = 0.41 (95%CI = 0.02–0.79) to SMD = 0.52 (95%CI = 0.22–0.83) while heterogeneity decreased (I2 = 98% to I2 = 95%). The pharmacy refill data subgroup in which this study was categorized was also impacted. Effect size of pharmacy refill interventions increased from SMD = −0.13 (95%CI = −0.70 – 0.44) to SMD = 0.13 (95%CI = −0.11 – 0.36) but remained statistically insignificant. Heterogeneity among studies decreased by 9% but still remained high (I2 = 90%).

      3.5 mHealth interventions

      3.5.1 Qualitative synthesis

      Studies categorized as using mHealth interventions were those administering clinical interventions that were supported by mobile devices such as mobile phones, patient monitoring devices, personal digital assistants, and other wireless devices as suggested by WHO's definition of mHealth [
      • Toney B.
      • Goff D.A.
      • Weber R.J.
      Social media as a leadership tool for pharmacists.
      ]. The six mHealth studies that were qualitatively evaluated in this review employed text messages, either primarily [
      • Strandbygaard U.
      • Thomsen S.F.
      • Backer V.
      A daily SMS reminder increases adherence to asthma treatment: a three-month follow-up study.
      ,
      • Petrie K.J.
      • Perry K.
      • Broadbent E.
      • Weinman J.
      A text message programme designed to modify patients' illness and treatment beliefs improves self-reported adherence to asthma preventer medication.
      ] or as an adjunct reminder [
      • Kolmodin MacDonell K.
      • Naar S.
      • Gibson-Scipio W.
      • Lam P.
      • Secord E.
      The Detroit young adult asthma project: pilot of a technology-based medication adherence intervention for African-American emerging adults.
      ,
      • Johnson K.B.
      • Patterson B.L.
      • Ho Y.X.
      • Chen Q.X.
      • Mulvaney S.A.
      • et al.
      The feasibility of text reminders to improve medication adherence in adolescents with asthma.
      ], and audiovisual reminders [
      • Chan A.H.
      • Stewart A.W.
      • Harrison J.
      • Camargo Jr., C.A.
      • Black P.N.
      • Mitchell E.A.
      The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial.
      ,
      • Charles T.
      • Quinn D.
      • Weatherall M.
      • Aldington S.
      • Beasley R.
      • Holt S.
      An audiovisual reminder function improves adherence with inhaled corticosteroid therapy in asthma.
      ]. Of the two studies primarily assessing the effect of text messages on adherence to ICS, one delivered tailored text messages based on individuals' illness and medication beliefs while the other delivered untailored messages. The frequencies of texting were daily versus three text messages per week, respectively. Among the studies utilizing text messages as an adjunct reminder, one employed a personal health application that enabled users to set up text message reminders while the other utilized motivational interviewing strategies via two computer sessions before following up with text message reminders. Three mHealth studies assessed adherence via electronic monitoring while the other three used self-report. In five of the six studies, adherence rates improved significantly post-intervention.

      3.5.2 Quantitative synthesis

      Five studies using mHealth interventions were included in the quantitative synthesis. The meta-analysis comparing mHealth interventions to control found a significant overall effect on adherence to ICS (SMD = 0.96, 95%CI = 0.28–1.64) across mHealth studies utilizing electronic monitoring and self-reports to measure adherence (Fig. 5). A test for subgroup differences indicated that the overall effect size was not associated with the method of adherence measurement (χ2 = 2.61, df = 1, p = 0.11). Indeed, subgroup analysis of mHealth studies found significant improvements in adherence both in the group of studies utilizing electronic monitoring (SMD = 1.28, 95%CI = 0.41–2.14) and those utilizing self-reports (SMD = 0.52, 95%CI = 0.23–0.82). No mHealth study utilized pharmacy refill data as a measure of adherence. The electronic monitoring sub-group was heterogenous (I2 = 90%), while the self-report sub-group appeared to be homogenous (I2 = 0%).
      Fig. 5
      Fig. 5mHealth Interventions. A forest plot of mHealth interventions versus control for adherence to ICS.*.
      *SMD between 0.3 and 0.5 is considered to be a clinically important difference.

      3.6 Telehealth interventions

      3.6.1 Qualitative synthesis

      Telehealth interventions were those utilizing technology to support long-distance clinical healthcare, patient and professional health education, public health, or health administration [
      • Toney B.
      • Goff D.A.
      • Weber R.J.
      Social media as a leadership tool for pharmacists.
      ]. Of the seven studies included in the qualitative analysis for this category, interactive voice response (IVR) calls were employed as refill reminders in two studies [
      • Bender B.G.
      • Apter A.
      • Bogen D.K.
      • Dickinson P.
      • Fisher L.
      • Wamboldt F.S.
      • Westfall J.M.
      Test of an interactive voice response intervention to improve adherence to controller medications in adults with asthma.
      ,
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ] while speech recognition was used for the same purpose in another study [
      • Bender B.G.
      • Cvietusa P.J.
      • Goodrich G.K.
      • Lowe R.
      • Nuanes H.A.
      • Rand C.
      • Shetterly S.
      • Tacinas C.
      • Vollmer W.M.
      • Wagner N.
      • Wamboldt F.S.
      • Xu S.
      • Magid D.J.
      Pragmatic trial of health care technologies to improve adherence to pediatric asthma treatment: a randomized clinical trial.
      ]. Two studies utilized telephone calls by health professionals as parts of their intervention – a trained nurse made bi-weekly telephone calls to provide asthma education with emphasis on treatment adherence in one study while monthly telephone consultations were made by trained pharmacists in another study [
      • Chatkin J.M.
      • Blanco D.C.
      • Scaglia N.
      • Wagner M.B.
      • Fritscher C.C.
      Impact of a low-cost and simple intervention in enhancing treatment adherence in a Brazilian asthma sample.
      ,
      • Young H.N.
      • Havican S.N.
      • Griesbach S.
      • Thorpe J.M.
      • Chewning B.A.
      • Sorkness C.A.
      Patient and phaRmacist telephonic encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study.
      ]. Furthermore, one study exposed participants in the treatment group to a multimedia intervention involving self-efficacy promotion followed by individual follow up via telephone calls [
      • Chen S.-Y.
      • Sheu S.
      • Chang C.-S.
      • Wang T.-H.
      • Huang M.-S.
      The effects of the self-efficacy method on adult asthmatic patient self-care behavior.
      ]. Gustafson et al. used an online interactive information program for caregivers combined with monthly case management phone calls by nurses [
      • Gustafson D.
      • Wise M.
      • Bhattacharya A.
      • Pulvermacher A.
      • Shanovich K.
      • Phillips B.
      • Lehman E.
      • Chinchilli V.
      • Hawkins R.
      • Kim J.S.
      The effects of combining Web-based eHealth with telephone nurse case management for pediatric asthma control: a randomized controlled trial.
      ]. Of the seven telehealth studies, two studies did not find any significant difference in the medication adherence level between the treatment and usual care groups post-intervention.

      3.6.2 Quantitative synthesis

      Five studies employing telehealth interventions were included in the quantitative synthesis. Three out of the five studies measured adherence to ICS using pharmacy refill data, one utilized self-report while one used electronic monitoring. A pooled analysis of these studies found a small and insignificant effect on adherence to ICS (SMD = 0.20, 95%CI = −0.02 – 0.43) when compared to control (Fig. 6).
      Fig. 6
      Fig. 6Telehealth Interventions. A forest plot of telehealth interventions versus control for ICS adherence.*.
      *SMD between 0.3 and 0.5 is considered to be a clinically important difference.

      3.7 EHR interventions

      One study was categorized as an EHR intervention based on the use of EHR technology to provide real-time, patient adherence information to physicians in the treatment group [
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • Walsh M.
      • Enberg R.
      • Lanfear D.E.
      • Pladevall M.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
      ]. The feedback was intended to enable discussions with patients by physicians during visits. There was no difference in adherence rate between the treatment and usual care groups. A separate meta-analysis was not conducted for the EHR intervention due to the availability of only one study eligible for inclusion in the review.

      3.8 Social media interventions

      One study was categorized as a social media intervention and employed web technology to create an interactive platform through which individuals could share or discuss user-generated content [
      • Koufopoulos J.T.
      • Conner M.T.
      • Gardner P.H.
      • Kellar I.
      A web-based and mobile health social support intervention to promote adherence to inhaled asthma medications: randomized controlled trial.
      ]. Joining this online community did not improve adherence to ICS. A separate meta-analysis could not be conducted as a result of having only one study in the social media category.

      3.9 Patient satisfaction

      Patient satisfaction was measured in only five of fifteen reviewed studies. Of those five studies, two utilized mHealth interventions. One of the mHealth studies assessed the effect of daily text reminders on adherence [
      • Strandbygaard U.
      • Thomsen S.F.
      • Backer V.
      A daily SMS reminder increases adherence to asthma treatment: a three-month follow-up study.
      ]. Participants were satisfied with the daily text reminders but found the timing (10am) unsuitable. In another mHealth study, real-time data on adherence and asthma symptoms was used in personalizing an intervention that included daily text message reminders [
      • Kolmodin MacDonell K.
      • Naar S.
      • Gibson-Scipio W.
      • Lam P.
      • Secord E.
      The Detroit young adult asthma project: pilot of a technology-based medication adherence intervention for African-American emerging adults.
      ]. Participants rated the program highly in overall satisfaction (mean rating = 3.6 out of 4 possible points, from 1 = poor to 4 = excellent) and helpfulness (3.7 out of 4 possible points).
      The remaining three studies assessed patients’ satisfaction with different kinds of telehealth interventions. In the study conducted by Young et al., 80% of the participants were satisfied with the program and did not have a desire to modify the telepharmacy intervention [
      • Young H.N.
      • Havican S.N.
      • Griesbach S.
      • Thorpe J.M.
      • Chewning B.A.
      • Sorkness C.A.
      Patient and phaRmacist telephonic encounters (PARTE) in an underserved rural patient population with asthma: results of a pilot study.
      ]. Of the 56% participants providing feedback on the interactive voice response (IVR) call intervention by Vollmer et al., half indicated that the program was helpful and should be continued while one-third believed that their asthma was better controlled as a result of the intervention [
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ]. Bender et al. compared IVR with usual care and more than 90% of participants found the intervention helpful [
      • Vollmer W.M.
      • Feldstein A.
      • Smith D.H.
      • Dubanoski J.P.
      • Waterbury A.
      • Schneider J.L.
      • Clark S.A.
      • Rand C.
      Use of health information technology to improve medication adherence.
      ]. In all, participants were satisfied with eHealth interventions.

      4. Discussion

      This study is the first to report the effect of various types of eHealth interventions on adherence to inhaled corticosteroids among patients. Our findings indicate that eHealth interventions in general are effective in improving adherence to ICS. A recent Cochrane review of electronic reminders, a type of eHealth-based intervention also found positive results in terms of improvement in adherence [
      • Normansell R.
      • Kew K.M.
      • Stovold E.
      Interventions to improve adherence to inhaled steroids for asthma.
      ]. Similarly, a previous systematic review on reminder systems, of which all were information technology-based, suggested that reminders are effective in improving adherence to inhaled corticosteroids [
      • Tran N.
      • Coffman J.M.
      • Sumino K.
      • Cabana M.D.
      Patient reminder systems and asthma medication adherence: a systematic review.
      ]. The moderate effect that was found for eHealth interventions in the current study is similar to the findings by a recent meta-analysis of mobile technology interventions for asthma self-management [
      • Miller L.
      • Schuz B.
      • Walters J.
      • Walters E.H.
      Mobile technology interventions for asthma self-management: systematic review and meta-analysis.
      ]. Furthermore, our findings showed that the approach employed in measuring adherence impacted the effect obtained by the intervention. For instance, studies utilizing electronic monitoring devices had an overall effect size of 1.19 while self-reports had an overall effect size of 0.25. Evidence suggests that a standardized mean difference, of 0.3–0.5 is a minimal clinically important difference [
      • Angst F.
      • Aeschlimann A.
      • Angst J.
      The minimal clinically important difference raised the significance of outcome effects above the statistical level, with methodological implications for future studies.
      ]. Interestingly, the overall effect obtained when electronic adherence monitoring was used was more than two-fold the overall effect obtained from pooling studies of all the different categories of adherence measures. The effect size in the eHealth self-report subgroup indicated a minor effect of the intervention but was not statistically significant. This may have been due to the different types of self-report measures employed by studies in this report, which ranged from established validated instruments like the simplified adherence medication questionnaire to single items in a questionnaire and phone calls. Unlike the electronic monitoring and self-report subgroups, the pooled estimate for the pharmacy refill data subgroup was in favor of control rather than eHealth interventions. A potential reason for this observation is the inclusion of an intervention aimed at the physician rather than the patients. A sensitivity analysis that involved removal of this study caused the overall point estimate of the pharmacy refill subgroup to lie in favor of the treatment group.
      Among the different types of eHealth interventions, our results indicate that mHealth interventions are effective in improving adherence to ICS compared to usual care. Contrary to findings by Miller et al., mHealth interventions exhibited a large overall effect on adherence [
      • Miller L.
      • Schuz B.
      • Walters J.
      • Walters E.H.
      Mobile technology interventions for asthma self-management: systematic review and meta-analysis.
      ]. In their study, mHealth interventions had a moderate positive effect on medication adherence compared to standard treatment. Looking at the different methods of adherence measurement, studies utilizing self-report had a moderate effect on adherence while those utilizing electronic monitoring obtained a large effect. A possible explanation for the difference in effect sizes is the fact that electronic monitoring is a more objective measure of adherence. Slight disparities in effect sizes based on method of adherence measurement is not new and have been previously reported by a meta-analysis investigating the effect of self-monitoring of blood pressure on adherence to anti-hypertensives [
      • Fletcher B.R.
      • Hartmann-Boyce J.
      • Hinton L.
      • McManus R.J.
      The effect of self-monitoring of blood pressure on medication adherence and lifestyle factors: a systematic review and meta-analysis.
      ]. Regarding studies using telehealth interventions, the effect size indicated a treatment effect compared to control, but was not statistically significant. However, our narrative review of telehealth interventions found five reports of significant effects of telehealth intervention over control. Furthermore, a previous meta-analysis on telemedicine delivered by pharmacists found significant effects on adherence [
      • Niznik J.D.
      • He H.
      • Kane-Gill S.L.
      Impact of clinical pharmacist services delivered via telemedicine in the outpatient or ambulatory care setting: a systematic review.
      ]. It is possible that the analysis in our study was not sufficiently powered to detect a significant effect of telehealth interventions, suggesting a need for more telehealth interventions to be conducted. Other subsets of eHealth such as EHR and social media had insufficient studies to be included in the meta-analysis.
      Heterogeneity among studies found in this review are likely due to population and methodological differences such as differences in age of the target population, method of adherence measurement, and other sociodemographic differences in intervention recipients. For example, a sensitivity analysis that involved removal of a study conducted in a pediatric setting [
      • Chan A.H.
      • Stewart A.W.
      • Harrison J.
      • Camargo Jr., C.A.
      • Black P.N.
      • Mitchell E.A.
      The effect of an electronic monitoring device with audiovisual reminder function on adherence to inhaled corticosteroids and school attendance in children with asthma: a randomised controlled trial.
      ] caused included mHealth studies to become more homogeneous (I2 = 0%). Similarly, removal of a study utilizing an intervention directed at physicians [
      • Williams L.K.
      • Peterson E.L.
      • Wells K.
      • Campbell J.
      • Wang M.
      • Chowdhry V.K.
      • Walsh M.
      • Enberg R.
      • Lanfear D.E.
      • Pladevall M.
      A cluster-randomized trial to provide clinicians inhaled corticosteroid adherence information for their patients with asthma.
      ] rather than patients reduced the heterogeneity among the pharmacy refill data subgroup in the analysis of eHealth versus control by 9%. Furthermore, variation of adherence measurement in this review may have contributed greatly to heterogeneity. For example, only one study utilizing self-report in adherence measurement used a validated instrument. Even at that, the validated tool was modified for the study. Also, others used un-validated items within a questionnaire or telephone calls to assess adherence.
      We found that few of the studies included in this review examined patient satisfaction and preference for particular types of eHealth interventions. Among included studies, participants found mHealth interventions such as text message reminders acceptable; however, timing may need to be modified to suit the population at hand. Additionally, telehealth interventions such as phone calls by trained health professionals and interactive voice response calls are also acceptable and helpful to users. There is need for more studies to evaluate user satisfaction with eHealth interventions targeted at improving adherence to ICS.
      This study is not without limitations. As discussed above, there was considerable heterogeneity among studies that were quantitatively synthesized. Also, the adherence measurement scales contributing to the standardized mean difference (SMD) calculations may have introduced variation that could not be fully addressed in the meta-analysis. There were less than three studies in some of the subgroups in the analyses involving mHealth and telehealth studies versus control. Furthermore, there were insufficient studies in certain eHealth categories, such as social media and EHR, limiting generalizability. Additionally, free computers were provided to participants in one study, and free medications in two other studies – this may have motivated participants, introducing an element of selection bias. Lastly, a total of seven studies were judged to be of high risk of bias in at least one domain. Future studies should employ either objective methods of adherence measurement or validated self-report instruments.

      5. Conclusion

      The evidence from this review suggests that eHealth-based interventions are effective in improving adherence to ICS. This is especially true for mHealth studies, including audiovisual and text message reminders. Patients perceive telephone consultations by health professionals, interactive voice response calls, and text message reminders as acceptable and helpful. However, the timing of messages may need to be modified to suit the population at hand. These findings can be translated into future practice-based interventions in order to optimally improve patient adherence to ICS and ultimately improve health outcomes for patients with persistent asthma.

      Declarations of interest

      None.

      Conflicts of interest

      The authors have no conflict of interest to disclose.

      Acknowledgements

      The authors would like to thank Ms. Adelia Grabowsky for her guidance in developing the literature search strategy.

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