Live Counseling Versus Web-Based Lifestyle/Medication Intervention to Reduce CHD Risk

Cardiology Review® Online, August 2014, Volume 30, Issue 4

This interesting study compared the effectiveness of human-led versus website-based counseling to reduce CHD risk.

Alison L. Bailey, MD

Review

Keyserling TC, Sheridan SL, Draeger LB, et al. A comparison of live counseling with a web-based lifestyle and medication intervention to reduce coronary heart disease risk. A randomized clinical trial. JAMA Intern Med. doi:10.1001/jamainternmed.2014.1984.

Coronary heart disease (CHD) is a leading cause of morbidity and mortality worldwide. It is well established that a healthy lifestyle and appropriate medication use can reduce the risk of symptomatic disease and prolong healthy longevity.1,2 Despite this knowledge, the prevalence of ideal cardiovascular health in the population remains unacceptably low.3,4 Efforts at improving these lifestyle metrics have proven challenging, with the results disappointing at best. Developing and implementing effective methods to increase healthy lifestyle behaviors remains an area of intense research in contemporary medicine. Evidence has shown that website-based interventions can be effective in a variety of clinical scenarios, but data are lacking in the CHD prevention arena. The present study aimed to compare the effectiveness of a lifestyle and medication counseling intervention when delivered by a counselor as compared with delivery via Web-based education.5

Study Design

This study was a comparative effectiveness trial designed to assess the effectiveness, acceptability, and cost effectiveness of a previously tested lifestyle and medication counseling intervention to reduce CHD risk in different formats. This intervention was delivered either by a trained health counselor or via a website-based platform, and outcomes were compared between groups.

Established patients with the family medicine clinic aged 35 to 79 years with no known cardiovascular disease (CVD) and at moderate to high risk of CHD as determined by the Framingham Risk Score (FRS) were assessed for inclusion. Initially, the FRS was calculated by chart review using documented age, blood pressure, total cholesterol level, high-density lipoprotein (HDL) cholesterol level, presence of diabetes, smoking, aspirin use, and left ventricular hypertrophy. Diabetes was included in the FRS and was not considered a CVD equivalent. A primary care physician then evaluated individuals with a 10-year FRS of ≥10% and a final determination was made for eligibility based on inclusion and exclusion criteria. Eligible participants were then formally assessed at an enrollment visit for potential bleeding risk with aspirin as well as confirmation of chart data and assessment of blood samples. The FRS was recalculated, and if it remained ≥10%, the baseline phone survey was completed. The individual was then invited to the first intervention visit, where randomization to counselor or the website-based platform occurred.

The intervention began as a website-based decision aid for both groups followed by the counseling program. The decision aid calculated the participants’ 10-year FRS and educated the participants about their individual CHD risk factors as well as pros and cons of risk-reducing strategies. It showed the participant how their CHD risk might be reduced by changes in diet, increased physical activity, smoking cessation, initiation of aspirin (men only), or initiation and/or intensification of treatment with statins or antihypertensive medications. Participants chose the risk-reducing strategies they wished to focus on during the program. Counseling was tailored to the individual’s risk factors and management choices and was the same whether delivered by a counselor or through a website-based intervention. Both counseling formats spanned a year and included an initial 4 sessions of about an hour each month during the intensive phase, followed by 3 sessions of about 30 minutes every 2 months during the maintenance phase. The educational content was identical in both formats and focused on:

· Improving carbohydrate and fat quality;

· Walking 7500 steps or 30 minutes on 5 days each week; and

· Understanding medication instructions, planning ahead for refills, and partnering with the clinician to make good decisions about medications to reduce CHD risk.

A variety of laboratory markers as well as anthropometric data were assessed at baseline, 4 months, and 12 months. Validated instruments for numeracy, literacy, and medication adherence were assessed at baseline. Throughout the intervention, investigators assessed:

· Medication use

· Fruit and vegetable intake

· Dietary fat quality

· Physical activity

· Quality of life, and

· Acceptability of the intervention.

Of the 2274 patients eligible for screening, 633 agreed to participate in the study. After further evaluation, 385 individuals were enrolled. The group had a mean age of 62 years, and the majority (88%) of participants had insurance. A total of 48% of enrollees were female, and 24% were African American. Overall, the group had a high cardiac risk, with most members having hypertension (86%), high cholesterol (85%), or diabetes (61%). The group’s mean 10-year FRS was 16.9%. Most participants elected to work on improving diet (95%) and increasing physical activity (66%). Follow-up rates at 4 and 12 months were 91% and 87%, respectively.

The primary outcome analysis was conducted using an intention-to-treat approach with a paired t test (1-sided) for changes in FRS within each intervention arm. Secondary outcomes were examined using paired t tests or McNemar tests for within-group comparisons (2-sided tests). Cost-effectiveness was assessed using the incremental cost-effectiveness ratio (ICER).

There was a statistically significant reduction in the primary outcome of 10-year FRS at 4 months and 12 months in both intervention groups. For the counselor group, the change was —2.3% (4 months) and –1.9% (12 months) while the website-based group saw changes of –1.5% (4 months) and –1.7% (12 months). Changes in other risk factors are summarized in the Table. After assessing by longitudinal analysis, there was no significant time-by-group interaction (P = .27), and within- and between-group comparisons were similar at each time point, suggesting no significant difference in the counseling delivery method. The costs of delivering the program from the payer perspective were about $207 for the counselor intervention and $110 for the website-based intervention (P <.001). The ICER for the website-based intervention was $73 per percentage-point reduction in CHD risk and $2973 per quality-adjusted life-year gained (highly cost effective).

Overall, the intervention was successful in both groups, as all components of the FRS improved as well as diet and physical activity metrics, with no adverse effects, and the changes were maintained from 4- to 12-month follow up. Both methods of counseling were well received, with the majority of participants indicating they would recommend the program to others and considered it cost-effective.

Commentary

Innovative strategies beyond personal counseling improve cardiovascular health

Cardiovascular risk can be assessed in a variety of ways, with the most common calculators compiling easily measured risk factors.5 There are strong epidemiological data correlating a reduction in CVD risk factors to a reduction in CVD event rates over the lifespan, and forms the basis for many of the recommendations for improving cardiovascular health.1,2 Despite this common knowledge, we have been unsuccessful in the United States in positively improving health through lifestyle. In the most recent update from the American Heart Association, 0.1% of adults and virtually no children meet all 7 metrics for ideal cardiovascular health.4 New methods of achieving improved cardiovascular health metrics must be found.

This study is intriguing because of the improvements in lifestyle attributes that were achieved. Objectively measured variables of BP, cholesterol and cholesterol subfractions, glycated hemoglobin, and weight all improved, with most metrics meeting statistical significance and the others trending in the direction of improvement. There were increases in fruit and vegetable consumption and exercise time as well as reductions in smoking rates that were preserved at 1 year. A significant improvement in FRS, the primary outcome of interest, was achieved. Over the long term, this should equate to reductions in event rates and, presumably, mortality. On a population level, this could have significant implications both in longevity of the population and health care costs.

The population studied was diverse and included a range of ages and varying socioeconomic status levels, education levels, and comfort with computers. Of all of the subgroups evaluated, the intervention appeared more effective in younger participants. Whether this is related to technology or some other unmeasured variable, it deserves consideration. Currently, we deliver risk reduction information the same way to all patients without considering learning style or other attributes that may optimize education. Perhaps effective lifestyle change strategies are more effective when based on individual characteristics—of which age may be very important. “Personalized medicine” is a popular term generally reserved for treatment based on genetics, but should be considered in the prevention realm. Personalized medicine in the prevention realm may well include assessment for preference of learning style as well as other skills traditionally reserved for the education community.

There were several study limitations that deserve mention. This trial did not have a classic “control” group to compare with the intervention groups. However, prior data indicate that the intervention is effective at lowering FRS compared with standard of care.7 Additionally, many of the outcomes of interest were measured by self-report. However, this is an inherent problem with any lifestyle intervention, and biomarker confirmation of the self-report was used when available (eg, to assess tobacco use, fruit/vegetable consumption, and aspirin use).

In conclusion, this trial shows us that there are innovative strategies to improve cardiovascular health variables beyond personally delivered counseling. We must continue to explore new options for motivating individuals to make sustainable change, and technology will surely play a role.

References

1. Lloyd-Jones DM, Hony Y, Labarthe D, et al. Defining and setting national goals for cardiovascular health promotion and disease reduction: the American Heart Association's strategic Impact Goal through 2020 and beyond. Circulation. 2010;121:586-613.

2. Dong C, Rundek T, Wright CB, Anwar Z, Elkind MS, Sacco RL.Ideal cardiovascular health predicts lower risks of myocardial infarction, stroke, and vascular death across whites, blacks, and hispanics: the northern Manhattan study. Circulation. 2012;125:2975-2984.

3. Bambs C, Kip KE, Dinga A, Mulukutla SR,Aiyer AN,Reis SE.Low prevalence of "ideal cardiovascular health" in a community-based population: the heart strategies concentrating on risk evaluation (Heart SCORE) study. Circulation. 2011;123:850-857.

4. Go AS, Mozaffarian D, Roger VL, et al. Heart disease and stroke statistics—2014 update: a report from the American Heart Association. Circulation. 2014;129:e28—e292.

5. Keyserling TC, Sheridan SL, Draeger LB, et al. A comparison of live counseling with a web-based lifestyle and medication intervention to reduce coronary heart disease risk: a randomized clinical trial. JAMA Intern Med. doi:10.1001/jamainternmed.2014.1984

6. Stone NJ, Robinson J, Lichtenstein AH, et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2013.

7. Sheridan SL, Draeger LB, Pignone MP, et al. Designing and implementing a comparative effectiveness study of two strategies for delivering high quality CHD prevention: methods and participant characteristics for the Heart to Health study. Contemp Clin Trials. 2013;36:394-405.

About the Author

Alison L. Bailey, MD, is associate professor of medicine and director of ambulatory cardiology, prevention and rehabilitation at the Gill Heart Institute, Division of Cardiovascular Medicine, at the University of Kentucky in Lexington. Dr Bailey received her MD from the University of Kentucky College of Medicine and completed her residency and fellowship at University of Kentucky Chandler Hospital. Her clinical interests include cardiovascular disease in women and cardiovascular disease prevention. Dr Bailey has been published in numerous peer-reviewed medical journals.