Hypertension
Conditions
Keywords
stroke, hypertension
Brief summary
This study evaluates a health theory based mobile health behavioral intervention to reduce blood pressure (BP) among hypertensive patients evaluated in a community Emergency Department (ED) setting.
Detailed description
Hypertension is the most important modifiable risk factor for cardiovascular disease, the leading cause of mortality in the United States. African Americans have the highest prevalence of hypertension of any race/ethnic group in the United States which largely contributes to their increased burden of stroke compared to non-Hispanic whites. In addition, uncontrolled hypertension is more common among socioeconomically disadvantaged populations than their counterparts. To improve health equity, new approaches to hypertension treatment focusing on health care systems and difficult-to-reach populations are needed. The Emergency Department (ED) represents a missed opportunity to identify and treat hypertension in difficult-to-reach populations. Currently, there are 136 million ED visits per year and nearly all have at least one blood pressure measured and recorded. African Americans and socioeconomically disadvantaged patients are disproportionally represented in the ED patient population and both are increasing. In the age of electronic health records and mobile health, the ED can feasibly become an integral partner in chronic disease management by programming the electronic health record to identify hypertensive patients and dispense a mobile health behavioral intervention. Facilitating ED follow up at primary care clinics is a key feature of the proposed intervention. Thereby leveraging the strengths of the ED and its large patient volume of uncontrolled, difficult-to-reach, hypertensive patients, with the strengths of the primary care clinics, continuity of care is the key to improving community wide utilization of health services and receipt of guideline concordant medical care. This study looks to determine which behavioral intervention components best contribute to a reduction in systolic blood pressure at one year through a multi-component theory based mobile health behavioral intervention. Sample Size and Population We originally planned to enroll approximately 960 patients into the eligibility phase. From this group, we estimate that 480 participants will report qualifying BPs and will be randomized to one of the eight intervention arms. We anticipate 240 participants will fully complete the 12 month, in person follow up visits. However, after accruing approximately 400 randomized participants, we noted lower than expected retention at 6 month visits. Therefore, we adjusted the maximum total number of enrollments and randomizations upwards by 50% each. The overall intention is to achieve approximately 240 protocol completers (attendees at 12-month visit). We will continue to monitor accrual and retention in order to achieve this target. Data Analysis The primary analysis will fit a linear regression model with the outcome of SBP change (baseline minus 12 months) and main effect-coded binary predictors of healthy behavior texts (yes vs. no), prompted BP self-monitoring frequency (high vs. low), and primary care provider visit scheduling and transportation (active vs. passive). Initial analyses will focus on the main effects. Additional analyses will include all the two-way interactions of the three intervention components (only considering interactions where at least one of the factors in the interaction demonstrates a sufficiently large main effect). The main secondary analyses will use time-to event (Cox Proportional Hazards) and logistic regression. For the endpoint of interest, (either time to first primary care visit, or the binary variable indicating attendance at two or more primary care visits within 1 year of randomization), the investigators will fit an adjusted regression model. Extension Study: Reach Out Cognition which will extend Reach Out data collection past the current 12 months to 15 and 18 months. During Reach Out Cognition, we aim to assess novel approaches to mobile health (mHealth) self-administered cognition and blood pressure (BP) measurements. These approaches may include cognitive assessments via mobile applications (apps) and Web-based surveys, and wireless BP measurements via Bluetooth-enabled blood pressure cuffs and apps. The study population for Reach Out Cognition will be drawn from Reach Out participants who complete the Reach Out intervention and are defined as: participants who complete the 12-month outcome assessment. We anticipate about 240 participants will have completed Reach Out's 12-month outcome assessment and will be eligible for Reach Out Cognition. Descriptive statistics will be used to evaluate acceptability, feasibility and satisfaction. The de-nominator is the number of Reach Out participants who complete the 12 month assessments. Regarding feasibility, we will separately determine the feasibility by mHealth measure (i.e. cognition vs. BP), phone type (i.e. smartphone vs. feature phone) and operating system type (iOS vs. Android vs. Windows) as a continuous and dichotomous (\>50% completion of each assessment type) measure. The satisfaction scale will be assessed for all participants. Given the difference in procedures by phone type, we will compare satisfaction between the smartphone and feature phone users using a Kruskal-Wallis test.
Interventions
Participants receive motivational health behavior texts
Participants do not receive healthy behavior texts
Daily text messages will prompt participants for BP by home cuff
Weekly text messages will prompt participants for BP by home cuff
Participants receive assistance scheduling physician appointment and transportation to those appointments
Participants do not receive assistance scheduling physician appointment or transportation
Sponsors
Study design
Eligibility
Inclusion criteria
* Age of 18 or greater * At least one BP with Systolic Blood Pressure (SBP) ≥ 160 or a Diastolic Blood Pressure (DBP) ≥ 100 (criteria 1) * If the patient has repeated measurements after achieving Criteria 1, at least one of the repeat BP remains SBP ≥ 140 or a DBP ≥ 90 * Must have cell phones with text-messaging capability and willingness to receive texts * Likely to be discharged from the ED
Exclusion criteria
* Unable to read English (\<1% at study site) * Prisoners * Pregnant * Pre-existing condition making one year follow-up unlikely * Terminal illness with death expected within 90 days * Current use of 3 or more antihypertensive agents * Patients with other serious medical conditions that prevent self-monitoring of BP * Critical illness with placement in resuscitation bay * Dementia/cognitive impairment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Change in Mean Systolic Blood Pressure | 12 months | Change in 12-month Systolic Blood Pressure (SBP) |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Hazard Ratio Analysis of Participant Time From Enrollment Emergency Department Visit to the First PCP Visit | Baseline ED visit (in days) | Utilizing multivariable Cox regression analysis, the relationship between mHealth components and attendance at initial Primary Care Physician (PCP) appointment after Emergency Department visit is explored. The analysis adjusts for age, sex, race, presence of a primary care provider, and usage of blood pressure medications. The Hazard Ratio in this context is a measure indicating the relative risk of experiencing the event of interest (time to first PCP visit). A Hazard Ratio greater than 1 implies a greater risk of receipt of a first PCP appointment, and a Hazard Ratio less than 1 implies a lower risk of receipt of a first PCP appointment within 12-month follow-up. The use of Hazard Ratio in this context allows for the assessment of the impact of mHealth components on the timing of primary care engagement while accounting for potential confounding variables. This allows more valuable insights into the effectiveness of these components in facilitating access to primary care visits. |
| Odds Ratio Analysis of Participants Completing 2 or More Primary Care Visits | 12 months | Utilizing logistic regression analysis, the probability of participants attending 2 or more primary care visits within a 12-month period is explored. The analysis adjusts for age, sex, race, presence of a primary care provider, and usage of blood pressure medications. The Odds Ratio in this context indicates the likelihood of an event occurring. A higher Odds Ratio suggests an increased likelihood of attending multiple primary care visits, while a lower Odds Ratio indicates a decreased likelihood. The use of Odds Ratio in this context is justified as it allows for the comparison of the likelihood of attending two or more primary care while accounting for covariates. This is useful in logistic regression analysis, where the outcome variable is binary (i.e., attending two or more primary care visits or not) and the focus is on understanding the association between predictor variables and the probability of the outcome. |
Countries
United States
Participant flow
Recruitment details
This trial was conducted in Flint, Michigan, an urban, low-income, predominately Black community. Participants were recruited from the city's only safety-net ED (i.e., hospitals where over 25% of patients are Medicaid recipients). Enrollment occurred between March 2019 and March 2020.
Pre-assignment details
Participants entered a run-in phase of 3 weeks to determine whether a participant had persistently elevated BP. During this time, participants were prompted to text their BP once per week to the study team. Participants responding at least once and with at least one systolic BP ≥ 140 or a diastolic BP ≥ 90 were randomized.
Participants by arm
| Arm | Count |
|---|---|
| Arm 1 No healthy behavior texts BP Monitoring Weekly Via Text Messaging No physician appointment and transportation scheduling
No healthy behavior texts: Participants do not receive healthy behavior texts
BP Monitoring Weekly Via Text Messaging: Weekly text messages will prompt participants for BP by home cuff
No physician appointment and transportation scheduling: Participants do not receive assistance scheduling physician appointment or transportation | 62 |
| Arm 2 Healthy Behavior Texts BP Monitoring Weekly Via Text Messaging No physician appointment and transportation scheduling
Healthy Behavior Texts: Participants receive motivational health behavior texts
BP Monitoring Weekly Via Text Messaging: Weekly text messages will prompt participants for BP by home cuff
No physician appointment and transportation scheduling: Participants do not receive assistance scheduling physician appointment or transportation | 60 |
| Arm 3 No healthy behavior texts BP Monitoring Daily Via Text Messaging No physician appointment and transportation scheduling
No healthy behavior texts: Participants do not receive healthy behavior texts
BP Monitoring Daily Via Text Messaging: Daily text messages will prompt participants for BP by home cuff
No physician appointment and transportation scheduling: Participants do not receive assistance scheduling physician appointment or transportation | 63 |
| Arm 4 Healthy Behavior Texts BP Monitoring Daily Via Text Messaging No physician appointment and transportation scheduling
Healthy Behavior Texts: Participants receive motivational health behavior texts
BP Monitoring Daily Via Text Messaging: Daily text messages will prompt participants for BP by home cuff
No physician appointment and transportation scheduling: Participants do not receive assistance scheduling physician appointment or transportation | 61 |
| Arm 5 No healthy behavior texts BP Monitoring Weekly Via Text Messaging Physician appointment and transportation scheduling
No healthy behavior texts: Participants do not receive healthy behavior texts
BP Monitoring Weekly Via Text Messaging: Weekly text messages will prompt participants for BP by home cuff
Physician appointment and transportation scheduling: Participants receive assistance scheduling physician appointment and transportation to those appointments | 58 |
| Arm 6 Healthy Behavior Texts BP Monitoring Weekly Via Text Messaging Physician appointment and transportation scheduling
Healthy Behavior Texts: Participants receive motivational health behavior texts
BP Monitoring Weekly Via Text Messaging: Weekly text messages will prompt participants for BP by home cuff
Physician appointment and transportation scheduling: Participants receive assistance scheduling physician appointment and transportation to those appointments | 61 |
| Arm 7 No healthy behavior texts BP Monitoring Daily Via Text Messaging Physician appointment and transportation scheduling
No healthy behavior texts: Participants do not receive healthy behavior texts
BP Monitoring Daily Via Text Messaging: Daily text messages will prompt participants for BP by home cuff
Physician appointment and transportation scheduling: Participants receive assistance scheduling physician appointment and transportation to those appointments | 64 |
| Arm 8 Healthy Behavior Texts BP Monitoring Daily Via Text Messaging Physician appointment and transportation scheduling
Healthy Behavior Texts: Participants receive motivational health behavior texts
BP Monitoring Daily Via Text Messaging: Daily text messages will prompt participants for BP by home cuff
Physician appointment and transportation scheduling: Participants receive assistance scheduling physician appointment and transportation to those appointments | 59 |
| Total | 488 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 | FG002 | FG003 | FG004 | FG005 | FG006 | FG007 |
|---|---|---|---|---|---|---|---|---|---|
| 12 Month Interventional Trial Period | Lost to Follow-up | 26 | 16 | 23 | 27 | 21 | 22 | 36 | 25 |
| 12 Month Interventional Trial Period | Withdrawal by Subject | 11 | 13 | 15 | 12 | 7 | 8 | 4 | 11 |
| Optional Six Month Follow-Up Period | Chose Not to start 6 month extension | 8 | 11 | 16 | 14 | 17 | 14 | 14 | 10 |
| Optional Six Month Follow-Up Period | ineligible | 8 | 5 | 2 | 2 | 1 | 5 | 2 | 4 |
| Optional Six Month Follow-Up Period | Lost to Follow-up | 8 | 11 | 6 | 4 | 9 | 8 | 3 | 6 |
| Optional Six Month Follow-Up Period | Withdrawal by Subject | 0 | 3 | 0 | 0 | 1 | 2 | 0 | 0 |
Baseline characteristics
| Characteristic | Total | Arm 8 | Arm 7 | Arm 6 | Arm 2 | Arm 5 | Arm 4 | Arm 1 | Arm 3 |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | 45.5 years STANDARD_DEVIATION 12.4 | 45.3 years STANDARD_DEVIATION 12.2 | 45.6 years STANDARD_DEVIATION 12.6 | 46.5 years STANDARD_DEVIATION 12.2 | 47.7 years STANDARD_DEVIATION 11.8 | 45.5 years STANDARD_DEVIATION 12.5 | 45.3 years STANDARD_DEVIATION 11.7 | 45.6 years STANDARD_DEVIATION 12.6 | 49 years STANDARD_DEVIATION 11.4 |
| Currently have a primary care provider | 380 Participants | 43 Participants | 49 Participants | 47 Participants | 50 Participants | 47 Participants | 48 Participants | 51 Participants | 45 Participants |
| Ethnicity (NIH/OMB) Hispanic or Latino | 17 Participants | 1 Participants | 2 Participants | 2 Participants | 1 Participants | 3 Participants | 2 Participants | 3 Participants | 3 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 471 Participants | 58 Participants | 62 Participants | 59 Participants | 59 Participants | 55 Participants | 59 Participants | 59 Participants | 60 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Prior medication for hypertension within the last 6 months | 273 Participants | 33 Participants | 36 Participants | 33 Participants | 35 Participants | 33 Participants | 34 Participants | 35 Participants | 34 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 2 Participants | 0 Participants | 0 Participants | 0 Participants | 2 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) Black or African American | 262 Participants | 30 Participants | 35 Participants | 39 Participants | 29 Participants | 35 Participants | 31 Participants | 29 Participants | 34 Participants |
| Race (NIH/OMB) More than one race | 22 Participants | 4 Participants | 2 Participants | 3 Participants | 2 Participants | 4 Participants | 1 Participants | 5 Participants | 1 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 1 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 1 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Race (NIH/OMB) White | 201 Participants | 25 Participants | 27 Participants | 19 Participants | 27 Participants | 19 Participants | 29 Participants | 28 Participants | 27 Participants |
| Region of Enrollment United States | 488 participants | 59 participants | 64 participants | 61 participants | 60 participants | 58 participants | 61 participants | 62 participants | 63 participants |
| Sex: Female, Male Female | 299 Participants | 37 Participants | 39 Participants | 38 Participants | 37 Participants | 36 Participants | 37 Participants | 37 Participants | 38 Participants |
| Sex: Female, Male Male | 189 Participants | 22 Participants | 25 Participants | 23 Participants | 23 Participants | 22 Participants | 24 Participants | 25 Participants | 25 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk | EG004 affected / at risk | EG005 affected / at risk | EG006 affected / at risk | EG007 affected / at risk |
|---|---|---|---|---|---|---|---|---|
| deaths Total, all-cause mortality | 0 / 62 | 0 / 60 | 0 / 63 | 2 / 61 | 0 / 58 | 0 / 61 | 1 / 64 | 0 / 59 |
| other Total, other adverse events | 0 / 62 | 0 / 60 | 0 / 63 | 0 / 61 | 0 / 58 | 0 / 61 | 0 / 64 | 0 / 59 |
| serious Total, serious adverse events | 0 / 62 | 0 / 60 | 0 / 63 | 0 / 61 | 0 / 58 | 0 / 61 | 0 / 64 | 0 / 59 |
Outcome results
Change in Mean Systolic Blood Pressure
Change in 12-month Systolic Blood Pressure (SBP)
Time frame: 12 months
Population: numbers analyzed in each row show all the participants at the two timepoints (baseline and 12 month) for which data exists.
| Arm | Measure | Group | Value (MEAN) |
|---|---|---|---|
| Arm 1 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -8.8 mmHg |
| Arm 1 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 135.1 mmHg |
| Arm 1 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 142.8 mmHg |
| Arm 2 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -8 mmHg |
| Arm 2 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 136.8 mmHg |
| Arm 2 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 146.8 mmHg |
| Arm 3 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 138.2 mmHg |
| Arm 3 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 143.9 mmHg |
| Arm 3 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -3.2 mmHg |
| Arm 4 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -8.8 mmHg |
| Arm 4 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 144.7 mmHg |
| Arm 4 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 135.4 mmHg |
| Arm 5 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 148 mmHg |
| Arm 5 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 136.9 mmHg |
| Arm 5 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -7.3 mmHg |
| Arm 6 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 145.8 mmHg |
| Arm 6 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 138.8 mmHg |
| Arm 6 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -5.4 mmHg |
| Arm 7 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 147.4 mmHg |
| Arm 7 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 139 mmHg |
| Arm 7 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -6 mmHg |
| Arm 8 | Change in Mean Systolic Blood Pressure | Mean Change from Baseline | -4.9 mmHg |
| Arm 8 | Change in Mean Systolic Blood Pressure | Mean @ Baseline | 149 mmHg |
| Arm 8 | Change in Mean Systolic Blood Pressure | Mean of Median SBP @ 12 months | 138.5 mmHg |
Hazard Ratio Analysis of Participant Time From Enrollment Emergency Department Visit to the First PCP Visit
Utilizing multivariable Cox regression analysis, the relationship between mHealth components and attendance at initial Primary Care Physician (PCP) appointment after Emergency Department visit is explored. The analysis adjusts for age, sex, race, presence of a primary care provider, and usage of blood pressure medications. The Hazard Ratio in this context is a measure indicating the relative risk of experiencing the event of interest (time to first PCP visit). A Hazard Ratio greater than 1 implies a greater risk of receipt of a first PCP appointment, and a Hazard Ratio less than 1 implies a lower risk of receipt of a first PCP appointment within 12-month follow-up. The use of Hazard Ratio in this context allows for the assessment of the impact of mHealth components on the timing of primary care engagement while accounting for potential confounding variables. This allows more valuable insights into the effectiveness of these components in facilitating access to primary care visits.
Time frame: Baseline ED visit (in days)
Population: 211 is all of the participants in each of the eight arms who completed
| Arm | Measure | Value (NUMBER) |
|---|---|---|
| Arm 1 | Hazard Ratio Analysis of Participant Time From Enrollment Emergency Department Visit to the First PCP Visit | 0.9 hazard ratio |
| Arm 2 | Hazard Ratio Analysis of Participant Time From Enrollment Emergency Department Visit to the First PCP Visit | 1.2 hazard ratio |
| Arm 3 | Hazard Ratio Analysis of Participant Time From Enrollment Emergency Department Visit to the First PCP Visit | 1.2 hazard ratio |
Odds Ratio Analysis of Participants Completing 2 or More Primary Care Visits
Utilizing logistic regression analysis, the probability of participants attending 2 or more primary care visits within a 12-month period is explored. The analysis adjusts for age, sex, race, presence of a primary care provider, and usage of blood pressure medications. The Odds Ratio in this context indicates the likelihood of an event occurring. A higher Odds Ratio suggests an increased likelihood of attending multiple primary care visits, while a lower Odds Ratio indicates a decreased likelihood. The use of Odds Ratio in this context is justified as it allows for the comparison of the likelihood of attending two or more primary care while accounting for covariates. This is useful in logistic regression analysis, where the outcome variable is binary (i.e., attending two or more primary care visits or not) and the focus is on understanding the association between predictor variables and the probability of the outcome.
Time frame: 12 months
| Arm | Measure | Value (NUMBER) |
|---|---|---|
| Arm 1 | Odds Ratio Analysis of Participants Completing 2 or More Primary Care Visits | 0.7 Odds Ratio |
| Arm 2 | Odds Ratio Analysis of Participants Completing 2 or More Primary Care Visits | 1.8 Odds Ratio |
| Arm 3 | Odds Ratio Analysis of Participants Completing 2 or More Primary Care Visits | 1.7 Odds Ratio |