Introduction

Hyperlipidemia represents a major risk factor for atherosclerotic cardiovascular disease (ASCVD). Prolonged exposure to even moderately increased levels of cholesterol are associated with coronary heart disease.¹ In the last few decades, an increase in the use of cholesterol lowering treatment has been associated with a decrease in the prevalence of hyperlipidemia, but much less progress has been made with lifestyle changes.² In 2013, the American College of Cardiology/American Heart Association simplified the guidelines for the management of blood cholesterol using moderate to high intensity statin therapy, but a recent study showed that its early impact on practice has been modest.³

While traditional methods (e.g., physician-patient encounters) continue to play an important role in the management of hyperlipidemia, alternative approaches are being explored. Many of these approaches (e.g., advanced practice provider clinic visits, media campaigns) can be expensive and are often moderately effective at best. Mobile health, or mHealth, is one alternative approach that is being investigated for its low cost and wide reach.

What is mHealth?

mHealth is defined as the use of mobile phone and wireless technologies to support the achievement of health objectives.⁴ It involves the use of phones, tablets, and other forms of mobile technology to enhance communication between patients and providers. Rapidly advancing mobile technology and its ability to reach more than 85% of the world's population has led to an increase in popularity of mHealth as a tool to improve risk factor control and patient outcomes.⁴ In this article, we evaluate mHealth as an aid in managing hyperlipidemia. A summary of some recent studies is provided in Table 1, while representative studies from the table are discussed below. Given that lifestyle changes and medication adherence are the two most important components in the management of hyperlipidemia, it is no surprise that they have been the focus of most mHealth interventions. Of the interventions employed, email and websites were utilized in earlier studies, whereas short message service (SMS) and mobile applications have been utilized more often in recent studies.⁵

One study that used email was by Dekkers et al. in 2011.⁶ Participants in the intervention group were provided with personalized counselling based on their risk factors. This was in addition to being provided brochures on topics such as overweight, physical activity, and healthy diet. A second intervention group received the same intervention, except that the use of email was replaced with phone calls. The control group received brochures discussed above. The results did not show any significant differences in low density lipoprotein cholesterol (LDL-C) levels between the three groups. LDL-C levels decreased from 5.1 mmol/L (197.2 mg/dL) to 5.0 mmol/L (193.3 mg/dL) in the group receiving emails, from 4.9 mmol/L (189.5 mg/dL) to 4.8 mmol/L (185.6 mg/dL) in the group receiving phone calls and from 4.9 mmol/L (189.5 mg/dL) to 4.9 mmol/L (189.5 mg/dL) in the control group.

The role of SMS as mHealth intervention has varied from study to study. Participants in the intervention group in the study by Blasco et al. underwent a lipid panel check each month and SMS were used by the participants to send results of this testing to a web application. This web application provided access to these test results to a cardiologist who could then make recommendations that were communicated to the participants via SMS.⁷ All participants in the study had at least one cardiac risk factor. The control group continued to receive usual care in the form of routine clinic visits. At 12 months, target LDL-C (<100mg/dL) was reached in 76.2% of participants in the intervention group and 76.6% in the control group (p = 0.94). The TEXT ME (Tobacco, Exercise and Diet Messages) trial, on the other hand, sent each participant in the intervention group four SMS weekly providing advice, motivational reminders, and support to change behaviors.⁸ Participants had documented coronary disease. The control group received usual care. At 6 months, both groups showed a decrease in the LDL-C levels; however, the decrease was greater in the intervention group (from 104 mg/dL to 79mg/dL) compared to the usual care group (from 101 mg/dL to 84 mg/dL, mean difference -5 mg/dL, 95% Confidence Interval [CI]: -9 mg/dL to 0 mg/dL, p = 0.04). The TEXT4HEART (A Text Message and Internet-Based Comprehensive Cardiac Rehabilitation Intervention) trial in New Zealand combined the use of SMS with a website.⁹ This trial, which was conducted over 6 months, enrolled patients with coronary heart disease undergoing cardiac rehabilitation in a mHealth program that included daily SMS in addition to website support to educate patients about their cardiac risk factors and provide support to make relevant lifestyle changes. The control group received usual cardiac rehabilitation. At 6 months, LDL-C levels decreased from 2.7 mmol/L (104.4 mg/dL) to 1.7 mmol/L (65.7 mg/dL) in the intervention group while it decreased from 2.4 mmol/L (92.8 mg/dL) to 1.9 mmol/L (73.8 mg/dL) in the control group; however, the difference in the decrease in LDL between the two groups (adjusted difference: -0.25mmol/L, 95% CI: -0.49mmol/L to 0.01mmol/L [9.7 mg/dL, 95% CI -18.9 mg/dL to 0.39 mg/dL]) reached borderline significance (p = 0.053).

While many studies have evaluated the use of mobile apps to improve hypertension and diabetes management, there have been very few that have evaluated the use of mobile apps for the management of hyperlipidemia. The study by Willey et al. was conducted in the United States in 2016 on 20 patients with no control group.¹⁰ Participants received a nutritional coaching and an exercise health program via a mobile app. At 12 weeks, mean LDL-C levels decreased from 114.6 mg/dL to 105.5 mg/dL (p = 0.11). Maxwell et al. in their recent study used video telehealth technology where clinical pharmacists used video conferencing to communicate with patients at centers where pharmacists were not available.¹¹ The aim was to improve patient knowledge regarding the importance of taking the prescribed medications. At 6 months, mean LDL-C decreased from 76 mg/dL to 70 mg/dL (p = 0.49). There was, however, no control group for comparison.

Based on above, we conclude that there are limited data on the use of mHealth in the management of hyperlipidemia. Studies that have been conducted have often been unable to show significant benefit. This may be explained by the fact that many of these studies have focused on other cardiac risk factors and were not designed to specifically evaluate hyperlipidemia. In addition, the follow-up period has frequently been only a few months. Studies have also not been able to identify which aspect of management—lifestyle modification or medication adherence—is responsible for improvement. Finally, most studies enrolled participants with preexisting CVD. Based on above, there are not enough data to recommend using mobile technology as part of routine clinical practice to aid in management of hyperlipidemia at this time. However, its true potential may lie with specific population subsets such as patients with intentional or unintentional medication non-adherence. Future work needs to explore such avenues with studies that are well designed and based on specific conceptual models to target specific gaps.

Table 1: Studies That Used mHealth Related Interventions for the Management of Hyperlipidemia

Study cited, year of publication, location	Technology used, Number of participants, study duration	Study Groups and their interventions	Findings
Blasco7 2012 Spain	SMS n = 203 Int = 102 Cont = 101 12 months	Int: Participants used SMS to send results of their lipid profiles to a web based application. This was accessed by cardiologist through a web interface who made recommendations based on results. Results were communicated to participants via SMS. Cont: Lifestyle counseling and usual treatment.	Participants achieving goal LDL-C (<100mg/dL) Int: 76.2% Cont: 76.6% (p = 0.94)
Willey10 2016 United States	Mobile App n = 10 Int = 10 No control group 12 weeks	Int: Nutritional and exercise coaching program via mobile app. Cont: No control group	Mean LDL-c Baseline: 114.6 mg/dL 12 weeks: 105.5 mg/dL (p = 0.11)
Maxwell11 2016 United States	Video Telehealth n = 26 Int = 26 No control group 6 months	Int: Pharmacists provided disease management clinical pharmacy services via video telemedicine.	Mean LDL-c Baseline: 76 mg/dL 6 months: 71 mg/dL (p = 0.66)
Text4Heart9 2015 New Zealand	SMS Website n = 123 Int = 61 Cont = 62 24 weeks	Int:  mHealth program that included daily SMS in addition to website support to educate patients about cardiac risk factors and providing support to make relevant lifestyle changes in addition to cardiac rehabilitation Cont: Cardiac rehabilitation	Change in LDL-C at 6 months in mmol/L* Int: From 2.7 to 1.7 Cont: From 2.4 to 1.9 (Adjusted mean difference: -0.25, 95% CI: -0.49 to 0.01, p = 0.053)
Dekkers6 2011 Netherlands	Email Phone Int = 48 Cont = 49 24 months	Int: Self-help materials on overweight, physical activity, and healthy diet via brochures + personal tailored counseling support for modules regarding lifestyle changes via email. Int 2: Self-help materials on overweight, physical activity, and healthy diet via brochures + personal tailored counseling support for modules regarding lifestyle changes via phone calls. Cont: Self-help materials on overweight, physical activity, and healthy diet via brochures.	Change in cholesterol (mmol/L)* Int 1: from 5.1 to 5.0 Int 2: from 4.9 to 4.8 Cont: from 4.9 to 4.9 Mean difference Int 1 vs Cont : -0.0 (95% CI: -0.3 to 0.3) Int 2 vs Cont: -0.1 (-0.4 to 0.2)
TEXTME8 2015 Australia	SMS n = 710 Int = 352 Cont = 358 6 months	Int: 4 text messages per week providing advice, motivational reminders and support to change lifestyle behaviors. Cont: Usual care	Change in mean LDL-c (mg/dL) Int: From 104 to 79 Cont: From 101 to 84 (Mean difference -5, 95% CI: -9 to 0, p = 0.04)

References

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6. Dekkers JC, van Wier MF, Ariens GA, et al. Comparative effectiveness of lifestyle interventions on cardiovascular risk factors among a Dutch overweight working population: a randomized controlled trial. BMC Public Health 2011;11:49.
7. Blasco A, Carmona M, Frenandez-Lozano I, et al. Evaluation of a telemedicine service for the secondary prevention of coronary artery disease. J Cardiopulm Rehabil Prev 2012;32:25-31.
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11. Maxwell LG, McFarland MS, Baker JW, Cassidy RF. Evaluation of the impact of a pharmacist-led telehealth clinic on diabetes-related goals of therapy in a veteran population. Pharmacotherapy 2016;36:348-56.

Keywords: Mobile Applications, Text Messaging, Electronic Mail, Risk Factors, Medication Adherence, Pharmacists, Cholesterol, LDL, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Cardiac Rehabilitation, Diet, Mentors, Telemedicine, Cholesterol, Coronary Artery Disease, Hyperlipidemias, Hypertension, Counseling, Diabetes Mellitus, Primary Prevention, Secondary Prevention

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