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Using AI Text Messaging to Improve AHA's Life's Essential 8 Health Behaviors

University of Colorado Denver (CU Denver) logo

University of Colorado Denver (CU Denver)

Status

Enrolling

Conditions

Lifestyle Factors
Cardiovascular Diseases

Treatments

Behavioral: Interactive AI chatbot text messaging
Behavioral: Proactive pharmacist support
Behavioral: Generic text messages

Study type

Interventional

Funder types

Other
NIH

Identifiers

NCT06324981
1UG3HL168504 (U.S. NIH Grant/Contract)
22-2097

Details and patient eligibility

About

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.

Full 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.

Enrollment

2,100 estimated patients

Sex

All

Ages

18 to 89 years old

Volunteers

No Healthy Volunteers

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.

Trial design

Primary purpose

Supportive Care

Allocation

Randomized

Interventional model

Parallel Assignment

Masking

Single Blind

2,100 participants in 3 patient groups

Generic text messages
Active Comparator group
Description:
The information content for these messages will be derived from trusted sources of medical information and contain links to websites such as American Heart Association. An example of such a message would be: Remember to take your blood pressure today! You can find more information from the American Heart Association by clicking here. Patients will be able to return texts with questions which will be addressed by the study team, including a clinical pharmacist if needed.
Treatment:
Behavioral: Generic text messages
Interactive AI chatbot text messaging
Active Comparator group
Description:
This AI system will utilize NLP and ML to facilitate bi-directional system-patient dialogue with messages that incorporate content utilizing tailoring, behavioral nudges and persuasive messaging as described above. An example message would be: Make a promise to yourself to check your blood pressure today! Your goal is to have the top number at 120 or lower and the bottom number at 80 or lower. Each message will end with a question for the participant that will encourage engagement with the AI conversational chatbot that allows greater opportunity to use theoretical content to engage patient autonomy, competence and relatedness, the mechanisms through which we will impact behaviors.
Treatment:
Behavioral: Proactive pharmacist support
Interactive AI chatbot text messaging + proactive pharmacist management
Active Comparator group
Description:
The AI chatbot will be the same as arm 2 (Interactive AI chatbot text messaging alone). In this arm, however, pharmacists will review patient's baseline LE8 risk factors and proactively contact patients via telephone and/or the EHR patient portal to address any risk factor that is in poor/intermediate health categories. The investigators are proposing proactive pharmacist involvement as a population-based approach to address patients with uncontrolled CV risk factors.
Treatment:
Behavioral: Proactive pharmacist support
Behavioral: Interactive AI chatbot text messaging

Trial documents
3

Trial contacts and locations

3

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Central trial contact

Lisa Sandy, MA

Data sourced from clinicaltrials.gov

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