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Only approximately half of patients with hypertension have their blood pressure controlled, due in large part to the tendency of primary care providers (PCPs) not to intensify treatment when blood pressure values are elevated.
This study tested the effect of an intervention designed to help patients ask questions at the point of care to encourage PCPs to appropriately intensify blood pressure treatment.
PCPs and their patients with hypertension (N=500) were recruited by letter and randomized into 2 study groups: (1) intervention condition in which patients used a fully automated website each month to receive tailored messages suggesting questions to ask their PCP to improve blood pressure control, and (2) control condition in which a similar tool suggested questions to ask about preventive services (eg, cancer screening). The Web-based tool was designed to be used during each of the 12 study months and before scheduled visits with PCPs. The primary outcome was the percentage of patients in both conditions with controlled blood pressure.
Of 500 enrolled patients (intervention condition: n=282; control condition: n=218), 418 (83.6%) completed the 12-month follow-up visit. At baseline, 289 (61.5%) of participants had controlled blood pressure. Most (411/500, 82.2%) participants used the intervention during at least 6 of 12 months and 222 (62.5%) reported asking questions directly from the Web-based tool. There were no group differences in asking about medication intensification and there were no differences in blood pressure control after 12 months between the intervention condition (201/282, 71.3%) and control condition (143/218, 65.6%;
The use of an interactive website designed to overcome clinical inertia for hypertension care did not lead to improvements in blood pressure control. Participant adherence to the intervention was high. The control intervention led to positive changes in the use of preventive services (eg, tetanus immunization) and the intervention condition led to more discussions of hypertension-relevant tests (eg, serum creatinine and urine protein). By providing patients with individually tailored questions to ask during PCP visits, this study demonstrated that participants were likely to discuss the questions with PCPs. These discussions did not, however, lead to improvements in blood pressure control.
ClinicalTrials.gov NCT00377208; http://clinicaltrials.gov/ct2/show/NCT00377208 (Archived by WebCite at http://www.webcitation.org/6IqWiPLon).
Hypertension is one of the most common chronic illnesses in the United States, affecting more than 1 in 4 adults [
Given the contribution of hypertension to cardiovascular disease and the relatively high rates of uncontrolled blood pressure, many intervention methods have been developed and tested. Team-based care, for example, in which the patient’s primary care provider works with other professionals, such as nurses, pharmacists, dietitians, social workers, and community health workers, has consistently been observed to improve blood pressure control [
Engaging patients in their own care, known as
We undertook this study to understand whether the same approach could be used with a chronic medical condition such as hypertension. We hypothesized that if patients whose blood pressure was not controlled were reminded to ask specific questions that may lead their provider to intensify their care, that the reminders would increase blood pressure control. The target, therefore, was clinical inertia, or the tendency of providers not to make a change to the plan of care for participants who are not at their treatment target [
The overall intent of the intervention was to encourage users whose blood pressure was not at goal to ask questions that would lead to medication intensification. We chose to target patients with hypertension that had a history of not being controlled, but did not require all patients at baseline to have uncontrolled hypertension for the following reasons. First, the intervention was designed for a managed care organization (MCO) to make available to the individual patients covered by the MCO. However, MCOs, other than staff-model MCO’s (eg, Kaiser Permanente), are typically unaware of which patients have controlled and uncontrolled blood pressure because they lack access to data from the electronic health record. For that reason, we anticipated that MCOs would make such a tool available to patients without regard to blood pressure values, given findings from Egan and others [
A complete description of the study design and baseline characteristics of participants is published elsewhere [
Physicians were randomized to the intervention condition or control condition and, consistent with a cluster-randomized trial design, all patients recruited from a physician were then assigned to the same condition as their physician. Therefore, all interventions pertained to the cluster to which the physician was assigned. For example, for providers assigned to the intervention condition, all of their patients who were enrolled in this study were assigned to the hypertension intervention. To reduce the chances that staff would treat patients differently, particularly while assessing outcomes, staff were blinded to the condition of the provider. Providers and their patients were randomized to 1 of 2 following conditions.
Participants were instructed to answer questions online once each month and before any visits with their hypertension care provider. Questions focused on the care they had recalled receiving (eg, creatinine testing) and the blood pressure from their most recent doctor visit. Based on their responses and prewritten rules, participants received a brief prewritten tailored feedback message. Each tailored feedback message included a question that the patient should consider asking their provider (eg, “What can you do to help me lower my blood pressure?”) and a lay summary of the guideline recommendation and the evidence underlying the recommendation. All decision rules and tailored messages were based on the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) [
Participants randomized to this group received Web-based tailored feedback and were prompted to ask questions during primary care provider (PCP) visits regarding preventive services that they were due to receive. All decision rules and tailored messages were based on guidelines from the United States Preventive Services Task Force (USPSTF; eg, tetanus vaccination, screening for colon cancer). The frequency of activities in the control condition was identical to those in the intervention condition.
The primary outcome measure was blood pressure control. Blood pressure was measured by a standardized protocol [
Changes in medications and hypertension-related tests (eg, creatinine) were measured by chart abstraction at 12 months after the baseline study visit. The use of preventive services (eg, tetanus vaccination) was measured via patient self-report. The impact of the intervention on doctor-patient communication was measured by a self-reported survey, completed within 72 hours after the participants’ first visits with their hypertension care provider. This exit survey was designed to measure what was discussed during the visit, and provide insight into how the tailored feedback was being used. Similar methods have been studied by 1 of the investigators (CNS) and observed to be accurate for identifying activities that occur during provider visits [
See
After getting consent from the PCP, study staff visited the practice to review the charts of patients to identify eligible patients who met the blood pressure and age criteria (
Eligible participants were scheduled for a baseline visit at their physician’s office, where study staff received their consent (see
CONSORT diagram of participant flow.
Patient inclusion and exclusion criteria.
Criteria | Description |
Inclusion | Age ≥21 years |
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Fluent in English |
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At least 2 high blood pressure readings in the previous 12 months (≥130/≥80 mmHg for patients with diabetes or chronic kidney disease, ≥140/≥90 mmHg without) |
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Primary care provider was participating in the study |
Exclusion | Receiving care from another physician for hypertension treatment (eg cardiologist) |
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Hospitalized for a psychiatric disorder in the past 3 years |
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Participating in another clinical research study |
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Pregnant or planned to become pregnant in the next 12 months |
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Planning on moving out of the area in the next 12 months |
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No personal access to the Internet at home or at work |
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No personal email account |
Randomization was done at the level of the PCP. PCPs were enrolled and randomized into 1 of 2 conditions by selecting an envelope containing a document noting the assigned condition (intervention condition or control condition) from a stack of sealed envelopes, the order of which was generated by the study statistician (EL). All patient participants were assigned to the same condition as their PCP, consistent with a cluster-designed randomized trial [
The intervention condition participants received access to the hypertension module of the Web-based intervention for 12 months, which included: (1) Web-based hypertension feedback based on the individual patient’s self-report of health variables (see
On the website, patients entered blood pressure values measured at clinical visits and answered questions about their hypertension-related care (eg, date and value of last creatinine blood test). The patient was then provided with onscreen tailored feedback, based on preprogrammed rules adapted from recommendations in JNC 7 [
The Web-based feedback was based on the hypertension guidelines in JNC 7 [
The intervention was designed to be used before a visit with the physician who provided the patient’s hypertension care. For that reason, it was essential to track the dates of these visits so the patients could be reminded to use the intervention before these visits. It was assumed that the intervention would be significantly less effective if used long before or following an office visit, as the intervention is designed to activate patients to ask specific questions during visits [
An important requirement of the intervention was that patients enter data (eg, blood pressure, creatinine values) that they would typically only receive during visits with a health care provider. For that reason, we created a wallet-sized pocket chart to help patients gather this data during office visits. The participant could then later enter these numbers into the website. Participants were encouraged to print the pocket chart and bring it to their doctor visits and ask their physician to record test results, or ask their physician for the test value and record it themselves.
The control condition was identical to the intervention condition, except that the content of the control condition intervention focused exclusively on preventive services rather than hypertension (see
The expected effect size was based on a meta-analysis by Stone and colleagues [
The 2 randomized groups were compared on important demographic and other baseline variables to ensure successful randomization. Student
Data analysis was focused on the primary hypothesis that a higher percentage of participants in the intervention condition condition, compared to control condition participants, would have controlled blood pressure at 12 months, using intent-to-treat principles [
Screenshot of intervention condition monthly survey.
Screenshot of intervention condition feedback from monthly survey.
Baseline data comparing characteristics in different conditions.
Characteristic | Total |
Intervention |
Control |
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Age (years), mean (SD) | 60.5 (11.9) | 59.6 (12.1) | 61.6 (11.4) | .07 | |
Gender (female), n (%) | 288 (57.6) | 165 (58.5) | 123 (56.4) | .64 | |
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Non-Hispanic white | 375 (75.0) | 123 (75.5) | 162 (74.3) | .75 |
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Hispanic | 13 (2.6) | 10 (3.5) | 3 (1.4) | .13 |
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Education (college ≥4 years) | 202 (42.4) | 113 (41.7) | 89 (43.4) | .71 |
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Income (≤US $50,000) | 221 (49.3) | 124 (49.0) | 97 (49.7) | .88 |
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Employed for wages | 214 (45.0) | 140 (51.7) | 74 (36.1) | <.001 |
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Body mass index, mean (SD) | 32.4 (7.4) | 32.1 (7.3) | 32.7 (7.6) | .42 |
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Smoking, n (%) | 41 (8.6) | 21 (7.8) | 20 (9.8) | .44 |
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Diabetes, n (%) | 104 (22.0) | 61 (22.6) | 43 (21.3) | .73 |
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Health (very good/excellent), n (%) | 160 (33.6) | 88 (32.5) | 72 (35.1) | .54 |
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Systolic (mm Hg), mean (SD) | 132.6 (15.0) | 132.7 (14.9) | 132.4 (15.2) | .84 |
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Diastolic (mm Hg), mean (SD) | 75.5 (11.0) | 75.7 (11.1) | 75.2 (10.9) | .62 |
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Systolic controlled, n (%) | 303 (64.5) | 181 (67.5) | 122 (60.4) | .11 |
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Diastolic controlled, n (%) | 405 (86.2) | 203 (85.8) | 175 (86.6) | .80 |
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Overall controlled, n (%) | 289 (61.5) | 170 (63.4) | 119 (58.9) | .32 |
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Number of BP medications, n (%) | 1.0 (1.61) | 1.0 (1.51) | 1.0 (1.73) | .02 |
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Internet use for health, ≥once/month | 94 (20.9) | 52 (20.4) | 42 (21.7) | .75 |
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Used Internet before a physician visit | 227 (51.1) | 140 (54.9) | 87 (46.0) | .06 |
a
Five university physicians group clinics associated with Hershey Medical Center and 836 family practices were contacted to enroll in our study. Of the physicians contacted, 54 (6.4%) responded and agreed to participate. Consistent with a cluster-randomized design, randomization was at the level of the provider, and each cluster included the provider and all patients of that single provider who were enrolled in the study. Therefore, all patients recruited were assigned to the condition (intervention condition or control condition) that the provider had been randomly assigned, and all analyses were performed at the level of the cluster, in this case the provider. After a medical record chart review, patients of enrolled physicians with a diagnosis of hypertension (n=4776) were sent recruitment letters inviting them to participate in the study. Of those who were sent a letter, 828 (17.3%) responded and 812 (17%) were able to be contacted and screened for eligibility. Eligible participants (n=528) were scheduled for a baseline visit at which 3 consecutive blood pressures were measured. Of those scheduled, 500 completed the baseline visit and 218 participants were enrolled into the control condition (prevention) and 282 into the intervention condition (hypertension). Following the baseline visit, 476 (95.2%) participants logged onto the website and completed the online baseline measures. From the 476 participants who completed the baseline measures questionnaire, demographic data as well as baseline secondary outcome data were collected (
As stated previously, the intervention was designed to be used by answering a series of questions and reviewing tailored feedback at least once each month. Of the 500 participants, 411 (82.2%) used the intervention during at least 6 of 12 months, and 174 (34.8%) logged into and used the website each of the 12 months enrolled in the study (
Because the goal of the intervention was to intervene on patients with uncontrolled blood pressure, a subgroup analysis was performed that was limited to those participants whose blood pressure was uncontrolled at baseline. Of the 188 participants found to be uncontrolled at baseline, 87 (46.3%) were controlled at 12-month follow-up. However, no significant difference was observed in blood pressure control rates between study groups (intervention condition: 47/103, 45.6%; control condition: 40/85, 47.1%;
Percentage of participants using the intervention during each of the 12 study months.
Mean (± standard error) number of log-ins per month in both conditions in each of the 12 study months.
Primary blood pressure (BP) outcomes.
Outcome | Total | Intervention | Control |
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Systolic BP (mm Hg), mean (SD) | 128.5 (13.9) | 128.3 (13.5) | 128.9 (14.4) | .88 |
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Diastolic BP (mm Hg), mean (SD) | 74.1 (9.2) | 73.8 (8.9) | 74.4 (9.6) | .15 |
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Systolic BP controlled, n (%) | 372 (74.4) | 206 (76.6) | 156 (71.6) | .35 |
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Diastolic BP controlled, n (%) | 447 (89.4) | 254 (90.1) | 193 (88.5) | .59 |
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Overall BP controlled, n (%) | 344 (68.8) | 201 (71.3) | 143 (65.6) | .27 |
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Systolic BP (mm Hg), mean (SD) | 135.4 (13.5) | 134.9 (13.3) | 136.1 (13.9) | .83 |
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Diastolic BP (mm Hg), mean (SD) | 77.0 (10.1) | 77.3 (9.5) | 76.7 (10.8) | .79 |
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Systolic BP controlled, n (%) | 103 (54.8) | 58 (56.3) | 45 (52.9) | .89 |
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Diastolic BP controlled, n (%) | 152 (80.9) | 81 (78.6) | 71 (83.5) | .51 |
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Overall BP control, n (%) | 87 (46.3) | 47 (45.6) | 40 (47.1) | .57 |
a
Impact on doctor–patient communication.
Self-reported outcomes | Total |
Intervention condition |
Control condition |
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Asked any questions from the website | 222 (62.5) | 125 (63.8) | 97 (61.0) | .52 |
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Discussed notes about website at visit | 143 (42.3) | 76 (39.8) | 70 (45.5) | .37 |
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Discussed having a tetanus shot | 78 (25.4) | 28 (16.9) | 50 (35.5) | <.001 |
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Discussed having a pneumonia shot | 62 (21.0) | 23 (14.4) | 39 (28.9) | .01 |
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Discussed having a flu shot | 143 (45.7) | 74 (43.3) | 69 (48.6) | .94 |
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Discussed having a test for colon cancer | 76 (24.9) | 38 (22.8) | 38 (27.5) | .55 |
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Discussed what your last blood pressure numbers were | 309 (87.3) | 171 (87.2) | 138 (87.3) | .97 |
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Discussed having creatinine tested | 141 (45.1) | 92 (52.6) | 49 (35.5) | .02 |
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Discussed urine test for protein | 102 (31.4) | 81 (44.8) | 21 (14.6) | <.001 |
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Discussed secondary causes of hypertension | 20 (7.2) | 10 (6.7) | 10 (7.8) | .52 |
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Discussed changing to blood pressure medication that works better for you | 27 (9.3) | 17 (10.7) | 10 (7.6) | .47 |
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Discussed more frequent visits until blood pressure controlled | 38 (13.7) | 24 (16.2) | 14 (10.9) | .42 |
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Doctor recommended starting a new blood pressure medication | 34 (10.3) | 21 (11.7) | 13 (8.7) | .62 |
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Doctor recommended increasing dose of a blood pressure medication | 31 (9.9) | 18 (10.7) | 13 (9.0) | .52 |
a
Secondary outcomes of changes in medications and preventive and hypertension screening tests.
Secondary outcomes | Total |
Intervention |
Control |
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Total number of medications at baseline | 1.61 (1.0) | 1.51 (1.0) | 1.73 (1.0) | .16 |
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Total number of medications at follow-up | 1.39 (1.1) | 1.34 (1.1) | 1.45 (1.1) | .64 |
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Change in number of medications | –0.22 (0.93) | –0.17 (0.92) | -0.28 (0.93) | .64 |
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Tetanus vaccine within 1 year | 45 (9.0) | 15 (5.3) | 30 (13.8) | .02 |
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Pneumonia vaccine within 1 year | 41 (8.2) | 16 (5.7) | 25 (11.5) | .02 |
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Influenza vaccine within 1 year | 280 (56.0) | 152 (53.9) | 128 (58.7) | .81 |
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Colonoscopy within 1 year | 37 (7.4) | 22 (7.8) | 15 (6.9) | .72 |
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Serum creatinine tested within 1 year | 367 (73.4) | 211 (74.8) | 156 (71.6) | .56 |
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Urine protein tested within 1 year | 144 (28.8) | 86 (30.5) | 58 (26.6) | .26 |
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Serum potassium tested within 1 year | 362 (72.4) | 209 (74.1) | 153 (70.2) | .31 |
a
The present study evaluated the efficacy of an intervention designed to prompt patients to ask questions about their blood pressure control. We hypothesized that by encouraging patients to ask questions with a focus on questions aimed at improving control (“What can you help me do to lower my blood pressure?”), physicians would give patients higher doses of blood pressure medications or additional medications, which would improve blood pressure control more in the intervention condition. The results indicated, however, that the intervention did not improve blood pressure control. Although the intervention led to more discussions of some hypertension-related screening tests (eg, creatinine testing), it did not lead to improvements in blood pressure control. At baseline, 312 of 500 (62.4%) participants had their systolic and diastolic blood pressure controlled as per JNC 7 guidelines [
There are several possible hypotheses to explain why no effect on blood pressure was observed. First, patients may not have been comfortable asking for intensifications to their medication treatment plan because of a concern about questioning the expertise of the provider. Although Kravitz and colleagues [
Asking for medication intensification may have been perceived by patients as questioning the judgment of the provider, which may have created a barrier to asking for medication intensifications. This is consistent with the observation, in
A second possible reason for the lack of effect may be the general lack of awareness of the significance of a blood pressure value that is not at target. Although professionals view a systolic blood pressure of 160 mm Hg very differently from 140 mm Hg, these differences are likely not as meaningful to patients. Wright-Nunes and colleagues [
A third possible reason is that blood pressure varies significantly from measurement to measurement, yet the decision rule that created the tailored message was based on just 1 blood pressure measurement [
Finally, a fourth possible reason for the lack of effect was the impact of secular trends of blood pressure in the United States. Hypertension control improved significantly between 1988 and 2008, which limited the ability of the study to affect blood pressure control because more patients were controlled than anticipated in our power calculations [
This study does have some limitations. First, the patients may not have used the intervention before doctor visits or asked questions during doctor visits and the study did not collect the data to assure that these were done. However, mean use per month (± standard error; as seen in
Second, a limitation of the study was the management and use of blood pressure values. Patients were encouraged to enter the most recent blood pressure value onto the website, which then generated tailored feedback based, in part, on that number. However, approximately one-third of participants did not enter a blood pressure value because they were unaware of their blood pressure. Even if the participant had entered a blood pressure value, during the subsequent visit to their provider, that value would likely have been different. This situation may have created confusion and uncertainty for patients, undermining their desire to ask for treatment intensifications. This would not be the case, for example, for tetanus vaccination, which is stable over time. To address this limitation, future studies should consider using home blood pressure monitoring, so that patients are prompted to ask questions based on their average home values. Powers and colleagues [
A third limitation of the study is that the level of blood pressure control observed at baseline in this study was higher than anticipated. The study was powered to detect a 60% blood pressure control rate in the intervention condition versus 40% in the control condition, yet 61.5% of patients had controlled blood pressure at baseline. Enrolling patients whose blood pressure was controlled or nearly controlled lessened the likelihood that patients would see a message from the program that convinced them that their blood pressure was sufficiently far from the goal to talk to their doctor about changing their medications. If the study had limited participation to those with Stage 2 hypertension (systolic ≥160 mm Hg, diastolic ≥100 mm Hg), for example, both providers and patients may have been more responsive to the interventions, believing that the distance from current control to the goal was further. However, if more of the same type of patients were enrolled, it is unlikely that the results would have been different. Of the 188 patients whose blood pressure was not controlled at baseline, blood pressure control at 12 months was slightly higher in the control condition than the intervention condition, suggesting that inflating the sample size would not have changed the outcomes.
Fourth, as in most clinical trials, ours was in a limited geographic region with patient profiles that do not match the target population in the entire United States. Only 1% of participants in this study were uninsured, for example, compared to 4% of primary care patients nationwide [
A fifth potential limitation is that detailed covariate data were not collected and may have differed between conditions, yet were not adjusted for. Physical activity, alcohol intake, and salt intake each can influence blood pressure [
There are several strengths to our study. First, the study used an active treatment control group. Not only did this limit participant attrition and control for contact time, the active treatment control condition provided data to document that the intervention was effective at increasing preventive care, limiting concerns over whether participants had actually used the intervention as it was designed. Second, using the Internet as a communication medium makes what is learned easily disseminated. Although most Web-based studies to date have not shown major health benefits (eg, weight control) [
Patient recruitment letter.
IRB approved informed consent form.
Patient online exit survey.
Patient online follow up measures.
Intervention online monthly survey.
Intervention online feedback.
Preventive online monthly survey.
Preventive online feedback.
CONSORT-EHEALTH checklist V1.6.2 [
Behavioral Risk Factor Surveillance Survey
Centers for Disease Control and Prevention
Consolidated Standards of Reporting Trials
Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure
Markov chain Monte Carlo
managed care organization
National Committee for Quality Assurance
National Health and Nutrition Examination Survey
odds ratio
primary care provider
Penn State Hershey Medical Center
United States Preventive Services Task Force
This study was funded by the National Heart, Lung and Blood Institute, grant# R01HL083432. The user interface development was done by Digital Alternatives under contract by authors.
None declared.