Using artificially intelligent text messaging technology to improve American Heart Association's Life's Simple 7 Health Behaviors: LS7 Bot + Backup

利用人工智能短信技术改善美国心脏协会的生活简单7个健康行为：LS7 Bot Backup

• 批准号: 10649884
• 负责人: SHEANA S BULL
• 金额: $ 79.63万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10649884
• 关键词: Adherence; Advocate; Affect; American Heart Association; Architecture; Artificial Intelligence; Attention; Authorization documentation; Behavior; Behavioral; Black race; Blood Glucose; Blood Pressure; Cardiovascular Diseases; Cardiovascular system; Categories; Cellular Phone; Cessation of life; Cholesterol; Chronic; Chronic Disease; Clinic; Clinical; Colorado; Communication; Communities; Competence; County; Data; Data Collection; Decision Making; Diabetes Mellitus; Diet; Disparity; Electronic Health Record; Eligibility Determination; Emerging Technologies; Enrollment; Equity; Family health status; Federally Qualified Health Center; Focus Groups; Future; Goals; Group Interviews; Health; Health Care Costs; Health Personnel; Health Services Accessibility; Health behavior; Health behavior change; Health system; Healthcare Systems; Hispanic; Hospitalization; Hospitals; Hypertension; Improve Access; Individual; Infrastructure; Intervention; Intervention Studies; Intuition; Latino; Lead; Learning; Life; Life Style; Limited English Proficiency; Location; Low income; Methods; Morbidity - disease rate; Myocardial Infarction; Neighborhood Health Center; Outcome; Patient-Focused Outcomes; Patients; Persons; Pharmaceutical Preparations; Pharmacists; Pharmacy facility; Phase; Physical activity; Pilot Projects; Population; Prevention program; Provider; Randomized; Reach, Effectiveness, Adoption, Implementation, and Maintenance; Risk; Risk Factors; Role; Sampling; Self Care; Self Efficacy; Self Management; Smoking; Social Environment; Target Populations; Technology; Testing; Text Messaging; Update; Weight; authority; cardiovascular disorder risk; cardiovascular risk factor; chatbot; clinical care; comparative effectiveness; contextual factors; disorder control; effectiveness outcome; ethnic minority; evidence base; experience; health care service utilization; health disparity; health equity; healthy lifestyle; implementation framework; implementation outcomes; improved; innovative technologies; intervention delivery; intervention mapping; intervention refinement; lifestyle factors; medication compliance; patient engagement; patient population; population based; pragmatic randomized trial; primary outcome; programs; randomized trial; rural patients; safety net; social culture; social health determinants; sociocultural determinant; text messaging intervention; theories; trial design

PROJECT SUMMARY/ABSTRACT Our goal is to improve control of cardiovascular (CV) disease risk factors using a multilevel intervention leveraging cellphone-based text messages integrated within health systems to improve control of American Heart Association’s Life’s Simple 7 (LS7) lifestyle factors (blood glucose, cholesterol, blood pressure, physical activity, weight, diet, and smoking). When uncontrolled, these lifestyle factors lead to common co-existing chronic conditions (e.g., hypertension, diabetes), morbidity, health care costs and death. Patients who experience health disparities (i.e., ethnic minorities, those with limited English proficiency and those with low- income) are disproportionately affected by CV diseases, have worse disease control and suffer greater sequelae. Self-management is an individual’s role in managing chronic disease and has strong evidence of benefit. It includes self-care, lifestyle changes (e.g., increase physical activity), taking medications as prescribed and managing exacerbations of chronic condition(s). Text messaging interventions have improved health behaviors including physical activity and medication adherence. Incorporating behavioral “nudges,” defined as a small change in choice architecture that “alters people’s behavior in a predictable way” into text messages may further augment its impact. Behavioral nudges are more personalized, resonate better with patients, and have changed health behaviors. However, text message interventions have typically not been delivered to large samples, focused on patients experiencing health disparities, nor leveraged health system electronic health record (EHR) data to personalize content and maximize scale, reach and impact of messages. Using a patient-level randomized pragmatic trial, we will test the comparative effectiveness of 3 text messaging delivery strategies: 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. We plan to enroll 6,000 patients from clinics within 3 health systems that care for large populations experiencing health disparities: 1) Denver Health and Hospital Authority, 2), Salud Family Health Centers and 3) STRIDE Community Health Center. We will use health system EHR data to identify eligible patients, deliver the intervention, and assess patient-centered outcomes. The study findings will provide evidence regarding the best population-based strategy for universal delivery to engage all patients with health disparities in self- management to improve the AHA’s LS7. The intervention will be delivered in real world settings to augment routine clinical care and improve access to care. We will incorporate lessons learned from one health system into adaptations for the other health systems in the study.

项目摘要/摘要 我们的目标是通过多层次干预提高心血管（CV）疾病风险因素的控制 利用基于手机的短信集成在卫生系统中，以改善对美国的控制 心脏协会生活的简单7（LS7）生活方式因素（血糖，胆固醇，血压，身体 活动，体重，饮食和吸烟）。当不受控制时，这些生活方式因素会导致共同存在 慢性病（例如高血压，糖尿病），发病率，医疗费用和死亡。患者 经历健康差异（即，少数民族，英语水平有限的人以及低 - 收入）受到简历疾病的影响不成比例，疾病控制较差，遭受更大的痛苦 后遗症。 自我管理是个人在管理慢性疾病方面的作用，并有强有力的福利证据。它 包括自我保健，生活方式改变（例如，增加体育锻炼），服用处方药， 管理慢性病的恶化。文本消息干预措施改善了健康行为 包括体育锻炼和药物依从性。结合行为“轻度”，定义为小 选择“以可预测方式改变人们的行为”的选择体系结构可能会变成短信 进一步增强其影响。行为轻度更具个性化，与患者产生更好的共鸣，并具有 改变了健康行为。但是，短信干预措施通常未交付给大型 样本，专注于经历健康差异的患者，也没有利用卫生系统电子健康 记录（EHR）数据以个性化内容和最大规模，消息的影响和影响。 使用患者级随机务实试验，我们将测试3个文本消息的比较效率 交付策略：1）通用短信； 2）互动AI聊天机器人文本消息利用证据 - 基于关注患者环境和社会文化因素影响自我的沟通策略 管理;或3）交互式AI聊天机器人文本消息传递以及主动的药剂师管理。我们计划 在3个卫生系统中招募6,000名诊所的患者，以照顾大量人群的健康 差异：1）丹佛健康和医院管理局，2），萨鲁德家庭保健中心和3）大步 社区卫生中心。我们将使用卫生系统EHR数据来识别合格的患者，交付 干预并评估以患者为中心的结果。研究结果将提供有关 最佳基于人群的普遍分娩策略，使所有具有健康分配的患者在自我 管理层改善AHA的LS7。干预措施将在现实世界中进行以增加 常规的临床护理并改善获得护理的机会。我们将纳入从一个卫生系统中学到的教训 对研究中其他卫生系统的适应。