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Cardiovascular disease (CVD) remains the leading cause of death worldwide. Mobile phones have become ubiquitous in most developed societies. Smartphone apps, telemonitoring, and clinician-driven SMS allow for novel opportunities and methods in managing chronic CVD, such as ischemic heart disease, heart failure, and hypertension, and in the conduct and support of cardiac rehabilitation.
A systematic review was conducted using seven electronic databases, identifying all relevant randomized control trials (RCTs) featuring a mobile phone intervention (MPI) used in the management of chronic CVD. Outcomes assessed included mortality, hospitalizations, blood pressure (BP), and BMI.
Electronic data searches were performed using seven databases from January 2000 to June 2019. Relevant articles were reviewed and analyzed. Meta-analysis was performed using standard techniques. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used.
A total of 26 RCTs including 6713 patients were identified and are described in this review, and 12 RCTs were included in the meta-analysis. In patients with heart failure, MPIs were associated with a significantly lower rate of hospitalizations (244/792, 30.8% vs 287/803, 35.7%; n=1595; OR 0.77, 95% CI 0.62 to 0.97;
The available data suggest that MPIs may have a role as a valuable adjunct in the management of chronic CVD.
Cardiovascular disease (CVD) is the leading cause of death worldwide [
Traditional cardiac rehabilitation (CR) programs are the embodiment of these principles, offering support, tailored education, and supervised exercise [
The outpatient management of heart failure is ideally performed using a multidisciplinary approach, including nurse-led medication titration services, which reduce readmission rates and mortality. However, these services are heavily dependent upon the limited resources of skilled nursing staff. Again, a novel approach to outpatient management is required.
The telemedicine care process involves using communication networks to deliver health care services and move patient information between locations. Literature reviews have underlined several advantages of using telemedicine to reduce inequalities in cardiovascular outcomes [
Mobile phones (particularly smartphones) provide new opportunities to remotely care for patients with cardiac conditions. Traditionally, telemedicine required the provision of home-based specialized monitoring equipment to patients. Smartphones, mobile phones, and wearable technology, however, offer tremendous potential for monitoring health through phone calls, text messages, data recording, highly portable peripheral devices, and activity monitoring, which may find utility for novel models of health care delivery that are cost-effective, accessible, and patient-centric. Mobile phones are ubiquitous, and the recent landmark Nature publication [
The purpose of this study was to systematically review and meta-analyze the evidence for mobile phone technology in the management of cardiac conditions according to the following questions: (1) What are the specific interventions available and do they involve an interface whereby the clinician can use the data to intervene (henceforth referred to as a
Electronic data searches were performed using Ovid MEDLINE, PubMed, EMBASE, Database of Abstracts of Review of Effects, American College of Physicians Journal Club, National Health Service Economic Evaluation Database, and Cochrane Database of Systematic Reviews from January 2000 to June 2019. A combination of search terms were used to maximize sensitivity:
Studies were considered eligible for this systematic review if a mobile phone app or text messaging (used interchangeably henceforth with SMS) were used in a randomized control trial (RCT) in the management of ischemic heart disease, cardiac failure, or hypertension in adult patients. Studies limited to the management of obesity, dyslipidemia, diabetes, sedentary lifestyle, and smoking cessation in patients without CVD were not included. Studies examining a combined population such as patients with either dyslipidemia or hypertension were not included unless the groups were analyzed separately. Where telephone calls were the primary intervention, the study was excluded as such an intervention could occur using landline telephones. Similarly, web-based interventions were not included as they could occur using a computer or tablet. Studies that recruited less than 10 subjects in each arm were excluded. Qualitative studies or those with no clinical endpoints were not included. Non-English language results were not included. Abstracts, case reports, editorials, and conference presentations were excluded.
Article screening was performed by reviewing abstracts (by PI). Clinical outcome data were extracted from article text, tables, and figures independently by 2 researchers (PI and DT) from articles where it was available in the text, tables, figures, or supplementary material. Any discrepancies were resolved after the collaborative review. The final results were reviewed by all authors.
Meta-analysis was performed by combining event rates of dichotomous variables and using the supplied means and standard deviations for continuous variables. The odds ratio (OR) was used as a summary statistic for dichotomous variables. A random effect model was used. Chi-square tests were used to study heterogeneity between trials. The I2 statistic was used to estimate the percentage of total variation across studies due to heterogeneity rather than chance. An I2 value of greater than 50% was considered to represent substantial heterogeneity. Subgroup analyses were not possible due to the lack of patient-level data. All
Using the search strategy described earlier, 306 unique references were retrieved (465 before deduplication). The screening process is summarized in the PRISMA chart in
Of the 26 RCTs, the target population was ischemic heart disease in 6 studies [
The studies were performed in 17 different countries, including 9 studies from Europe, 6 from North America, 5 from Australia/New Zealand, 4 from Asia, and 1 each from Africa and South America. In total, 10 studies examined a 1-way SMS intervention, 3 examined an interactive SMS intervention—where participants could reply, 4 examined an automatic telemonitoring system in which metrics were transmitted to the research team without the need for manual entry, 6 examined a manual telemonitoring system, and 3 studies examined a smartphone app that did not fit the previous criteria. Moreover, 10 studies included a
Blinding of the participants was not possible in any of the 26 identified studies. This was expected given the nature of the interventions. Only 8 studies featured blinding of the researchers or outcome assessors, and only 7 studies were adjudicated as having a low risk of bias (
Search strategy and results for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method.
Characteristics of the studies included in the systematic review.
Reference | Country | Multicenter | Population | Number of patients (N) | Follow-up (weeks) | Intervention | Back-end |
Blasco 2012 [ |
Spain | No | IHDa-ACSb | 203 | 52 | Manual telemonitoring | Yes |
Chow 2015 [ |
Australia | No | IHD-ACS and stable CADc | 710 | 26 | One-way SMS | No |
Fang 2016 [ |
China | No | IHD-stable CAD | 271 | 26 | One-way SMS | No |
Khonsari 2015 [ |
Malaysia | No | IHD-ACS | 62 | 8 | One-way SMS | No |
Park 2015 [ |
United States | No | IHD-ACS, stable | 90 | 4.5 | Interactive SMS | No |
Quilici 2013 [ |
France | No | IHD-ACS | 499 | 4.5 | One-way SMS | No |
Chen 2019 [ |
China | No | HFd | 512 | 26 | One-way SMS | No |
Dendale 2012 [ |
Belgium | Yes | HF | 160 | 26 | Auto telemonitoring | Yes |
Koehler 2011 [ |
Germany | Yes | HF | 710 | 52 | Auto telemonitoring | Yes |
Scherr 2009 [ |
Austria | No | HF | 120 | 26 | Manual telemonitoring | Yes |
Seto 2012 [ |
Canada | No | HF | 100 | 26 | Auto telemonitoring | Yes |
Vuorinen 2014 [ |
Finland | No | HF | 94 | 26 | Manual telemonitoring | Yes |
Bobrow 2016 [ |
South Africa | No | HTNe | 1372 | 52 | Interactive SMS | No |
Kiselev 2012 [ |
Russia | No | HTN | 199 | 52 | One-way SMS | No |
Logan 2012 [ |
Canada | Yes | HTN | 110 | 52 | Auto telemonitoring | Yes |
Morawski 2018 [ |
United States | Yes | HTN | 411 | 12 | Manual telemonitoring | No |
Morikawa 2011 [ |
Japan | No | HTN | 41 | 4 | One-way SMS | No |
Varleta 2017 [ |
Chile | Yes | HTN | 314 | 26 | One-way SMS | No |
Bravo-Escobar 2017 [ |
Spain | No | CRf-ischemic CMg | 28 | 8 | App (other) | Yes |
Del Rosario 2018 [ |
Australia | No | CR (mixed) | 66 | 12 | Manual telemonitoring | No |
Maddison 2019 [ |
New Zealand | Yes | IHD-ACS | 162 | 24 | App (other) | Yes |
Pandey 2017 [ |
Canada | No | CR-ACS | 34 | 52 | One-way SMS | No |
Pandey 2017 [ |
Canada | No | CR-ACS | 50 | 52 | One-way SMS | No |
Pfaeffli Dale 2015 [ |
New Zealand | Yes | CR-ACS and stable CAD | 123 | 26 | Interactive SMS | No |
Piotrowicz 2010 [ |
Poland | No | CR (HF) | 152 | 8 | Manual telemonitoring | No |
Varnfield 2014 [ |
Australia | No | CR-ACS | 120 | 6 | App (other) | Yes |
aIHD: ischemic heart disease.
bACS: acute coronary syndrome.
cCAD: coronary artery disease.
dHF: heart failure.
eHTN: hypertension.
fCR: cardiac rehabilitation.
gCM: cardiomyopathy.
Endpoints examined in randomized trials of mobile phone technology in cardiovascular disease.
Author | Population | Primary endpoint | Primary result | Major secondary endpoints | ||||
|
|
|
|
Mortality | Hospitalization | Blood pressure | BMI | Medication adherence |
Blasco 2012 [ |
IHDa | Cardiovascular risk | NSb | NRc | NR | NS | NS | NR |
Chow 2015 [ |
IHD | Lipid profile | Pd | NR | NR | P | P | NR |
Fang 2016 [ |
IHD | Medication adherence | P | NR | NR | NR | NR | P1e |
Khonsari 2015 [ |
IHD | Medication adherence | P | NS | NS | NR | NR | P1 |
Park 2015 [ |
IHD | Medication adherence | P | NR | NR | NR | NR | P1 |
Quilici 2013 [ |
IHD | Medication adherence | P | NR | NR | NR | NR | P1 |
Chen 2019 [ |
HFf | Mortality | NS | NS1g | P | NR | NR | P |
Dendale 2012 [ |
HF | Mortality | P | P1 | NS | NR | NR | NR |
Koehler 2011 [ |
HF | Mortality | NS | NS1 | NS | NR | NR | NR |
Scherr 2009 [ |
HF | Mortality | NS | NS1 | NS | NR | NR | NR |
Seto 2012 [ |
HF | BNPh | NS | NR | NR | NR | NR | NR |
Vuorinen 2014 [ |
HF | Readmissions | NS | NS | NS1 | NR | NR | NR |
Bobrow 2016 [ |
HTNi | Blood pressure | P | NR | NS | P1 | NR | P |
Kiselev 2012 [ |
HTN | Blood pressure | P | NR | NR | P1 | NS | NR |
Logan 2012 [ |
HTN | Blood pressure | P | NR | NR | P1 | NR | NR |
Morawski 2018 [ |
HTN | Blood pressure | NS | NR | NR | NS1 | NR | P |
Morikawa 2011 [ |
HTN | Blood pressure | P | NR | NR | P1 | NS | NR |
Varleta 2017 [ |
HTN | Medication adherence | NS | NR | NR | NS | NR | NS1 |
Bravo-Escobar 2017 [ |
CRj | Physical fitness | NS | NR | NR | NS | NS | NR |
Del Rosario 2018 [ |
CR | CR completion rate | P | NR | NR | NS | NS | NR |
Maddison 2019 [ |
CR | Physical fitness | NS | NR | NR | NR | NR | NR |
Pandey 2017 [ |
CR | Medication adherence | NS | NR | NR | NR | NR | NS1 |
Pandey 2017 [ |
CR | Lifestyle adherence | NS | NR | NR | NR | NR | NR |
Pfaeffli Dale 2015 [ |
CR | Lifestyle adherence | NS | NR | NR | NS | NS | P |
Piotrowicz 2010 [ |
CR | Functional status | P | NR | NR | NR | NR | NR |
Varnfield 2014 [ |
CR | CR completion rate | NS | NR | NR | NS | P | NR |
aIHD: ischemic heart disease.
bNS: not significant.
cNR: not reported.
dP: positive.
eP1: positive primary endpoint.
fHF: heart failure.
gNS1: not significant primary endpoint.
hBNP: brain natriuretic peptide.
iHTN: hypertension.
jCR: cardiac rehabilitation.
A total of 6 interventions were identified that were targeted at patients with ischemic heart disease, excluding patients who were exclusively recruited from CR. The most commonly assessed primary endpoint was medication adherence, and the results are tabulated in
The largest and most comprehensive study was the pivotal Tobacco, Exercise and Diet Messages (TEXT ME) trial [
A Spanish RCT investigated a 2-way messaging service in patients who had experienced an acute coronary syndrome [
Fang et al [
A small study performed in Malaysia randomized 62 patients with a recent acute coronary syndrome to receive an SMS reminder before scheduled medication times or usual care only, for an 8-week period post discharge [
Park et al [
Quilici et al [
A total of 6 RCTs assessed the efficacy of telemedicine-based interventions in the management of heart failure; 5 out of the 6 studies demonstrated at least one clinical benefit for the intervention, although there was no endpoint that was shown to be consistently improved across all studies. One study demonstrated an improvement in mortality [
A recent large RCT from China randomized patients with chronic heart failure into 3 arms: structured telephone support (a single phone call within 30 days of discharge with the opportunity to speak to a nurse during work hours), an SMS-based support system, or a control group [
Dendale et al [
The study by Koehler et al [
The MOBIle TELemonitoring in Heart Failure Patients study compared the use of a manual monitoring system with standard care [
Seto et al [
Vuorinen et al [
In total, 6 RCTs examined smartphone apps in the management of patients previously diagnosed with hypertension; 4 of these demonstrated a statistically significant reduction in systolic BP. The results are summarized in
The SMS Text Adherence Support trial randomized 1372 patients to receive SMS information, interactive SMS, or usual care [
Kiselev et al [
A multicenter Canadian study of 110 diabetic patients examined the impact of an automatic telemonitoring system using a smartphone app and Bluetooth-enabled BP machine [
The Medication Adherence Improvement Support App For Engagement—Blood Pressure app used a web-based recruitment platform to randomize 411 patients with essential hypertension to receive either an automatic, Bluetooth-enabled sphygmomanometer or the companion Medisafe smartphone app [
Morikawa et al [
A multicenter study from Chile examined the effect of 1 SMS every 2 weeks on BP and medication adherence [
Eight randomized controlled trials studied the addition of mobile phone interventions (MPIs) to standard CR. All trials demonstrated at least one benefit in the intervention group, although specific positive results varied significantly between trials.
Del Rosario et al [
The Text4Heart trial, undertaken in New Zealand, examined the addition of a personalized 24-week program of educational and motivational text messages, delivered daily, to standard CR for patients with postmyocardial infarction [
Piotrowicz et al [
Varnfield et al [
Pandey et al [
Two studies focused on the use of a wearable ECG monitoring system using smartphone technology. An RCT from New Zealand compared home-based CR using a smartphone-based platform including an ECG monitoring vest and web-based education with center-based CR. This noninferiority trial demonstrated comparable average physical fitness (as measured by maximal oxygen consumption: VO2 max) between the 2 groups [
For the heart failure cohort, all 6 studies were included in the meta-analysis. There was no significant difference in mortality (measured at 6 months in all studies, with the exception of Koehler et al [
Readmissions due to heart failure over 6 months were less common in the intervention group than in the control group for the 3 studies that reported this endpoint (96/686, 14.0% vs 129/696, 18.5%; OR 0.69, 95% CI 0.48 to 0.98;
The rate of hospitalization for any reason over 6 months was significantly lower in the intervention group (244/792, 30.8% vs 287/803, 35.7%; OR 0.77, 95% CI 0.62 to 0.97;
The difference in systolic BP was analyzed from 5 studies that reported the endpoint at 6 or 12 months. The mean systolic BP was 4.3 mm Hg less in the intervention group than in the control group (95% CI −7.8 to −0.78 mm Hg;
Four studies reported the percentage of patients who reached the target BP, defined as 140/90 mm Hg in 3 studies [
There was no significant difference in the change in BMI between the 4 studies that reported the endpoint after 6 or more months (mean difference −0.46; 95% CI −1.44 to 0.52;
A meta-analysis of medication adherence could not be performed, as there was no uniform measurement for assessing the outcome.
Forest plot of the odds ratio (OR) of mortality in patients with heart failure who were involved in randomized controlled trials comparing a mobile phone intervention versus control. The estimate of the OR of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% CI. The summary OR is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics. MPI: mobile phone intervention, df: degrees of freedom.
Forest plot of the odds ratio (OR) of heart failure readmissions in patients with heart failure who were involved in randomized controlled trials comparing a mobile phone intervention versus control. The estimate of the OR of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% CI. The summary OR is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics. MPI: mobile phone intervention, df: degrees of freedom.
Forest plot of the odds ratio (OR) of all-cause readmissions in patients with heart failure who were involved in randomized controlled trials comparing a mobile phone intervention versus control. The estimate of the OR of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% CI. The summary OR is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics. MPI: mobile phone intervention, df: degrees of freedom.
Forest plot of the mean difference in blood pressure in patients with hypertension who were involved in randomized controlled trials comparing a mobile phone intervention versus control. The mean difference of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% CI. The summary mean difference is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics. MPI: mobile phone intervention, df: degrees of freedom.
Forest plot of the odds ratio (OR) in patients with hypertension who achieved the prespecified target blood pressure and who were involved in randomized controlled trials comparing a mobile phone intervention versus control. The estimate of the OR of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% CI. The summary OR is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics. MPI: mobile phone intervention, df: degrees of freedom.
This meta-analysis demonstrated that in patients with heart failure, the use of MPIs reduced the rate of hospital admission, both in relation to total admissions and heart failure admissions. There was no significant difference in mortality rates between the groups. In patients with hypertension, those who used MPIs had a significantly lower systolic BP and were more likely to reach the target BP. There was no significant difference in BMI.
Mobile phone and smartphone technology represent a significant opportunity for health care providers to improve outcomes for large populations of patients with CVD. Although no single holistic cardiac care app has been rigorously trialed, a multitude of small, targeted apps have been studied. In general, these heterogeneous and underpowered data do not allow for clear conclusions to be made on the overall benefit of MPIs; however, several important observations are made.
In patients with ischemic heart disease, MPIs universally improved medication compliance. It was not possible to perform meta-analysis of this endpoint due to the variation in reporting systems used between studies, but this is an important finding. Reasons for noncompliance are multiple; however, by providing physical reminders as well as motivational support, text messaging appears to be an effective method of reinforcing adherence, particularly in the context of asymptomatic disease. Given the relatively low cost and negligible risk of text messaging, it could be considered a mainstream management strategy for patients possessing a mobile phone. It remains to be seen, however, whether improved compliance leads to a clinically significant benefit, as cardiovascular event rates were generally not examined in these trials. The successful use of mobile phone technology to promote medication compliance has also been demonstrated in other fields of medicine [
In hypertensive patients, reductions in BP are also likely a reflection of improved compliance [
In the cardiac failure cohort, five studies used home monitoring of BP and weight. Although benefits were shown with regard to quality of life and functional status, only one study demonstrated a difference in mortality, and the results of the meta-analysis were negative. The negative result for mortality was driven largely by the study by Koehler et al [
From these data, it is clear that not all interventions are equal. Dendale et al [
The results for mobile phone technology as an adjunct to CR suggested potential improvements in medication adherence [
Other studies of telemonitoring in heart failure, using technologies other than mobile phones, have shown mixed results. Multiple meta-analyses have shown superior outcomes for telemonitoring in heart failure patients compared with standard care [
The cost-effectiveness of mobile phone technology for any of the aforementioned indications in CVD has not been conclusively studied. It is believed that a reduction of adverse clinical outcomes and an associated reduction in costs of hospitalization would likely offset costs of implementing the software and monitoring data, although there was a notable paucity of cost-effectiveness data. There remains only a single published cost-effectiveness analysis of an MPI based on randomized trial data [
Assuming that the mobile phone is not operated during driving or other dangerous tasks, there are no significant risks to the patient in any of the described interventions. There are several limitations of the available data contained within this systematic review and meta-analysis, and the results should be interpreted with caution. Although all studies were RCTs, they were generally small, with varying methodologies, and prone to bias. No follow-up period was longer than 26 months; thus, data on recurrent clinical events in the medium to long term were lacking. In addition, patient compliance with the mobile phone technology itself over longer periods is unknown. The utility of such interventions in the older population is uncertain, given that advanced age is one of the most significant risk factors for all forms of CVD. One study demonstrated a high rate of dropout due to inability of patients to operate the app (22%) [
Several gaps remain in this literature. There is significant potential of this technology to gather data that can be reviewed in real-time and subsequently allow for rapid modifications in patient therapy in response, although this was only examined in a small number of trials. When patients are reviewed routinely by a clinician in the community, the clinician only sees a
The majority of smartphone apps examined here had a single aim or function, and the management of CVD entails the optimization of multiple factors. Therefore, there remains a need for an adequately powered RCT examining the effect of a holistic smartphone intervention with multiple features that possess the ability to react to collected data and improve therapy and therefore clinical endpoints, and there is a need to identify which patients would benefit the most.
MPIs have been applied to a variety of target groups in CVD. These fall into several categories including SMS apps, automatic and manual monitoring, and purpose-built apps. A number of RCTs have been published. The results suggest that mobile phone technology may improve medication adherence in patients with ischemic heart disease, BP in individuals with hypertension, and hospitalization rates in patients with heart failure. Further large RCTs with longer follow-up periods and a greater focus on clinical endpoints are required. However, given the relatively low risk and cost of such interventions, they should be considered as an adjunctive therapy in the management of patients with CVD or at risk of CVD.
Study interventions and target populations.
Other secondary endpoints of included studies.
Bias assessment according to the Cochrane Risk of Bias Tool.
Summary of mobile phone interventions for medication adherence in patients with ischaemic heart disease.
Mobile phone interventions for treatment of heart failure.
Mobile phone interventions for treatment of hypertension.
Forest plot of the mean difference in body mass index (BMI) in patients who were involved in randomised controlled trials comparing a mobile phone intervention (MPI) versus control. The mean difference of each trial corresponds to the middle of the squares, and the horizontal line shows the 95% confidence interval (CI). The summary mean difference, is represented by the middle of the solid diamond. A test of heterogeneity is given below the summary statistics where df refers to degrees of freedom.
blood pressure
cardiac rehabilitation
cardiovascular disease
electrocardiogram
left ventricular ejection fraction
Morisky Medication Adherence Scale
mobile phone intervention
New York Heart Association
odds ratio
Preferred Reporting Items for Systematic Reviews and Meta-Analyses
randomized control trials
None declared.