Text Message Medication Adherence Reminders Automated and Delivered at Scale Across Two Institutions: Testing the Nudge System: Pilot Study

Mobile phone text messaging for medication adherence in secondary prevention of cardiovascular disease

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for almost 18 million deaths annually. People with CVDs have a five times greater chance of suffering a recurrent cardiovascular event than people without known CVDs. Although drug interventions have been shown to be cost-effective in reducing the risk of recurrent cardiovascular events, adherence to medication remains suboptimal. As a scalable and cost-effective approach, mobile phone text messaging presents an opportunity to convey health information, deliver electronic reminders, and encourage behaviour change. However, it is uncertain whether text messaging can improve medication adherence and clinical outcomes. This is an update of a Cochrane review published in 2017.

OBJECTIVES

To evaluate the benefits and harms of mobile phone text messaging for improving medication adherence in people with CVDs compared to usual care.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, four other databases, and two trial registers. We also checked the reference lists of all primary included studies and relevant systematic reviews and meta-analyses. The date of the latest search was 30 August 2023.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) with participants with established arterial occlusive events. We included trials investigating interventions using short message service (SMS) or multimedia messaging service (MMS) with the aim of improving adherence to medication for the secondary prevention of cardiovascular events. The comparator was usual care. We excluded cluster-RCTs and quasi-RCTs.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methods. Our primary outcomes were medication adherence, fatal cardiovascular events, non-fatal cardiovascular events, and combined CVD event. Secondary outcomes were low-density lipoprotein cholesterol for the effect of statins, blood pressure for antihypertensive drugs, heart rate for the effect of beta-blockers, urinary 11-dehydrothromboxane B2 for the antiplatelet effects of aspirin, adverse effects, and patient-reported experience. We used GRADE to assess the certainty of the evidence for each outcome.

MAIN RESULTS

We included 18 RCTs involving a total of 8136 participants with CVDs. We identified 11 new studies in the review update and seven studies in the previous version of the review. Participants had various CVDs including acute coronary syndrome, coronary heart disease, stroke, myocardial infarction, and angina. All studies were conducted in middle- and high-income countries, with no studies conducted in low-income countries. The mean age of participants was 53 to 64 years. Participants were recruited from hospitals or cardiac rehabilitation facilities. Follow-up ranged from one to 12 months. There was variation in the characteristics of text messages amongst studies (e.g. delivery method, frequency, theoretical grounding, content used, personalisation, and directionality). The content of text messages varied across studies, but generally included medication reminders and healthy lifestyle information such as diet, physical activity, and weight loss. Text messages offered advice, motivation, social support, and health education to promote behaviour changes and regular medication-taking. We assessed risk of bias for all studies as high, as all studies had at least one domain at unclear or high risk of bias. Medication adherence Due to different evaluation score systems and inconsistent definitions applied for the measurement of medication adherence, we did not conduct meta-analysis for medication adherence. Ten out of 18 studies showed a beneficial effect of mobile phone text messaging for medication adherence compared to usual care, whereas the other eight studies showed either a reduction or no difference in medication adherence with text messaging compared to usual care. Overall, the evidence is very uncertain about the effects of mobile phone text messaging for medication adherence when compared to usual care. Fatal cardiovascular events Text messaging may have little to no effect on fatal cardiovascular events compared to usual care (odds ratio 0.83, 95% confidence interval (CI) 0.47 to 1.45; 4 studies, 1654 participants; low-certainty evidence). Non-fatal cardiovascular events We found very low-certainty evidence that text messaging may have little to no effect on non-fatal cardiovascular events. Two studies reported non-fatal cardiovascular events, neither of which found evidence of a difference between groups. Combined CVD events We found very low-certainty evidence that text messaging may have little to no effect on combined CVD events. Only one study reported combined CVD events, and did not find evidence of a difference between groups. Low-density lipoprotein cholesterol Text messaging may have little to no effect on low-density lipoprotein cholesterol compared to usual care (mean difference (MD) -1.79 mg/dL, 95% CI -4.71 to 1.12; 8 studies, 4983 participants; very low-certainty evidence). Blood pressure Text messaging may have little to no effect on systolic blood pressure (MD -0.93 mmHg, 95% CI -3.55 to 1.69; 8 studies, 5173 participants; very low-certainty evidence) and diastolic blood pressure (MD -1.00 mmHg, 95% CI -2.49 to 0.50; 5 studies, 3137 participants; very low-certainty evidence) when compared to usual care. Heart rate Text messaging may have little to no effect on heart rate compared to usual care (MD -0.46 beats per minute, 95% CI -1.74 to 0.82; 4 studies, 2946 participants; very low-certainty evidence).

AUTHORS' CONCLUSIONS

Due to limited evidence, we are uncertain if text messaging reduces medication adherence, fatal and non-fatal cardiovascular events, and combined cardiovascular events in people with cardiovascular diseases when compared to usual care. Furthermore, text messaging may result in little or no effect on low-density lipoprotein cholesterol, blood pressure, and heart rate compared to usual care. The included studies were of low methodological quality, and no studies assessed the effects of text messaging in low-income countries or beyond the 12-month follow-up. Long-term and high-quality randomised trials are needed, particularly in low-income countries.

Developing an Artificial Intelligence-Driven Nudge Intervention to Improve Medication Adherence: A Human-Centred Design Approach

To improve medication adherence, we co-developed a digital, artificial intelligence (AI)-driven nudge intervention with stakeholders (patients, providers, and technologists). We used a human-centred design approach to incorporate user needs in creating an AI-driven nudge tool. We report the findings of the first stage of a multi-phase project: understanding user needs and ideating solutions. We interviewed healthcare providers (n = 10) and patients (n = 10). Providers also rated example nudge interventions in a survey. Stakeholders felt the intervention could address existing deficits in medication adherence tracking and were optimistic about the solution. Participants identified flexibility of the intervention, including mode of delivery, intervention intensity, and the ability to stratify to user ability and needs, as critical success factors. Reminder nudges and provision of healthcare worker contact were rated highly by all. Conversely, patients perceived incentive-based nudges poorly. Finally, participants suggested that user burden could be minimised by leveraging existing software (rather than creating a new App) and simplifying or automating the data entry requirements where feasible. Stakeholder interviews generated in-depth data on the perspectives and requirements for the proposed solution. The participatory approach will enable us to incorporate user needs into the design and improve the utility of the intervention. Our findings show that an AI-driven nudge tool is an acceptable and appropriate solution, assuming it is flexible to user requirements.

Nudging oral habits; application of behavioral economics in oral health promotion: a critical review

Background

Oral health disorders significantly contribute to the global incidence of chronic diseases. Nudge interventions have demonstrated effectiveness in enhancing people's decision-making and self-management capacities in a cost-efficient manner. As a result, these interventions could be valuable tools for fostering improved oral care habits. This critical review explores potential behavioral nudges applicable to promoting oral health.

Methods

A thorough electronic literature search was conducted on Scopus, Embase, and PubMed databases for papers published post-2008. The search focused on empirical evidence concerning the direct and indirect application of Nudge theory in oral health enhancement. In addition, the investigation included the nudge intervention's role in managing common non-communicable disease risk factors (tobacco, alcohol, and sugar) and their use in other health sectors.

Results and conclusion

There is a dearth of studies on behavioral economics, particularly those involving reward and reminder techniques. However, various successful nudge interventions have been identified in other sectors that aim to improve health decisions. These include strategies encouraging healthier nutritional choices, tobacco and alcohol cessation, medication compliance, routine physical activity, and regular health check-ups. Such interventions can also have direct or indirect positive impacts on oral health. Implementing these interventions within an oral care framework could promote oral health due to similar underlying cognitive mechanisms. However, different types of nudge interventions have varying degrees of effectiveness. Furthermore, factors such as the method of delivery and the characteristics of the targeted population significantly influence the outcome of the intervention. Hence, it is imperative to conduct extensive studies in diverse socioeconomic settings to fully understand the potentials, limitations, and impacts of nudge interventions in promoting oral health.

Description of patient questions received by clinical pharmacists in the Nudge Study

PURPOSE

The Nudge Study is a patient level-randomized trial testing different text message medication refill reminders sent to patients assigned to 4 arms: (1) usual care, (2) generic text, (3) optimized text, and (4) optimized text plus chatbot. This report describes the frequency and types of patient questions sent to clinical pharmacists (CPs) following text reminders.

METHODS

Patients were enrolled from Denver Health and Hospital Authority (DHHA) and Veterans Affairs Eastern Colorado Health Care System (VA ECHCS) from October 1, 2019, through May 30, 2021. Included patients responded to at least 1 text or interactive voice response (IVR) message. Patients were dichotomized as those who posed at least 1 question to a CP and those who posed no questions.

RESULTS

Of the 6,325 patients enrolled in an intervention arm, 3,323 (52.5%) responded to at least 1 text or IVR message, and among those responding, 305 (9.2%) responded with a pharmacist question. Patient factors associated with submitting a CP question included age (45-74 years), enrollment from DHHA, and receipt of the optimized text or optimized text plus chatbot message versus the generic text. Questions to CP were in the following categories: medication related (48.2%), refill logistics (38.4%), cost (9.2%), and other (17.7%).

CONCLUSION

In a text messaging intervention focused on medication refills, there were few questions directed to the CP. Patients assigned to receive optimized texts were more likely to have questions. We hypothesize that this may suggest greater patient engagement regarding their condition, resulting in more questions.

Effects of the theory of planned behavior and nudge strategy-based intervention on the adherence to anticoagulation treatment in patients with non-valvular atrial fibrillation

BACKGROUND

Non-valvular atrial fibrillation is associated with the incidence of thromboembolism. Current guidelines recommend preferential use of novel oral anticoagulants(NOAC) in patients with nonvalvular atrial fibrillation. Oral anticoagulation medication adherence rate was relatively low among discharged patients with non-valvular atrial fibrillation.

AIM

To investigate the effects of the anticoagulation programs based on the theory of planned behavior and nudge strategy among patients with non-valvular atrial fibrillation.

METHODS

130 patients with non-valvular atrial fibrillation were randomized to the intervention group or control group, 72 patients in the intervention group, and 58 patients in the control group with a 6-month follow-up. Medication adherence,intention,attitude, perceived behavioral control and subjective norm and quality of life were assessed.

RESULTS

There were significantly differences in the attitude and subjective norm between the two groups at one month,three months and six months follow-up(P <0.01).There were significantly differences in the perceived behavioral control between the two groups at six months follow-up(P <0.01).There were significantly differences in the intention scale between the two groups at three months follow-up(P <0.01). The medication adherence scale score was higher in the intervention group than in the control group at six months follow-up.However, there were no differences in quality of life between the two groups at six months follow-up.

CONCLUSIONS

The program based on the theory of planned behavior and nudge strategy can improve medication adherence in patients with non-valvular atrial fibrillation.

Feasibility of a Reinforcement Learning-Enabled Digital Health Intervention to Promote Mammograms: Retrospective, Single-Arm, Observational Study

BACKGROUND

Preventive screenings such as mammograms promote health and detect disease. However, mammogram attendance lags clinical guidelines, with roughly one-quarter of women not completing their recommended mammograms. A scalable digital health intervention leveraging behavioral science and reinforcement learning and delivered via email was implemented in a US health system to promote uptake of recommended mammograms among patients who were 1 or more years overdue for the screening (ie, 2 or more years from last mammogram).

OBJECTIVE

The aim of this study was to establish the feasibility of a reinforcement learning-enabled mammography digital health intervention delivered via email. The research aims included understanding the intervention's reach and ability to elicit behavioral outcomes of scheduling and attending mammograms, as well as understanding reach and behavioral outcomes for women of different ages, races, educational attainment levels, and household incomes.

METHODS

The digital health intervention was implemented in a large Catholic health system in the Midwestern United States and targeted the system's existing patients who had not received a recommended mammogram in 2 or more years. From August 2020 to July 2022, 139,164 eligible women received behavioral science-based email messages assembled and delivered by a reinforcement learning model to encourage clinically recommended mammograms. Target outcome behaviors included scheduling and ultimately attending the mammogram appointment.

RESULTS

In total, 139,164 women received at least one intervention email during the study period, and 81.52% engaged with at least one email. Deliverability of emails exceeded 98%. Among message recipients, 24.99% scheduled mammograms and 22.02% attended mammograms (88.08% attendance rate among women who scheduled appointments). Results indicate no practical differences in the frequency at which people engage with the intervention or take action following a message based on their age, race, educational attainment, or household income, suggesting the intervention may equitably drive mammography across diverse populations.

CONCLUSIONS

The reinforcement learning-enabled email intervention is feasible to implement in a health system to engage patients who are overdue for their mammograms to schedule and attend a recommended screening. In this feasibility study, the intervention was associated with scheduling and attending mammograms for patients who were significantly overdue for recommended screening. Moreover, the intervention showed proportionate reach across demographic subpopulations. This suggests that the intervention may be effective at engaging patients of many different backgrounds who are overdue for screening. Future research will establish the effectiveness of this type of intervention compared to typical health system outreach to patients who have not had recommended screenings as well as identify ways to enhance its reach and impact.

Applications of Behavioral Economics to Pharmaceutical Policymaking: A Scoping Review with Implications for Best-Value Biological Medicines

BACKGROUND AND OBJECTIVE

Pharmaceutical policies are generally based on the assumption that involved stakeholders make rational decisions. However, behavioral economics has taught us that this is not always the case as people deviate from rational behavior in rather predictable patterns. This scoping review examined to what extent behavioral concepts have already been applied in the pharmaceutical domain and what evidence exists about their effectiveness, with the aim of formulating future applications and research hypotheses on policymaking for best-value biologicals.

METHODS

A scoping literature review was conducted on the evidence of behavioral applications to pharmaceuticals. Scientific databases (Embase, MEDLINE, APA PsycArticles, and Scopus) were searched up to 20 October, 2021.

RESULTS

Forty-four full-text scientific articles were identified and narratively described in this article. Pharmaceutical domains where behavioral concepts have been investigated relate to influencing prescribing behavior, improving medication adherence, and increasing vaccination uptake. Multiple behavioral concepts were examined in the identified studies, such as social norms, defaults, framing, loss aversion, availability, and present bias. The effectiveness of the applied interventions was generally positive, but depended on the context. Some of the examined interventions can easily be translated into effective policy interventions for best-value biological medicines. However, some applications require further investigation in a research context.

CONCLUSIONS

Applications of behavioral economics to pharmaceutical policymaking are promising. However, further research is required to investigate the effect of behavioral applications on policy interventions for a more sustainable market environment for best-value biological medicines.

OUP accepted manuscript

The increasing volume and richness of healthcare data collected during routine clinical practice have not yet translated into significant numbers of actionable insights that have systematically improved patient outcomes. An evidence-practice gap continues to exist in healthcare. We contest that this gap can be reduced by assessing the use of nudge theory as part of clinical decision support systems (CDSS). Deploying nudges to modify clinician behaviour and improve adherence to guideline-directed therapy represents an underused tool in bridging the evidence-practice gap. In conjunction with electronic health records (EHRs) and newer devices including artificial intelligence algorithms that are increasingly integrated within learning health systems, nudges such as CDSS alerts should be iteratively tested for all stakeholders involved in health decision-making: clinicians, researchers, and patients alike. Not only could they improve the implementation of known evidence, but the true value of nudging could lie in areas where traditional randomized controlled trials are lacking, and where clinical equipoise and variation dominate. The opportunity to test CDSS nudge alerts and their ability to standardize behaviour in the face of uncertainty may generate novel insights and improve patient outcomes in areas of clinical practice currently without a robust evidence base.

Leave me out: Patients' characteristics and reasons for opting out of a pragmatic clinical trial involving medication adherence

Opt-out procedures are sometimes used instead of standard consent practices to enable patients to exercise their autonomous preferences regarding research participation while reducing patient and researcher burden. However, little is known about the characteristics of patients who opt-out of research and their reasons for doing so. We gathered such information in a large pragmatic clinical trial (PCT) evaluating the effect of theory informed text messages on medication adherence.Eligible patients, identified through electronic health records, were sent information about the study and provided with an opportunity to opt-out. Those opting out were asked to complete a voluntary survey regarding their reasons for doing so. Demographic data were compared among patients opting-out vs those included in the study using chi-squared tests and a log binomial regression model.Of 9046 patients receiving study packets, 906 (10.0%) patients returned opt-out forms. Of those, 451 (49.8%) returned the opt-out survey. Patients who opted out were more likely to be older, white, and nonHispanic than those who were included in the PCT. Survey respondents expressed high levels of trust in their health care providers, research, and system. Nearly half (46.6%) reported concerns about time as a reason to opt-out.In this PCT, 10% of patients receiving packets opted out, with significant differences in age, race, gender, and ethnicity compared to those included. Future trials should further investigate representativeness and reasons patients choose to opt-out of participating in research.

Reevaluating medication adherence in the era of digital health

INTRODUCTION

Medication adherence is a worldwide issue impacting more than half the population. The cost associated with nonadherence is tremendous and has spurred the growth of novel technologies to address this growing problem.

AREAS COVERED

This perspective covers the different digital health medication adherence tools that have come to market in the past decade and their clinical impact. These digital interventions and their applicability to medication adherence across different stakeholders are then evaluated.

EXPERT OPINION

Digital health will play a significant role in creating new pathways to care in the 2020s. However, the current design of medication adherence tools has not demonstrated a clinical impact that will be relevant for the digital health space without a change in redesign factoring in relevant stakeholders' incentives to address adherence issues. A focus on only adherence has not yielded the economic or clinical benefit as expected, which is likely due to a lack of focus on broader drug-related problems (DRPs) that are causative factors beyond adherence alone. As such, adherence tools will see disparate uptake, likely due to condition-specific interventions rather than adherence issues as a whole, and future endeavors will need to address the larger DRP considerations to actualize clinical outcomes.

Enhancing the use of EHR systems for pragmatic embedded research: lessons from the NIH Health Care Systems Research Collaboratory

OBJECTIVE

We identified challenges and solutions to using electronic health record (EHR) systems for the design and conduct of pragmatic research.

MATERIALS AND METHODS

Since 2012, the Health Care Systems Research Collaboratory has served as the resource coordinating center for 21 pragmatic clinical trial demonstration projects. The EHR Core working group invited these demonstration projects to complete a written semistructured survey and used an inductive approach to review responses and identify EHR-related challenges and suggested EHR enhancements.

RESULTS

We received survey responses from 20 projects and identified 21 challenges that fell into 6 broad themes: (1) inadequate collection of patient-reported outcome data, (2) lack of structured data collection, (3) data standardization, (4) resources to support customization of EHRs, (5) difficulties aggregating data across sites, and (6) accessing EHR data.

DISCUSSION

Based on these findings, we formulated 6 prerequisites for PCTs that would enable the conduct of pragmatic research: (1) integrate the collection of patient-centered data into EHR systems, (2) facilitate structured research data collection by leveraging standard EHR functions, usable interfaces, and standard workflows, (3) support the creation of high-quality research data by using standards, (4) ensure adequate IT staff to support embedded research, (5) create aggregate, multidata type resources for multisite trials, and (6) create re-usable and automated queries.

CONCLUSION

We are hopeful our collection of specific EHR challenges and research needs will drive health system leaders, policymakers, and EHR designers to support these suggestions to improve our national capacity for generating real-world evidence.

Mobile phone-based interventions for improving adherence to medication prescribed for the primary prevention of cardiovascular disease in adults

BACKGROUND

Cardiovascular disease (CVD) is a major cause of disability and mortality globally. Premature fatal and non-fatal CVD is considered to be largely preventable through the control of risk factors by lifestyle modifications and preventive medication. Lipid-lowering and antihypertensive drug therapies for primary prevention are cost-effective in reducing CVD morbidity and mortality among high-risk people and are recommended by international guidelines. However, adherence to medication prescribed for the prevention of CVD can be poor. Approximately 9% of CVD cases in the EU are attributed to poor adherence to vascular medications. Low-cost, scalable interventions to improve adherence to medications for the primary prevention of CVD have potential to reduce morbidity, mortality and healthcare costs associated with CVD.

OBJECTIVES

To establish the effectiveness of interventions delivered by mobile phone to improve adherence to medication prescribed for the primary prevention of CVD in adults.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and two other databases on 7 January 2020. We also searched two clinical trials registers on 5 February 2020. We searched reference lists of relevant papers. We applied no language or date restrictions.

SELECTION CRITERIA

We included randomised controlled trials investigating interventions delivered wholly or partly by mobile phones to improve adherence to cardiovascular medications prescribed for the primary prevention of CVD. We only included trials with a minimum of one-year follow-up in order that the outcome measures related to longer-term, sustained medication adherence behaviours and outcomes. Eligible comparators were usual care or control groups receiving no mobile phone-delivered component of the intervention.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane. The main outcomes of interest were objective measures of medication adherence (blood pressure (BP) and cholesterol), CVD events, and adverse events. We contacted study authors for further information when this was not reported.

MAIN RESULTS

We included 14 trials with 25,633 randomised participants. Participants were recruited from community-based primary and tertiary care or outpatient clinics. The interventions varied widely from those delivered solely through short messaging service (SMS) to those involving a combination of modes of delivery, such as SMS in addition to healthcare worker training, face-to-face counselling, electronic pillboxes, written materials, and home blood pressure monitors. Some interventions only targeted medication adherence, while others additionally targeted lifestyle changes such as diet and exercise. Due to heterogeneity in the nature and delivery of the interventions and study populations, we reported most results narratively, with the exception of two trials which were similar enough to meaningfully pool in meta-analyses. The body of evidence for the effect of mobile phone-based interventions on objective outcomes of adherence (BP and cholesterol) was of low certainty, due to most trials being at high risk of bias, and inconsistency in outcome effects. Two trials were at low risk of bias. Among five trials (total study enrolment: 5441 participants) recording low-density lipoprotein cholesterol (LDL-C), two studies found evidence for a small beneficial intervention effect on reducing LDL-C (-5.30 mg/dL, 95% confidence interval (CI) -8.30 to -2.30; and -9.20 mg/dL, 95% CI -17.70 to -0.70). The other three studies found results varying from a small reduction (-7.7 mg/dL) to a small increase in LDL-C (0.77 mg/dL). All of which had wide confidence intervals that included no effect. Across 13 studies (25,166 participants) measuring systolic blood pressure, effect estimates ranged from a large reduction (MD -12.45 mmHg, 95% CI -15.02 to -9.88) to a small increase (MD 2.80 mmHg, 95% CI 0.30 to 5.30). We found a similar range of effect estimates for diastolic BP, ranging from -12.23 mmHg (95% CI 14.03 to -10.43) to 1.64 mmHg (95% CI -0.55 to 3.83) (11 trials, 19,716 participants). Four trials showed intervention benefits for systolic and diastolic BP with confidence intervals excluding no effect, and among these were all three of the trials evaluating self-monitoring of blood pressure with mobile phone-based telemedicine. The fourth trial included SMS and provider support (with additional varied features). Seven studies (19,185 participants) reported 'controlled' BP as an outcome, and intervention effect estimates varied from negligible effects (odds ratio (OR) 1.01, 95% CI 0.76 to 1.34) to large improvements in BP control (OR 2.41, 95% CI: 1.57 to 3.68). The three trials of clinician training or decision support combined with SMS (with additional varied features) had confidence intervals encompassing benefits and harms, with point estimates close to zero. Pooled analyses of the two trials of interventions solely delivered through SMS were indicative of little or no beneficial intervention effect on systolic BP (MD -1.55 mmHg, 95% CI -3.36 to 0.25; I² = 0%) and small increases in controlled BP (OR 1.32, 95% CI 1.06 to 1.65; I² = 0%). Based on four studies (12,439 participants), there was very low-certainty evidence (downgraded twice for imprecision and once for risk of bias) relating to the intervention effect on combined (fatal and non-fatal) CVD events. Two studies (2535 participants) provided low-certainty evidence for the effect of the intervention on cognitive outcomes, with little or no difference between trial arms for perceived quality of care and satisfaction with treatment. There was moderate-certainty evidence (downgraded due to risk of bias) that the interventions did not cause harm, based on six studies (8285 participants). Three studies reported no adverse events attributable to the intervention. One study reported no difference between groups in experience of adverse effects of statins, and that no participants reported intervention-related adverse events. One study stated that potential side effects were similar between groups. One study reported a similar number of deaths in each arm, but did not provide further information relating to potential adverse events.

AUTHORS' CONCLUSIONS

There is low-certainty evidence on the effects of mobile phone-delivered interventions to increase adherence to medication prescribed for the primary prevention of CVD. Trials of BP self-monitoring with mobile-phone telemedicine support reported modest benefits. One trial at low risk of bias reported modest reductions in LDL cholesterol but no benefits for BP. There is moderate-certainty evidence that these interventions do not result in harm. Further trials of these interventions are warranted.