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Two Self-management Interventions to Improve Hypertension Control: A Randomized Trial FREE

Hayden B. Bosworth, PhD; Maren K. Olsen, PhD; Janet M. Grubber, MSPH; Alice M. Neary, RN; Melinda M. Orr, MEd; Benjamin J. Powers, MD; Martha B. Adams, MD; Laura P. Svetkey, MD; Shelby D. Reed, PhD; Yanhong Li, MS; Rowena J. Dolor, MD, MHS; and Eugene Z. Oddone, MD, MHS
[+] Article and Author Information

From the Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Center for Aging and Human Development, Duke Hypertension Center, and Duke Clinical Research Institute, Duke University, Durham, North Carolina.


Disclaimer: The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs.

Grant Support: By grant R01 HL070713 from the National Heart, Lung, and Blood Institute; a Pfizer Foundation Health Communication Initiative Award; and an Established Investigator Award from the American Heart Association (Dr. Bosworth).

Potential Conflicts of Interest: None disclosed.

Reproducible Research Statement:Study protocol and data set: Available from Dr. Bosworth (e-mail, hayden.bosworth@duke.edu). Statistical code: Available from Dr. Olsen (e-mail, maren.olsen@duke.edu).

Requests for Single Reprints: Hayden B. Bosworth, PhD, Center for Health Services Research in Primary Care, Duke University, 2424 Erwin Road, Hock Plaza, Durham, NC 27703; e-mail, hayden.bosworth@duke.edu.

Current Author Addresses: Drs. Bosworth and Powers and Ms. Neary: Center for Health Services Research in Primary Care, Duke University, 2424 Erwin Road, Hock Plaza, Durham, NC 27703.

Drs. Olsen and Oddone, Ms. Grubber, and Ms. Orr: Durham Veterans Affairs Medical Center (152), 508 Fulton Street, Durham, NC 27705.

Dr. Adams: Duke University Medical Center, Box 3230, Durham, NC 27710.

Dr. Svetkey: Duke Hypertension Center, Sarah W. Stedman Nutrition and Metabolism Center, 3475 Erwin Road, Suite 100, Durham, NC 27705.

Drs. Reed and Dolor and Ms. Li: Duke Clinical Research Institute, 2400 Pratt Street, Room 311, Durham, NC 27705.

Author Contributions: Conception and design: H.B. Bosworth, M.K. Olsen, M.M. Orr, M.B. Adams, L.P. Svetkey, E.Z. Oddone.

Analysis and interpretation of the data: H.B. Bosworth, M.K. Olsen, J.M. Grubber, L.P. Svetkey, S.D. Reed, Y. Li, E.Z. Oddone.

Drafting of the article: H.B. Bosworth, M.K. Olsen, J.M. Grubber, A.M. Neary, M.M. Orr, E.Z. Oddone.

Critical revision of the article for important intellectual content: H.B. Bosworth, M.K. Olsen, A.M. Neary, B.J. Powers, M.B. Adams, L.P. Svetkey, S.D. Reed, R.J. Dolor, E.Z. Oddone.

Final approval of the article: H.B. Bosworth, M.K. Olsen, M.M. Orr, L.P. Svetkey, S.D. Reed, Y. Li, R.J. Dolor, E.Z. Oddone.

Provision of study materials or patients: A.M. Neary, B.J. Powers, L.P. Svetkey.

Statistical expertise: H.B. Bosworth, M.K. Olsen, J.M. Grubber, Y. Li.

Obtaining of funding: H.B. Bosworth, M.K. Olsen, E.Z. Oddone.

Administrative, technical, or logistic support: H.B. Bosworth, M.M. Orr, M.B. Adams, R.J. Dolor, E.Z. Oddone.

Collection and assembly of data: J.M. Grubber, A.M. Neary, M.M. Orr, Y. Li.


Ann Intern Med. 2009;151(10):687-695. doi:10.7326/0000605-200911170-00148
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Background: Fewer than 40% of persons with hypertension in the United States have adequate blood pressure (BP) control.

Objective: To compare 2 self-management interventions for improving BP control among hypertensive patients.

Design: A 2 × 2 randomized trial, stratified by enrollment site and patient health literacy status, with 2-year follow-up. (ClinicalTrials.gov registration number: NCT00123058)

Setting: 2 university-affiliated primary care clinics.

Patients: 636 hypertensive patients.

Intervention: A centralized, blinded, and stratified randomization algorithm was used to randomly assign eligible patients to receive usual care, a behavioral intervention (bimonthly tailored, nurse-administered telephone intervention targeting hypertension-related behaviors), home BP monitoring 3 times weekly, or the behavioral intervention plus home BP monitoring.

Measurements: The primary outcome was BP control at 6-month intervals over 24 months.

Results: 475 patients (75%) completed the 24-month BP follow-up. At 24 months, improvements in the proportion of patients with BP control relative to the usual care group were 4.3% (95% CI, −4.5% to 12.9%) in the behavioral intervention group, 7.6% (CI, −1.9% to 17.0%) in the home BP monitoring group, and 11.0% (CI, 1.9%, 19.8%) in the combined intervention group. Relative to usual care, the 24-month difference in systolic BP was 0.6 mm Hg (CI, −2.2 to 3.4 mm Hg) for the behavioral intervention group, −0.6 mm Hg (CI, −3.6 to 2.3 mm Hg) for the BP monitoring group, and −3.9 mm Hg (CI, −6.9 to −0.9 mm Hg) for the combined intervention group; patterns were similar for diastolic BP.

Limitation: Changes in medication use and diet were monitored only in intervention participants; 24-month outcome data were missing for 25% of participants, BP control was adequate at baseline in 73% of participants, and the study setting was an academic health center.

Conclusion: Combined home BP monitoring and tailored behavioral telephone intervention improved BP control, systolic BP, and diastolic BP at 24 months relative to usual care.

Primary Funding Source: National Heart, Lung, and Blood Institute; Pfizer Foundation Health Communication Initiative; and the American Heart Association.

Editors' Notes
Context

  • Can self-management interventions help improve blood pressure control in hypertensive patients?

Contribution

  • In this trial, 636 patients with hypertension were randomly assigned to receive usual care; a telephone-delivered, nurse-administered behavioral self-management intervention; home blood pressure self-monitoring; or both of the latter 2 interventions. Compared with usual care, the adjusted improvement in the proportion of patients with blood pressure control at 24 months was 4.3% for the behavioral intervention group, 7.6% for the blood pressure monitoring group, and 11.0% for the combined intervention group.

Caution

  • Patients were recruited from 2 university-affiliated clinics, and most (73%) already had reasonable blood pressure control at trial entry.

—The Editors

Although multiple treatment options are available for hypertension, only one third of U.S. patients with hypertension have their blood pressure (BP) under effective control (1). Home BP monitoring is a potentially important aspect of successful hypertension management (2). Adopting a healthy lifestyle and adhering to provider recommendations are also important in managing hypertension. Few educational and BP monitoring studies have provided long-term follow-up (>12 months) or implemented a multidimensional intervention that is tailored to patients' needs and delivered by telephone (3). A tailored telephone behavioral intervention and home BP monitoring may be a cost-effective method for improving BP outcomes (4).

We compared the effectiveness of BP self-monitoring, a tailored, nurse-administered behavior self-management intervention, and a combination of the 2 interventions with that of usual care.

The study was approved by the Duke University Institutional Review Board, and all patients provided written informed consent.

Setting and Participants

Recruitment occurred from May 2004 to December 2005, with follow-up from November 2004 to January 2008. Potentially eligible study patients were identified through weekly data extractions from the billing and appointment database for 2 Duke University Health System primary care clinics. Patients were cared for by 7 faculty general internists in 1 clinic and 85 residents under the supervision of faculty at the other clinic.

Initial inclusion criteria were hypertension diagnosed at least 12 months before the data extraction date (International Classification of Diseases, 9th revision, codes 401.0, 401.1, or 401.9), enrollment with a primary care physician at the included clinic for at least 12 months before data extraction, self-report of current antihypertensive medication use, a scheduled appointment with a nonlaboratory primary care provider during the next 30 days, and residence in 1 of 32 specified ZIP codes in the areas around Duke University Health System.

Exclusion criteria applied before randomization were a diagnosis of dementia, Parkinson disease, atrial fibrillation, or end-stage renal disease; patient of a study investigator or physician not expected to remain at the practice during the entire study period; resident in nursing home or receiving home health care; hospitalization for stroke or heart attack, surgery for blocked arteries, or diagnosis of metastatic cancer in the previous 3 months; poor vision or difficulty hearing on the telephone; difficulty understanding English on the telephone; participant in another BP study; spouse participating in current study; arm circumference greater than 17 inches and wrist circumference greater than 8.5 inches; pregnant or planning to become pregnant in the next 2 years; or not receiving most medical care from Duke clinics. Patients also were excluded after randomization because they were no longer receiving medical care at the Duke clinics, had initiated dialysis, had received an organ transplant in the previous 6 months, resided in a nursing home or receiving home health care, had no telephone, or received a diagnosis of pulmonary hypertension in the previous 6 months.

The study team mailed qualifying patients a letter from the patient's primary care provider that gave information about the study and stated that the study team may contact them to participate. Research assistants made weekly screening telephone calls to patients from a randomly ordered list of eligible patients with upcoming clinic appointments.

Figure 1 shows the flow of participants in the study. Overall, 2060 invitation letters were mailed to patients. Research assistants attempted to contact 1728 potential participants by telephone. Six hundred fifty-six patients were enrolled and consented to participate; the remaining 1072 were not enrolled for various reasons. Twenty additional patients were excluded at the time of the baseline interview.

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Figure 1.
Study flow diagram.

BP = blood pressure.

* No longer receiving care at Duke clinics, receiving dialysis, received an organ transplant, residing in a nursing home or receiving home health care, had no telephone, or had pulmonary hypertension.

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Randomization and Intervention

The 636 eligible patients were randomly assigned to receive usual care, a tailored behavioral telephone intervention, home BP monitoring, or the behavioral intervention plus BP monitoring. In a 2 × 2 design, randomization was stratified at baseline by enrollment site (2 primary care clinics) and health literacy status, as determined by using the Rapid Estimate of Adult Literacy in Medicine (5) (low literacy, score of 0 to 60 [9th-grade level or less] [6], vs. adequate literacy, score of 61 to 66 [greater than 9th-grade level] [7]). Consecutively numbered envelopes were used to randomly assign patients in each stratum. Randomization blocks of 16 were computer generated by the study statistician and used to ensure ongoing balanced enrollment across the 4 groups. The research assistants were blinded to block size, and patient randomization sequences were maintained by the study statistician in a separate office from the clinics. At completion of the baseline interview, a research assistant opened an envelope and disclosed the patient's randomization status. Participants were reimbursed $25 for the baseline visit and for each of the 4 subsequent 6-month BP measurement visits ($125 total).

Usual Care

Patients assigned to usual care received hypertension care from their primary care provider. They were not provided home BP monitors and did not have access to the nurse-administered behavioral intervention. They underwent the same 6-month outcome assessment measurements as the other groups.

Tailored Behavioral Self-management Intervention

Patient factors targeted in the behavioral intervention included perceived risk for hypertension, memory, literacy, social support, patients' relationships with their health care providers, and side effects of antihypertension medication. In addition, the intervention focused on improving adherence to the Dietary Approaches to Stop Hypertension (DASH) dietary pattern (811), weight loss (1213), reduced sodium intake (1314), regular moderate-intensity physical activity (1516), smoking cessation, and moderation of alcohol intake (17).

The intervention was delivered by 1 nurse during bimonthly telephone calls. All information was presented in an easily understood format with a Flesch–Kincaid readability score of less than 9th grade (18). Each encounter included a core group of modules potentially implemented during each call (for example, medication and side effects) plus additional modules activated at specific intervals (for example, diet and social support) (19).

Home BP Monitoring Intervention

Patients assigned to home BP monitoring received an Omron HEM 773AC arm monitor (OMRON Healthcare, Bannockburn, Illinois) if arm circumference was 17 inches or less or an Omron HEM 637 wrist monitor if arm circumference was greater than 17 inches and wrist circumference was less than 8.5 inches. Two research assistants trained patients in proper use of the home BP devices. At each 6-month assessment, patients were retrained if their BP assessment procedure was incorrect. Patients were asked to measure their BP 3 times weekly on 3 separate days, at the same time of day, and record their values in a log. Patients were asked to mail their logs in every 2 months by using study-provided, preaddressed, stamped envelopes.

Combined Intervention

Patients assigned to the combined intervention received a home BP monitor, training on its use, and the behavioral self-management intervention. The nurse did not examine home BP values and did not use the home BP values to adjust the intervention.

Outcomes and Measurements
Baseline Measurement

Patient demographic information and diagnosis of diabetes were obtained from patients during a face-to-face baseline interview. Inadequate income was assessed by asking patients to report whether they had enough money to pay bills only by cutting back on things or had difficulty paying bills (20). Health literacy was evaluated as a dichotomous variable (7). Body weight abstracted from the medical record and self-reported height were used to calculate body mass index.

Study Outcomes: BP Control and Systolic and Diastolic BP

The primary outcome was the proportion of participants with adequate BP control at each study time point (baseline and 6, 12, 18, and 24 months). Blood pressure control was defined as systolic BP less than 140 mm Hg and diastolic BP less than 90 mm Hg for patients without diabetes, and systolic BP less than 130 mm Hg and diastolic BP less than 80 mm Hg for patients with diabetes (21). Secondary outcomes were systolic and diastolic BP at each time point over 24 months. At each time point, a research assistant who was blinded to the patient's group assignment obtained 2 BP measurements with a digital sphygmomanometer (BPTRU Automated Non-invasive BP monitor, Model BPM-100, BpTRU Medical Devices Headquarters, Coquitlam, British Columbia, Canada); the first was obtained after patients were seated and had rested for at least 5 minutes, and the second was obtained 30 seconds after the first. The mean of the 2 values was used as the outcome for that time point.

We collected data on secondary outcomes, including hypertension knowledge and self-efficacy; however, these results are not reported here.

Health Care Utilization and Cost

Electronic data on medical resource use in the Duke University Health System were obtained for all enrolled patients from randomization through 24 months. These data included the cost estimates for all health care services.

The cost of each patient intervention encounter was based on an estimate of annual fixed costs (for example, office space and telephone) and the nurse's salary and assumed that 7 encounters were completed per 6-hour day. This estimate was assigned to each completed patient encounter. Our cost estimates also included variable costs, which covered a relatively small amount for patient education materials (for example, paper and toner). Variable costs for home BP monitoring costs included the cost of the BP monitor and batteries.

Follow-up Procedures and Monitoring

We did not anticipate any specific adverse effects of the intervention. We monitored for cardiovascular adverse events, such as myocardial infarction, death, and hospitalizations, through medical record and patient report. A data safety and monitoring board met annually to review all adverse events.

Statistical Analysis

Sample size estimation was based on the primary hypothesis that patients assigned to an intervention group would have improved BP control at 24 months compared with the usual care group. A linear change in BP control was assumed, so the comparison was a difference in slopes (the treatment-by-time interaction in a logistic mixed-effects regression model [22]). Sample size and power estimates were generated empirically in a simulation study by using PROC NLMIXED in SAS, version 9.1 (SAS Institute, Cary, North Carolina). On the basis of previous studies (2324), we estimated baseline BP control as 40% and the 24-month dropout rate as 15%. The random intercept variance component was assumed to be 0.7 (equivalent to a patient interclass correlation of 0.18) (22). To detect a difference in slopes resulting in 10% improvement in BP control at 24 months with 80% power and a type I error rate of 5%, 570 patients were needed; however, to account for dropout, we enrolled 636 individuals.

Primary Analysis

A logistic mixed-effects regression model (22) was used to estimate change in BP control over time for each intervention group relative to usual care (that is, a difference in slopes). Observed means and exploratory analyses indicated that, on average, BP control improved in a linear trend over time and there were equal correlations between patients' repeated measurements. The fixed effects for the model were coded to reflect the 2 × 2 factorial design and included a common intercept (25), the 2 stratification variables, time (in months), and the following interaction terms: behavioral intervention by month, home BP monitoring by month, and behavioral intervention by home BP monitoring by month. A random effect was included to account for the correlation of patients' repeated measurements over time. Estimates for the proportion of patients with BP control for each intervention group and the usual care group at 12 and 24 months were converted to marginalized probabilities (22). One thousand bootstrap samples were used to derive CIs around the estimated differences of the marginalized probabilities between each intervention group and the usual care group at 12 and 24 months (26).

Secondary Analyses

For systolic and diastolic BPs, general linear models (PROC MIXED in SAS, version 9.1) were used to estimate changes in BP over time and to test for BP differences in the intervention groups relative to usual care at 12 and 24 months. Exploratory analyses indicated that both systolic and diastolic BPs had quadratic shapes in which improvements in BPs were greatest during the first half of the study. Predictors in the model were coded to reflect the 2 × 2 factorial design. The final model included a common intercept, the 2 stratification variables, and the following interaction terms: behavioral intervention by month, home BP monitoring by month, behavioral intervention by home BP monitoring by month, behavorial intervention by month squared, home BP monitoring by month squared, and behavioral intervention by home monitoring by month squared.

Patients were analyzed on the basis of initial randomization group (intention to treat); 634 patients were included in the analyses (Figure 1). All available data, including data from participants who subsequently discontinued the study, were used for analyses. Our analysis techniques assumed ignorable dropout, meaning that the probability of dropout may depend on covariates in the model or participants' previous responses but not on current or future responses (22).

Role of the Funding Source

The study was funded by the National Heart, Lung, and Blood Institute; a Pfizer Foundation Health Communication Initiative Award; and an Established Investigator Award from the American Heart Association to Dr. Bosworth. The funding sources had no role in the study design; data collection; administration of the interventions; analysis, interpretation, or reporting of data; or decision to submit the findings for publication.

Patients

Of the 636 study patients, 49% were African American, 66% were female, and 19% reported having inadequate income; the mean age was 61 years (Table 1). At baseline, mean systolic BP was 125 mm Hg (SD, 18) and mean diastolic BP was 71 mm Hg (SD, 11). Seventy-three percent of participants had their BP under control at baseline. Baseline characteristics did not differ meaningfully by treatment group.

Table Jump PlaceholderTable 1.  Patient Characteristics at Baseline

The 1424 persons who were excluded before random allocation were similar to study participants in sex (64% female) and diagnosis of diabetes but were slightly older (mean age, 63 years) and were more likely to be African American (57%). No crossover among study groups occurred; however, individuals not assigned to the home BP intervention groups may have used their own BP monitors. No study-related adverse events occurred in any intervention group.

Overall, BP measurements were available for 475 (75%) patients at 24 months of follow-up (Figure 1): 81%, 78%, 72%, and 69% of patients in the usual care, behavioral intervention, home BP monitoring, and combined intervention groups, respectively (P = 0.075). Sixty-three percent of patients with lower health literacy and 79% of those with higher health literacy (P < 0.001) and 57% of patients at one of the clinics versus 82% at the other clinic (P < 0.001) had BP readings at 24 months.

Primary Outcome: BP Control

The combined intervention had the greatest increase in the proportion of patients with BP control (Figure 2). At 24 months, the adjusted improvement compared with usual care was 11.0% (95% CI, 1.9% to 19.8%; P = 0.012) for the combined intervention group, 4.3% (CI, −4.5% to 12.9%; P = 0.34) in the behavioral intervention group, and 7.6% (CI, −1.9% to 17.0%; P = 0.096) for the home BP monitoring group. The 3-way interaction of behavioral intervention by home BP monitoring by month was not significant (P = 0.99), indicating that the 2 interventions did not have a synergistic effect on BP control over time.

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Figure 2.
Changes in study outcomes from baseline to 24 months, by intervention group.

Bars represent 95% CIs. BP = blood pressure. Top. Estimated proportion of patients with BP control. Estimates are marginalized probabilities from a logistic mixed-effects regression model (22). The model-estimated intrapatient correlation was 0.56. The 95% CIs at 12 and 24 months were derived from 1000 bootstrap samples. Middle. Estimated mean systolic BP. Estimates are based on a general linear model with an unstructured covariance matrix. The model-estimated correlation between time points ranged from 0.41 (baseline and 24 months) to 0.58 (months 6 and 12). Bottom. Estimated mean diastolic BP. Estimates are based on a general linear model with an unstructured covariance matrix. The model-estimated correlation between time points ranged from 0.54 (baseline and 24 months) to 0.66 (baseline and 6 months).

Grahic Jump Location
Secondary Outcomes
Systolic and Diastolic BP

The largest sustained improvement for systolic and diastolic BP was observed in the combined intervention group (Figure 2). The 3-way interaction of behavioral intervention by home monitoring by month squared was significant (P = 0.041 for the systolic BP model; P = 0.004 for the diastolic BP model), indicating that the main effects of home BP monitoring and the behavioral interventions on BP over time enhanced one another (Table 2).

Table Jump PlaceholderTable 2.  Changes in BP Control and Systolic and Diastolic BP at 12 and 24 Months

Figure 2 shows the changes in BP over time. At 12 months, the mean systolic BP was lower by 1.6 mm Hg (CI, −3.9 to 0.7 mm Hg; P = 0.174) in the behavioral intervention group, 3.7 mm Hg (CI, −6.1 to −1.2 mm Hg; P = 0.004) in the home BP monitoring group, and 3.3 mm Hg (CI, −5.7 to −0.8 mm Hg; P = 0.009) in the combined intervention group than the usual care group. However, by 24 months, the mean systolic BP was statistically significantly lower only in the combined intervention group than in the usual care group, indicating the synergistic effect of the 2 interventions on improving BP over time. Compared with the usual care group, the adjusted 24-month difference in systolic BP was 0.6 mm Hg (CI, −2.2 to 3.4 mm Hg; P = 0.67) in the behavioral intervention group, −0.6 mm Hg (CI, −3.6 to 2.3 mm Hg; P = 0.69) in the home BP monitoring group, and −3.9 mm Hg (CI, −6.9 to −0.9 mm Hg; P = 0.010) in the combined intervention group.

Compared with the usual care group at 12 months, the mean diastolic BP was lower by 1.4 mm Hg (CI, −2.6 to −0.1 mm Hg; P = 0.030) in the behavioral intervention group, 3.1 mm Hg (CI, −4.4 to −1.8 mm Hg; P < 0.001) in the home BP monitoring group, and 2.2 mm Hg (CI, −3.5 to −0.8 mm Hg; P = 0.001) in the combined intervention group (Figure 2). Similarly to systolic BP, the synergistic effect of the combined intervention on diastolic BP was evident by the end of follow-up. Compared with that in the usual care group, the adjusted 24-month difference in diastolic BP was 0.4 mm Hg (CI, −1.1 to 1.9 mm Hg; P = 0.61) in the behavioral intervention group, −1.2 mm Hg (CI, −2.9 to 0.4 mm Hg; P = 0.132) in the home BP monitoring group, and −2.2 mm Hg (CI, −3.8 to −0.6 mm Hg; P = 0.009) in the combined intervention group.

Adherence

Behavioral Self-management Intervention. The nurse completed 1682 telephone calls to the 160 patients assigned to the behavioral intervention. The mean number of completed calls per patient was 11 (SD, 2) of a possible 12, and the mean call length was 16 minutes (SD, 7).

Home BP Monitoring. Of the 158 patients assigned to the home BP monitoring intervention, 91% of patients in the first 2 months of the study and 64% of patients in the last 2 months turned in BP logs with at least 1 recorded BP reading. The percentage of patients who turned in their logs was higher among patients who completed the study.

Combined Intervention. Of the 159 patients assigned to the combined intervention group, 89% and 59% turned in BP logs with at least 1 recorded BP reading for the first and last 2 months of the study, respectively; these proportions were 99% and 81%, respectively, for the 110 patients with a BP measurement at 24 months. Nurses completed 1589 telephone calls to 156 patients; the mean number of completed calls per patient was 10 (SD, 3) of a possible 12, and the mean call length was 16 minutes (SD, 7).

Medical Resource Use and Costs

The number of outpatient encounters over 24 months was similar for the 4 groups; medians ranged from 13 to 15 (P = 0.73). The proportion of hospitalized individuals did not differ (range, 19.5% to 22.6%; P = 0.91). The mean 2-year medical cost across the groups was $15 641 (SD, $25 769; median, $6698).

Intervention Cost Analysis

Intervention costs over 2 years were estimated to be $345 for the behavioral intervention, $90 for home BP monitoring, and $416 for the combined intervention (not including patient time costs). In sensitivity analyses, the mean cost to implement the combined intervention ranged from $208 to $811 per patient, depending on assumptions regarding the mean time between successful encounters and various direct costs of implementing the intervention.

Additional Analyses

We examined self-reported medication adherence and exercise at 6 and 24 months of follows-up; however, although there were trends indicating improvement over time, changes in the intervention groups compared with the usual care group were not generally statistically significant.

We examined the effects of a patient behavioral intervention delivered by telephone, home BP monitoring, and a combination of these interventions in improving BP among hypertensive adults treated in primary care. Neither intervention alone improved BP control at 24 months; however, the combination intervention resulted in a clinically significant improvement in BP control of 11% compared with usual care. Patients in the combined intervention group also had a clinically meaningful decrease in systolic BP of 3.9 mm Hg compared with the usual care group. These effects were observed with a brief telephone intervention that was implemented bimonthly and the use of home BP monitors, which required minimal patient training (<5 minutes every 6 months).

Home BP monitoring alone has been well studied as a method to improve BP control. Its main effect is thought to be on BP recognition, which may lead to improved adherence and better control. Our results regarding home BP monitoring are consistent with those of a meta-analysis of 18 randomized, controlled trials that compared home BP monitoring with usual care and found that home BP monitoring resulted in small improvements in BP (reduction of 2.2/1.9 mm Hg) (27). A decrease in BP may encourage the patient to continue treatment, whereas continued high BP readings may encourage appropriate changes in lifestyle or therapy (28) and faster changes to medical regimens (29).

A literature search through June 2009 using the terms self-management and behavior intervention yielded 7 randomized, controlled trials. These trials reported mean differences in systolic BP ranging from −15.7 to 0.6 mm Hg (30) and had an average follow-up of less than 12 months. However, the trials involved in-person contact, which potentially reduces scalability and increases intervention costs. In a review of 10 studies testing mostly in-person behavioral interventions, results favored counseling over usual care, with improvements of 11.1 mm Hg in systolic BP and 3.5 mm Hg in diastolic BP (31). Few studies have implemented a multidimensional intervention that is tailored to patients' needs and delivered by telephone, yet based in primary care practices. Furthermore, few studies have examined changes in BP for longer than 12 months, which was particularly relevant in our study; the effects of using home BP monitors at 12 months indicated an almost 4–mm Hg decrease in systolic BP, but these findings dissipated by 24 months for all but the combined intervention group. The combined intervention did not increase health care use, and its cost was approximately $400 for 2 years.

The patient self-management intervention was effective only when combined with home BP monitoring. One proposed explanation is that self-management may be most effective when it includes ongoing disease monitoring by patients that creates the opportunity to respond to new information (32).

Our study had limitations, 2 of which were the high rate of BP control (73%) in the study population at baseline and the academic health center setting. The relationship between BP and cardiovascular risk is continuous, and BP reductions translate to reductions in clinical events, even with observed relatively low baseline BP (21). Changes in process measures, such as medication use and salt intake during the trial, were measured only in the intervention groups. Finally, 25% of the sample was not available at 24 months; however, we used mixed-effects models as our primary analysis tool, which includes all patients with any BP measurements and leads to valid inferences.

In conclusion, the combination of home BP monitoring and a tailored brief behavioral intervention resulted in a clinically and statistically significant improvement in BP control and decreased systolic and diastolic BPs at 24 months, at minimal cost. This combination may be a valuable tool for improving BP control rates.

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Svetkey LP, Sacks FM, Obarzanek E, Vollmer WM, Appel LJ, Lin PH. et al.  The DASH Diet, Sodium Intake and Blood Pressure Trial (DASH-sodium): rationale and design. DASH-Sodium Collaborative Research Group. J Am Diet Assoc. 1999; 99:S96-104. PubMed
 
Svetkey LP, Simons-Morton D, Vollmer WM, Appel LJ, Conlin PR, Ryan DH. et al.  Effects of dietary patterns on blood pressure: subgroup analysis of the Dietary Approaches to Stop Hypertension (DASH) randomized clinical trial. Arch Intern Med. 1999; 159:285-93. PubMed
 
Neter JE, Stam BE, Kok FJ, Grobbee DE, Geleijnse JM.  Influence of weight reduction on blood pressure: a meta-analysis of randomized controlled trials. Hypertension. 2003; 42:878-84. PubMed
 
.  The effects of nonpharmacologic interventions on blood pressure of persons with high normal levels. Results of the Trials of Hypertension Prevention, Phase I. JAMA. 1992; 267:1213-20. PubMed
 
Cutler JA.  Randomized clinical trials of weight reduction in nonhypertensive persons. Ann Epidemiol. 1991; 1:363-70. PubMed
 
Kelley GA, Kelley KS.  Progressive resistance exercise and resting blood pressure: A meta-analysis of randomized controlled trials. Hypertension. 2000; 35:838-43. PubMed
 
Whelton SP, Chin A, Xin X, He J.  Effect of aerobic exercise on blood pressure: a meta-analysis of randomized, controlled trials. Ann Intern Med. 2002; 136:493-503. PubMed
 
Xin X, He J, Frontini MG, Ogden LG, Motsamai OI, Whelton PK.  Effects of alcohol reduction on blood pressure: a meta-analysis of randomized controlled trials. Hypertension. 2001; 38:1112-7. PubMed
 
Kincaid J, Fishburne RP Jr, Rogers RL, Chissom BS.  Derivation of new readability formulas (Automated Readability Index, Fog Count, and Flesch Reading Ease Formula) for Navy enlisted personnel. Research Branch Report 8-75. Millington, TN: Naval Technical Training U.S. Naval Air Station, Memphis; 1975.
 
Bosworth HB, Olsen MK, Neary A, Orr M, Grubber J, Svetkey L. et al.  Take Control of Your Blood Pressure (TCYB) study: a multifactorial tailored behavioral and educational intervention for achieving blood pressure control. Patient Educ Couns. 2008; 70:338-47. PubMed
 
Bosworth HB, Bastian LA, Kuchibhatla MN, Steffens DC, McBride CM, Skinner CS. et al.  Depressive symptoms, menopausal status, and climacteric symptoms in women at midlife. Psychosom Med. 2001; 63:603-8. PubMed
 
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003; 289:2560-72. PubMed
 
Hedeker D, Gibbons RD.  Longitudinal Data Analysis. New York: J Wiley; 2006.
 
Bosworth HB, Olsen MK, Goldstein MK, Orr M, Dudley T, McCant F. et al.  The veterans' study to improve the control of hypertension (V-STITCH): design and methodology. Contemp Clin Trials. 2005; 26:155-68. PubMed
 
Bosworth HB, Olsen MK, Dudley T, Orr M, Goldstein MK, Datta SK. et al.  Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J. 2009; 157:450-6. PubMed
 
Fitzmaurice G, Laird NM, Ware JH.  Applied Longitudinal Analysis. Hoboken, NJ: J Wiley; 2004. Wiley Series in Probability and Statistics.
 
SAS Knowledge Base.  Samples & SAS Notes. Sample 24982: jackknife and bootstrap analyses. Accessed athttp://support.sas.com/kb/24/982.htmlon 18 August 2009.
 
Cappuccio FP, Kerry SM, Forbes L, Donald A.  Blood pressure control by home monitoring: meta-analysis of randomised trials. BMJ. 2004; 329:145. PubMed
 
Stahl SM, Kelley CR, Neill PJ, Grim CE, Mamlin J.  Effects of home blood pressure measurement on long-term BP control. Am J Public Health. 1984; 74:704-9. PubMed
 
Campbell NR, Bass M, Chockalingam A, LeBel M, Milkovich L.  Self-measurement of blood pressure: benefits, risks and interpretation of readings. The Canadian Coalition for High Blood Pressure Prevention and Control. Can J Cardiol. 1995; 11:Suppl H18H-22H. PubMed
 
Fahey T, Schroeder K, Ebrahim S.  Interventions used to improve control of blood pressure in patients with hypertension. Cochrane Database Syst Rev. 2006; CD005182. PubMed
 
Boulware LE, Daumit GL, Frick KD, Minkovitz CS, Lawrence RS, Powe NR.  An evidence-based review of patient-centered behavioral interventions for hypertension. Am J Prev Med. 2001; 21:221-32. PubMed
 
Warsi A, Wang PS, LaValley MP, Avorn J, Solomon DH.  Self-management education programs in chronic disease: a systematic review and methodological critique of the literature. Arch Intern Med. 2004; 164:1641-9. PubMed
 
Morisky DE, Green LW, Levine DM.  Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care. 1986; 24:67-74. PubMed
 

Figures

Grahic Jump Location
Figure 1.
Study flow diagram.

BP = blood pressure.

* No longer receiving care at Duke clinics, receiving dialysis, received an organ transplant, residing in a nursing home or receiving home health care, had no telephone, or had pulmonary hypertension.

Grahic Jump Location
Grahic Jump Location
Figure 2.
Changes in study outcomes from baseline to 24 months, by intervention group.

Bars represent 95% CIs. BP = blood pressure. Top. Estimated proportion of patients with BP control. Estimates are marginalized probabilities from a logistic mixed-effects regression model (22). The model-estimated intrapatient correlation was 0.56. The 95% CIs at 12 and 24 months were derived from 1000 bootstrap samples. Middle. Estimated mean systolic BP. Estimates are based on a general linear model with an unstructured covariance matrix. The model-estimated correlation between time points ranged from 0.41 (baseline and 24 months) to 0.58 (months 6 and 12). Bottom. Estimated mean diastolic BP. Estimates are based on a general linear model with an unstructured covariance matrix. The model-estimated correlation between time points ranged from 0.54 (baseline and 24 months) to 0.66 (baseline and 6 months).

Grahic Jump Location

Tables

Table Jump PlaceholderTable 1.  Patient Characteristics at Baseline
Table Jump PlaceholderTable 2.  Changes in BP Control and Systolic and Diastolic BP at 12 and 24 Months

References

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CrossRef
 
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Morisky DE, DeMuth NM, Field-Fass M, Green LW, Levine DM.  Evaluation of family health education to build social support for long-term control of high blood pressure. Health Educ Q. 1985; 12:35-50. PubMed
 
Schroeder K, Fahey T, Ebrahim S.  How can we improve adherence to blood pressure-lowering medication in ambulatory care? Systematic review of randomized controlled trials. Arch Intern Med. 2004; 164:722-32. PubMed
 
Baker DW, Williams MV, Parker RM, Gazmararian JA, Nurss J.  Development of a brief test to measure functional health literacy. Patient Educ Couns. 1999; 38:33-42. PubMed
 
Parker RM, Baker DW, Williams MV, Nurss JR.  The test of functional health literacy in adults: a new instrument for measuring patients' literacy skills. J Gen Intern Med. 1995; 10:537-41. PubMed
 
Dewalt DA, Berkman ND, Sheridan S, Lohr KN, Pignone MP.  Literacy and health outcomes: a systematic review of the literature. J Gen Intern Med. 2004; 19:1228-39. PubMed
 
Karanja NM, Obarzanek E, Lin PH, McCullough ML, Phillips KM, Swain JF. et al.  Descriptive characteristics of the dietary patterns used in the Dietary Approaches to Stop Hypertension Trial. DASH Collaborative Research Group. J Am Diet Assoc. 1999; 99:S19-27. PubMed
 
Sacks FM, Appel LJ, Moore TJ, Obarzanek E, Vollmer WM, Svetkey LP. et al.  A dietary approach to prevent hypertension: a review of the Dietary Approaches to Stop Hypertension (DASH) Study. Clin Cardiol. 1999; 22:III6-10. PubMed
 
Svetkey LP, Sacks FM, Obarzanek E, Vollmer WM, Appel LJ, Lin PH. et al.  The DASH Diet, Sodium Intake and Blood Pressure Trial (DASH-sodium): rationale and design. DASH-Sodium Collaborative Research Group. J Am Diet Assoc. 1999; 99:S96-104. PubMed
 
Svetkey LP, Simons-Morton D, Vollmer WM, Appel LJ, Conlin PR, Ryan DH. et al.  Effects of dietary patterns on blood pressure: subgroup analysis of the Dietary Approaches to Stop Hypertension (DASH) randomized clinical trial. Arch Intern Med. 1999; 159:285-93. PubMed
 
Neter JE, Stam BE, Kok FJ, Grobbee DE, Geleijnse JM.  Influence of weight reduction on blood pressure: a meta-analysis of randomized controlled trials. Hypertension. 2003; 42:878-84. PubMed
 
.  The effects of nonpharmacologic interventions on blood pressure of persons with high normal levels. Results of the Trials of Hypertension Prevention, Phase I. JAMA. 1992; 267:1213-20. PubMed
 
Cutler JA.  Randomized clinical trials of weight reduction in nonhypertensive persons. Ann Epidemiol. 1991; 1:363-70. PubMed
 
Kelley GA, Kelley KS.  Progressive resistance exercise and resting blood pressure: A meta-analysis of randomized controlled trials. Hypertension. 2000; 35:838-43. PubMed
 
Whelton SP, Chin A, Xin X, He J.  Effect of aerobic exercise on blood pressure: a meta-analysis of randomized, controlled trials. Ann Intern Med. 2002; 136:493-503. PubMed
 
Xin X, He J, Frontini MG, Ogden LG, Motsamai OI, Whelton PK.  Effects of alcohol reduction on blood pressure: a meta-analysis of randomized controlled trials. Hypertension. 2001; 38:1112-7. PubMed
 
Kincaid J, Fishburne RP Jr, Rogers RL, Chissom BS.  Derivation of new readability formulas (Automated Readability Index, Fog Count, and Flesch Reading Ease Formula) for Navy enlisted personnel. Research Branch Report 8-75. Millington, TN: Naval Technical Training U.S. Naval Air Station, Memphis; 1975.
 
Bosworth HB, Olsen MK, Neary A, Orr M, Grubber J, Svetkey L. et al.  Take Control of Your Blood Pressure (TCYB) study: a multifactorial tailored behavioral and educational intervention for achieving blood pressure control. Patient Educ Couns. 2008; 70:338-47. PubMed
 
Bosworth HB, Bastian LA, Kuchibhatla MN, Steffens DC, McBride CM, Skinner CS. et al.  Depressive symptoms, menopausal status, and climacteric symptoms in women at midlife. Psychosom Med. 2001; 63:603-8. PubMed
 
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, National Heart, Lung, and Blood Institute Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure.  The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report. JAMA. 2003; 289:2560-72. PubMed
 
Hedeker D, Gibbons RD.  Longitudinal Data Analysis. New York: J Wiley; 2006.
 
Bosworth HB, Olsen MK, Goldstein MK, Orr M, Dudley T, McCant F. et al.  The veterans' study to improve the control of hypertension (V-STITCH): design and methodology. Contemp Clin Trials. 2005; 26:155-68. PubMed
 
Bosworth HB, Olsen MK, Dudley T, Orr M, Goldstein MK, Datta SK. et al.  Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J. 2009; 157:450-6. PubMed
 
Fitzmaurice G, Laird NM, Ware JH.  Applied Longitudinal Analysis. Hoboken, NJ: J Wiley; 2004. Wiley Series in Probability and Statistics.
 
SAS Knowledge Base.  Samples & SAS Notes. Sample 24982: jackknife and bootstrap analyses. Accessed athttp://support.sas.com/kb/24/982.htmlon 18 August 2009.
 
Cappuccio FP, Kerry SM, Forbes L, Donald A.  Blood pressure control by home monitoring: meta-analysis of randomised trials. BMJ. 2004; 329:145. PubMed
 
Stahl SM, Kelley CR, Neill PJ, Grim CE, Mamlin J.  Effects of home blood pressure measurement on long-term BP control. Am J Public Health. 1984; 74:704-9. PubMed
 
Campbell NR, Bass M, Chockalingam A, LeBel M, Milkovich L.  Self-measurement of blood pressure: benefits, risks and interpretation of readings. The Canadian Coalition for High Blood Pressure Prevention and Control. Can J Cardiol. 1995; 11:Suppl H18H-22H. PubMed
 
Fahey T, Schroeder K, Ebrahim S.  Interventions used to improve control of blood pressure in patients with hypertension. Cochrane Database Syst Rev. 2006; CD005182. PubMed
 
Boulware LE, Daumit GL, Frick KD, Minkovitz CS, Lawrence RS, Powe NR.  An evidence-based review of patient-centered behavioral interventions for hypertension. Am J Prev Med. 2001; 21:221-32. PubMed
 
Warsi A, Wang PS, LaValley MP, Avorn J, Solomon DH.  Self-management education programs in chronic disease: a systematic review and methodological critique of the literature. Arch Intern Med. 2004; 164:1641-9. PubMed
 
Morisky DE, Green LW, Levine DM.  Concurrent and predictive validity of a self-reported measure of medication adherence. Med Care. 1986; 24:67-74. PubMed
 

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