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Medication nonadherence leads to suboptimal treatment outcomes, making it a major priority in health care. eHealth provides an opportunity to offer medication adherence interventions with minimal effort from health care providers whose time and resources are limited.
The aim of this systematic review is twofold: (1) to evaluate effectiveness of recently developed and tested interactive eHealth (including mHealth) interventions on medication adherence in adult patients using long-term medication and (2) to describe strategies among effective interventions.
MEDLINE, EMBASE, Cochrane Library, PsycINFO, and Web of Science were systematically searched from January 2014 to July 2019 as well as reference lists and citations of included articles. Eligible studies fulfilled the following inclusion criteria: (1) randomized controlled trial with a usual care control group; (2) a total sample size of at least 50 adult patients using long-term medication; (3) applying an interactive eHealth intervention aimed at the patient or patient’s caregiver; and (4) medication adherence as primary outcome. Methodologic quality was assessed using the Cochrane risk of bias tool. Selection and quality assessment of studies were performed by 2 researchers (BP and BvdB or JV) independently. A best evidence synthesis was performed according to the Cochrane Back Review Group.
Of the 9047 records screened, 22 randomized clinical trials were included reporting on 29 interventions. Most (21/29, 72%) interventions specified using a (mobile) phone for calling, SMS text messaging, or mobile apps. A majority of all interactive interventions (17/29) had a statistically significant effect on medication adherence (
Overall, this review supports the hypothesis that interactive eHealth interventions can be effective in improving medication adherence. Intervention strategies that improve patients’ treatment involvement and their medication management skills are most promising and should be considered for implementation in practice.
Long-term medication aims to reduce the risk of disease progression, comorbidity, and mortality [
Medication adherence is defined as the extent to which medication taking behavior corresponds with the medication regimen agreed upon with the health care professional [
eHealth might provide an opportunity to offer accessible, interactive, timely, and feasible medication adherence interventions that require minimal effort from health care providers whose time and resources are limited. eHealth or telemedicine—these words are used interchangeably—is defined as the use of information and communication technology in health care [
eHealth seems a promising way forward but recent systematic reviews showed conflicting results for eHealth interventions on improving medication adherence [
This systematic review adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) statement [
Searches were undertaken in MEDLINE, EMBASE, Cochrane Library, PsycINFO, and Web of Science to identify eligible studies. The search strategy comprised 3 blocks: eHealth, medication adherence, and randomized clinical trial (see
Eligible studies fulfilled the following inclusion criteria: (1) randomized controlled trial with a usual care control group; (2) applying an interactive eHealth intervention aimed at the patient or patient’s caregiver; (3) medication adherence as primary outcome; (4) a total sample size of at least 50 adult patients using long-term medication as determined by Zwikker et al [
Two researchers (BP and JV) independently assessed the internal validity of included studies using the Cochrane Collaboration’s tool for assessing risk of bias [
A standardized template was made to extract data on study characteristics, eHealth interventions, and medication adherence outcomes. Details of the eHealth interventions were extracted according to the Template for Intervention Description and Replication (TIDieR) checklist [
Statistical data pooling was not feasible due to heterogeneity between studies and interventions. Therefore a best evidence synthesis was performed to examine the effectiveness of interactive eHealth interventions on medication adherence. The Cochrane Back Review Group defines 4 levels of evidence: strong, moderate, limited, and conflicting evidence [
PRISMA flow diagram of study search and selection.
Fifteen studies had a positive score on at least five domains and were regarded high-quality studies as shown in
Summary of risk of bias assessment using the Cochrane Collaboration’s tool for assessing risk of bias.
Over half of the studies (13/22) included long-term medication for cardiovascular disease, diabetes, or both. Seven studies focused on other, single long-term conditions, leaving 2 studies that looked at any long-term conditions where long-term medication was in use.
The smallest study reported on 70 participants at baseline and the largest study involved 21,752 participants. Because all studies were randomized, baseline characteristics of the different groups were generally the same.
Follow-up was short (ie, less than 6 months) in 11 studies and long (at least six months) in 11 studies. The primary medication adherence outcome of each of the studies was mainly assessed objectively using medication monitoring devices, pharmacy prescription data, and serum levels. The remaining 6 studies measured adherence subjectively with validated self-report questionnaires (eg, Immunosuppressant Therapy Adherence Instrument).
Twenty-nine different interactive eHealth interventions were evaluated as shown in
Most (25/29) interventions were aimed at the patient, 3 interventions were aimed at the caregiver, and another was aimed at either patient or caregiver.
Sixteen interventions were provided through automated software without involvement of a health care professional: 6 mobile apps, 5 monitoring devices, 3 SMS text messages or IVR interventions, and 2 e-training modules through an online portal. Another 7 interventions were provided through automated software in combination with tele-feedback by a health care professional or caregiver: 4 monitoring devices, 2 IVR or SMS text message interventions, 1 e-training. The 6 remaining interventions were telephone calls performed by health care professionals.
Regarding intervention strategies, nearly all (23/29, 79%) interventions aimed at informing and educating patients and just over half (15/29, 52%) sought to support patients by providing assistance and encouragement. All other strategies (eg, teaching skills, facilitating communication or decision making) were less frequently applied (see
Overall, 17 interventions yielded a statistically significant improvement of medication adherence compared to the control group (
Characteristics of the eHealth interventions.
Study and medication | Adherence inclusion criterion | Intervention arm (n) | Control arm (n) | Follow-up (in weeks) | Mode of adherence tele-feedback | Description of the intervention | |
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Tacrolimus | None | 38 | 50 | 13 | App | Transplant Hero is an interactive alarm to remind patients to take their medications as well as providing educational content. |
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Tacrolimus | None | 20 | 50 | 13 | App and smart-watch | Transplant Hero (see above) combined with a smartwatch that displayed the reminder notifications. |
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Bisphosphonates | None | 127 | 118 | 4 | IVRa | An IVR call focusing on known reasons for not initiating therapy. If the medication was not picked up 7 days after receiving the call, a reminder letter was sent. |
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Antihypertensives or medication for lowering blood glucose or cholesterol | None | 1220 | 1158 | 9 | Call | A single-protocol-structured telephone call from an interventionist using positive reinforcement and probing for reasons of nonadherence. |
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Statins | <80% | 51 | 34 | 26 | Device | A wireless pill bottle generated an alert message, sent to the participant, if medication was missed the previous day and at least once in the 2 prior days. |
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Statins | <80% | 46 | 34 | 26 | Device | A wireless pill bottle generated an automated alert message (see above), sent to the participant and a designated caregiver. |
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Antihypertensives | None | 73 | 75 | 52 | App | The AlerHTA app aimed to promote health education in hypertension and remind for both appointments and medication intake time. |
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Apixaban | None | 579 | 583 | 24 | e-Training | An education program consisting of an education booklet, one or more reminder tools chosen by the participant, and access to a telephone clinic. |
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Statins | <80% | 67 | 67 | 13 | Device | PROMOTE-1: a wireless pill bottle generated a weekly adherence report in which the patient’s adherence was compared to other patients. |
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Statins | <80% | 67 | 67 | 13 | Device | PROMOTE-2: a wireless pill bottle generated a weekly adherence report. |
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Statins | <80% | 50 | 50 | 13 | Device | SUPPORT-1: a wireless pill bottle generated a daily adherence report. |
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Statins | <80% | 50 | 50 | 13 | Device | SUPPORT-2: a wireless pill bottle generated a weekly adherence report. |
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Statins | <80% | 50 | 50 | 13 | Device | SUPPORT-3: a wireless pill bottle generated an email alert if the patient missed a dose the previous day. |
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Tacrolimus | None | 40 | 40 | 26 | Device | A wireless pill bottle generated an alert when medication was due and patients could select additional reminders such as SMS text messages, calls, or emails. |
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Tacrolimus | None | 40 | 40 | 26 | Device | A wireless pill bottle generated an alert (see above). If adherence decreased to <90% in a 14-day period, the study coordinator would call the patient and notify the involved HCPsc. |
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Calcipotriol/betamethasone foam | none | 68 | 66 | 4 | App | An app which provided once-daily reminders and information on number of treatment applications and amount of prescribed foam applied. |
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RASb inhibitors | <80% | 87 | 99 | 26 | Call | A brief telephone intervention by pharmacists to remind the patients of their overdue refill and to identify potential adherence barriers. |
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RAS inhibitors | <80% | 248 | 495 | 26 | Call | Six motivational interviewing phone calls by pharmacy students to identify potential adherence barriers and provide guidance to address these barriers. |
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Antihypertensives or medication for lowering blood glucose or cholesterol | <80% | 2038 | 2040 | 52 | Call | Tailored telephone consultation to develop a shared plan to improve adherence and disease control. At 6 and 9 months progress reports were mailed. |
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Bisphosphonates and strontium ranelate | None | 79 | 85 | 52 | Call | Bimonthly telephone follow-up to motivate patients to maintain good adherence, detect difficulties in compliance, and recall the importance of treatment continuation. |
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Bisphosphonates, RAS inhibitors, and statins | None | 2008 | 2914 | 52 | Call | Telephone counselling 7-21 days after the start of therapy assessing practical and perceptual barriers and providing information and motivation. |
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RAS inhibitors and statins | <90% | 7247 | 7255 | 52 | IVR | An IVR call when (over)due for a refill providing patient education and refill support. |
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RAS inhibitors and statins | <90% | 7250 | 7255 | 52 | IVR | In addition to IVR calls (see above), a reminder letter was sent if they were 60-89 days overdue, a call was made if they were ≥90 days overdue, and primary care provider informed. Patients also received a personalized health report, a pill organizer, and bimonthly mailings. |
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Highly active antiretroviral therapy | <95% | 47 | 50 | 4 | e-Training | eLifeSteps: a single-session, self-paced multimedia intervention tackling practical and psychological adherence barriers accompanied with a workbook. |
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Immunosuppressants | None | 35 | 35 | 26 | e-Training | Transplant-TAVIE was composed of 3 interactive Web-based sessions by a virtual nurse aimed at developing and reinforcing self-management skills required for medication intake. |
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Preventive medication for stroke | None | 100 | 100 | 8 | SMS text messages | SMS4stroke sent automated customized SMS text message reminders to either patient or caregiver. |
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Statins and antiplatelets | None | 99 | 98 | 13 | IVR and SMS | Daily IVR call services, daily prescription-tailored medication reminders, and once weekly life style modification messages. |
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All medication allowed, >2 | None | 51 | 49 | 13 | App | A tablet-based medication self-management app (ALICE) with medication reminders and medication information such as pictures, interactions, storage instructions, and common errors in medication use. |
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Antihypertensives | None | 209 | 202 | 12 | App | The MediSafe app is a medication reminder app with additional functions such as adherence reports, tracking of measurements, and peer support. |
aIVR: interactive voice response.
bRAS: renin–angiotensin system.
cHCP: health care professional.
Adherence measure and medication adherence results of the studies reviewed.
Adherence measure, study, and results on medication adherence | Statistically significanta | ||
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The coefficient of variability (SD/mean × 100) of tacrolimus levels was 33.0 for the intervention group and 32.8 for the control group (Cohen |
– | |
The coefficient of variability was 33.8 for the intervention group and 32.8 for the control group (Cohen |
– | ||
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49% of the intervention group filled their first prescription compared to 31% of the control group (ORb 2.17; 95% CI 1.29-3.67). | + |
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– | |
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84% of the intervention group filled their first prescription compared to 84% of the control group (OR 0.94; 95% CI 0.79-1.11). | – |
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Average daily adherence was 53% for the intervention group and 36% for the control group (Cohen |
+ |
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Average daily adherence was 55% for the intervention group and 36% for the control group (Cohen |
+ |
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Average daily adherence was 86% for the intervention group and 63% for the control group (Cohen |
+ |
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Average daily adherence was 92% for the intervention group and 92% for the control group (Cohen |
– |
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Average daily adherence was 77% for the intervention group and 75% for the control group. | – |
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Average daily adherence was 71% for the intervention group and 75% for the control group. | – |
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Average daily adherence was 73% for the intervention group and 79% for the control group. | – |
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Average daily adherence was 75% for the intervention group and 79% for the control group. | – |
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Average daily adherence was 75% for the intervention group and 79% for the control group. | – |
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Average daily adherence (during the final 90 days) was 78% for the intervention group and 55% for the control group (Cohen |
+ |
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Average daily adherence (during final 90 days) was 88% for the intervention group and 55% for the control group (Cohen |
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66% of the intervention group was considered adherent compared to 38% of the control group (OR 3.22; 95% CI 1.53-6.80). | + |
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PDC was 58% for the intervention group and 29% for the control group (Cohen |
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PDC was 66% for the intervention group and 57% for the control group (Cohen |
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PDC was 46% for the intervention group and 42% for the control group (Cohen |
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65% of the intervention group was considered adherent compared to 33% of the control group (OR 3.71; 95% CI 1.94-7.07). | + |
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PDC was 81% for the intervention group and 76% for the control group (Cohen |
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PDC was 58% for the intervention group and 56% for the control group (Cohen |
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PDC was 59% for the intervention group and 56% for the control group (Cohen |
+ |
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Adherence was 81% for the intervention group and 81% for the control group (Cohen |
– |
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Mean ITAS score was 11.7 in the intervention group and 11.3 in the control group (Cohen |
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Mean MMAS score was 7.4 in the intervention group and 6.7 in the control group (Cohen |
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Mean MMAS score was 7.3 in the intervention group and 7.1 in the control group (Cohen |
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Mean MMAS score was 7.4 in the intervention group and 7.3 in the control group (Cohen |
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Mean MMAS score was 6.3 in the intervention group and 5.7 in the control group (Cohen |
+ |
aAs reported by the authors. + indicates
bOR: odds ratio.
cPDC: percentage of days covered.
dAll PDC outcomes were based on refill data; pill counts were considered separately.
eAACTGAI: Adult AIDS Clinical Trials Group Adherence Instrument.
fITAS: Immunosuppressant Therapy Adherence Instrument.
gMMAS: Morisky Medication Adherence Scale.
Further details of the study, population, intervention, and outcomes can be found in the extraction database provided as
The best evidence synthesis (
In the post hoc sensitivity analysis the criteria for a high-quality study were more stringent (6 out of 7 domains graded as low risk of bias). The sensitivity analysis showed that the strong evidence for a positive effect for SMS or IVR as mode of adherence tele-feedback remained, whereas the evidence turned to conflicting for interventions delivered through mobile apps and calls (see
The level of evidence of the intervention strategies was also assessed. There was strong evidence for a positive effect of strategies to teach skills, to facilitate communication or decision making, and to improve health care quality. For all other intervention strategies (eg, to support, to inform and educate) there was conflicting evidence (see
Results of the best evidence synthesis.
Mode of adherence tele-feedback and quality | Statistically significanta | Level of evidence | |
Monitoring device |
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Conflicting evidence | |
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9 HQb interventions | +, +, +, +, –, –, –, –, – |
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0 LQc interventions |
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SMS text messaging or IVRd |
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Strong evidence for a positive effect | |
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5 HQ interventions | +, +, +, +, – |
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0 LQ interventions |
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Mobile app |
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Strong evidence for a positive effect | |
3 HQ interventions | +, +, + |
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3 LQ interventions | +, –, – | ||
Call |
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Strong evidence for a positive effect | |
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4 HQ interventions | +, +, +, – |
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2 LQ interventions | +, + | ||
e-Training |
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Moderate evidence for no effect | |
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1 HQ intervention | – |
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2 LQ interventions | –, – |
a+ indicates
bHQ: high quality.
cLQ: lower quality.
dIVR: interactive voice response.
This systematic review examined the effectiveness of interactive eHealth interventions to improve medication adherence in patients using long-term medication published between 2014 and 2019. A majority, 17/29 interactive interventions, had a statistically significant (
This study showed strong evidence for a positive effect on medication adherence of eHealth interventions across various channels, including SMS, IVR, mobile apps, and calls. Our findings add robustness to the positive effect of eHealth interventions provided by previous systematic reviews and meta-analyses [
We found a lack of convincing evidence for interventions applying an electronic monitoring device or e-training. By contrast, van Heuckelum et al [
To describe intervention strategies among effective interactive eHealth interventions we used Lowe’s taxonomy as it is specific for adherence interventions with clear examples for each strategy. Although other taxonomies (eg, Abraham and Michie [
Noteworthy, the included studies in our review using eHealth interventions to address medication adherence reflect 2 distinct patient populations, namely, the large patient population (eg, metabolic and cardiovascular disease) and the population where optimal medication adherence is critical (eg, immunosuppressants, antiretroviral therapy). Applying eHealth to address medication adherence can be advantageous for both populations albeit for different reasons. eHealth interventions can be accessible for large patient populations, giving health care professionals a large outreach with limited resources. For populations where optimal medication adherence is critical, eHealth interventions can be tailored to patients’ specific needs and provide continuous support.
Where others found a lack of high-quality studies and stressed the importance of improving study quality [
We clustered evidence of various long-term conditions in our best evidence synthesis to provide a comprehensive overview. This overview is based on the statistically significant effects (
The synthesis was limited to medication adherence and did not consider other clinical outcomes. As a result, our findings may not be applicable one-on-one to specific conditions. Next step is to study the identified effective interventions/strategies in specific long-term conditions to ascertain that this may lead to improved medication adherence and other clinical outcomes.
Only postintervention effectiveness on medication adherence was assessed in this review. Whether the found beneficial effects will be maintained over a longer period (>12 months) remains unclear. However, 12/17 effective interventions in our review had a follow-up of at least six months which is considered the shortest period to accurately assess long-term medication adherence [
We were surprised to find many interactive eHealth interventions that use technologies published in the 20th century. Although technology changes, applied techniques are very similar. To be able to build upon data and lessons learnt from older technologies, crosslinks between similar techniques need to be made (eg, between SMS text messaging and chat services such as WhatsApp or WeChat).
Technological developments are very fast paced and eHealth interventions continuously change. This high turnaround speed creates a need for study designs that allow continuous evaluation of interventions over a period of at least six months.
In this review intervention exposure ranged from a single call to daily messages for months. To establish a relation between exposure and medication taking behavior change, dose–response studies are called for.
We found that a majority of interactive eHealth interventions are effective in improving adherence to long-term medication. Intervention strategies that improve patient’s treatment involvement and their medication management skills are most promising. While most interactive eHealth interventions were multifaceted, even simple eHealth technologies such as SMS text messaging and telephone calls can be effective in promoting medication adherence in a wide variety of patient populations.
MEDLINE search strategy.
Overview of the intervention strategies present in each e-Health intervention.
Sensitivity analysis.
Level of evidence of intervention strategies.
Extraction database.
Adult AIDS Clinical Trials Group Adherence Instrument
high quality
Immunosuppressant Therapy Adherence Instrument
interactive voice response
lower quality
Morisky Medication Adherence Scale
odds ratio
percentage of days covered
renin–angiotensin system
Template for Intervention Description and Replication
BP developed the PROSPERO protocol which was reviewed by JV, AL, HvO, MV, SvD, and BvdB. BP developed and conducted search strategy and screening and inclusion of the studies, designed extraction template, extracted data, and drafted the manuscript. Rating study quality and revision of subsequent drafts of the manuscript were done by BP and JV. JV and BvdB also performed article screening. CB, AL, HvO, MV, SvD, and BvdB critically reviewed the manuscript. All authors read and approved the final manuscript.
None declared.