Clinical trial NCT06324981: Using AI Text Messaging to Improve AHA's Life's Essential 8 Health Behaviors
Official title: Using Artificially Intelligent Text Messaging Technology to Improve American Heart Association's Life's Essential 8 Health Behaviors: LE8 Bot + Backup
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Cardiovascular Diseases
Lifestyle Factors
Keywords: cardiovascular disease
Life's Essential 8
mHealth
Lead sponsor: University of Colorado, Denver
Sponsor class: OTHER
Collaborators: name: National Heart, Lung, and Blood Institute (NHLBI)
First posted: 2024-03-22
Enrollment: 2100
Sex: ALL
Minimum age (years): 18
Maximum age (years): 89
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: SUPPORTIVE_CARE

Brief summary: The goal of our pragmatic clinical trial is to compare how well three different strategies might do to reduce risk factors for cardiovascular disease in patients experiencing health disparities. The three different strategies are: 1) text messages, 2) interactive chatbot messages, and 3) chatbot messages with proactive pharmacist support. To measure cardiovascular risk factors, the investigators are using the American Heart Association's Life's Essential 8 (LE8) factors-blood glucose, cholesterol, blood pressure, physical activity, body mass index, diet, and smoking.

This study focuses on improving cardiovascular risk factors for individuals facing health disparities, such as ethnic minorities, limited English proficiency, and low-income groups. These groups are more likely to be seriously affected by cardiovascular diseases. Self-management, or an individual's roles in managing their own chronic disease, includes lifestyle changes, medication adherence. Improving patients' self-management has been shown to improve health behaviors, better disease control and improved patient outcomes.

The main question this study aims to answer is if one of the strategies (texting, chatbot, or chatbot with pharmacist support) may improve patient self-management and patient outcomes.

The investigators will enroll up to 2,100 patients from three health systems that serve large populations experiencing health disparities: Denver Health, Salud Family Health Centers, and STRIDE Community Health Center.

The results might help researchers and health care systems find the best ways to involve patients with health disparities to managing their chronic cardiovascular disease.

Detailed description: Our goal is to improve control of cardiovascular (CV) disease risk factors by engaging patients experiencing health disparities in an innovative technology-based self-management intervention with linkages to health system providers. The investigators will focus on the American Heart Association's Life's Essential 8 (LE8) lifestyle factors (blood glucose, cholesterol, blood pressure, physical activity, body mass index, diet, and smoking), that when uncontrolled lead to common co-existing chronic conditions (e.g., hypertension, diabetes), morbidity, health care costs and death. Patients disproportionately affected by these risk factors (e.g., Black, Hispanic/Latino), have worse disease control with greater adverse sequelae (e.g., heart attacks and death).

Self-management is an individual's role in managing chronic disease and has strong evidence of benefit. It includes self-care, a healthy lifestyle (e.g., being physically active), taking medications as prescribed and managing exacerbations of chronic condition(s). Self-management for patients experiencing disparities is enhanced when programs recognize patient context and sociocultural factors that may modify healthy behavior. Self-management can be further enriched when patients are directly supported by their health care provider. Ample evidence shows text messaging can impact self-management behaviors, with the advantage of being universally available through mobile phones. Emerging technologies utilize artificially intelligent (AI) chatbots for the delivery of text messages have the promise of improving the impact of text messaging, particularly if they integrate evidence based communication strategies, including tailoring, behavioral nudges that support intuitive decision-making, and persuasive messaging. These strategies can optimize message content beyond generic, "one size fits all" communication. It is unknown if AI chatbot text messaging with linkages to providers can improve self-management support in large diverse patient populations.

Using a patient level randomized pragmatic trial in 3 health systems caring for large patient populations experiencing health disparities, the investigators will test the comparative effectiveness of theory-based, tailored and socially contextualized communications for self-management support. Patients with CV disease risk factors will be randomized to 1 of 3 automated communication approaches: 1) generic text messages; 2) interactive AI chatbot text messaging leveraging evidenced-based communication strategies with attention to patient context and sociocultural factors influencing self-management; or 3) interactive AI chatbot text messaging plus proactive pharmacist management. Our goal is to increase patient self-management autonomy, competence, and relatedness to health systems, leading to improved and sustained health behaviors, better disease control and improved patient outcomes. The primary effectiveness outcome will be an improved LE8 health score. The investigators will partner with: 1) Salud Family Health Centers, a Federally Qualified Health Center (FQHC) with 13 clinics across Colorado, 2) Denver Health and Hospital Authority, a safety net health system with 9 FQHC clinics, and 3) STRIDE Community Health Center, a FQHC with18 locations surrounding Denver county. The investigators will enroll diverse patients including: Black, Hispanic/Latino, low-income, Spanish speaking-only and rural patients with at least one LE8 factor in the poor/intermediate health category and poor adherence to CV medications. Patients will be identified using demographic, clinical and pharmacy EHR data from each health system. In Year 1 (UG3 phase), applying the Health Equity in Implementation Framework, the investigators will partner with patients, providers, community advocates and health systems stakeholders to develop the AI chatbot infrastructure and message content relevant to the patient population using an intervention mapping approach; assess how best to integrate the intervention within each health system's existing CV prevention programs; and conduct a pilot study of the intervention. In Years 2-5 (UH3 phase), the investigators will conduct a pragmatic patient randomized trial.

Aim 1 (UG3; Year 1): Iteratively update the infrastructure and expand content for the AI text message chatbot with attention to social determinants of health and sociocultural contextual relevant to the target population through stakeholder engaged N-of-1 and focus group interviews and nominal group sessions.

Aim 2 (UG3; Year 1): Conduct a randomized pilot to demonstrate feasibility of intervention delivery and outcomes data collection to assess preliminary effects and to refine the intervention prior to widespread implementation Aim 3 (UH3; Years 2-5): Conduct a pragmatic patient-level randomized intervention of 3 text messaging delivery strategies for self-management support of CV risk factors. Primary outcome will be change in LE8 health score. Secondary effectiveness outcomes will include individual components of the LE8 lifestyle factors, Framingham risk score, self-efficacy, medication adherence, clinical outcomes (e.g., CV related hospitalizations), and healthcare utilization.

Aim 4 (UH3; Years 2-5): Evaluate the intervention using PRISM and a mixed methods approach to evaluate pragmatic clinical and implementation outcomes (reach, effectiveness, adoption, implementation, and maintenance) with an emphasis on equity and representativeness, and systematically assess contextual influences to inform sustainment and future tailoring, adaptations, and dissemination.

Eligibility criteria: Inclusion Criteria:

* diagnosis of one or more of the following CV risk factors (i.e., hypertension, diabetes or hyperlipidemia); and
* the risk factor is at poor or intermediate health levels as defined by LE8 (e.g., BP\>140/90 mm Hg); and
* the patient exhibits poor adherence to prescribed medication to treat the CV risk factor as defined by a delay in refilling the medication within the past 6 months.

Exclusion Criteria:

* patients who do not have cellphone; or
* enrolled in hospice or palliative care; or
* Non-English or Spanish speaking; or
* enrolled in another clinical trial if denoted in the EHR.

Primary outcomes:
measure: Change in Life's Essential 8 risk score
timeFrame: Baseline and 12 months after randomization
Secondary outcomes:
measure: Blood pressure (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Total cholesterol (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Blood sugar (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Body Mass Index (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Physical activity (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Sleep (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Smoking habits (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Health diet pattern (Individual Life's Essential 8 components)
timeFrame: Baseline and 12 months after randomization
measure: Self-Efficacy for Managing Chronic Diseases
timeFrame: Baseline and 12 months after randomization
measure: Number of medication refill gaps (Medication adherence)
timeFrame: Baseline and 12 months after randomization
measure: Length of refill gaps (Medication adherence)
timeFrame: Baseline and 12 months after randomization
measure: Clinic events
timeFrame: Baseline and 12 months after randomization
measure: Risk Score for Recurrent Coronary Heart Disease, Framingham Risk Score
timeFrame: Baseline and 12 months after randomization
measure: Risk Score for Coronary Heart Disease (2-year risk) - First Event, Framingham Risk Score
timeFrame: Baseline and 12 months after randomization
measure: Rate of routine clinical visits and/or other procedures associated with the clinical condition
timeFrame: Baseline and 12 months after randomization
measure: Cost
timeFrame: Baseline and 12 months after randomization
Other outcomes:
Locations:
city: Denver
country: United States
facility: Denver Health
state: Colorado
city: Fort Lupton
country: United States
facility: Salud Family Health Centers
state: Colorado
city: Wheat Ridge
country: United States
facility: STRIDE Community Health Centers
state: Colorado
Study officials:
affiliation: University of Colorado, Denver
name: P. Michael Ho, MD PhD
role: PRINCIPAL_INVESTIGATOR
References: