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.
