A novel patient-facing mobile platform to collect and implement patient-reported outcomes and voice biomarkers in underserved adult patients with asthma

一种面向患者的新型移动平台，用于收集和实施服务不足的成年哮喘患者的患者报告结果和语音生物标志物

• 批准号: 10665856
• 负责人: JONATHAN M. FELDMAN
• 金额: $ 13.83万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10665856
• 关键词: novel; patient; facing; mobile; platform

Factors contributing to poor outcomes among minority patients with asthma include poverty and other social determinants of health (SDoH), poor medication adherence and self-management skills, and environmental exposures. There are challenges in providing asthma education in the outpatient setting, such as time constraints and prioritizing acute symptoms or recent exacerbations. The lack of proven, guideline-based, and user-centered mobile platforms that promote self-management and shared decision-making among patients with asthma is an important unmet need. Vocal biomarker technology using machine learning can assess a patient’s respiratory dysfunction and is generalizable to multiple respiratory conditions. On the basis of a 6-second voice sample, this vocal biomarker technology has been shown to detect patients with asthma while correlating with the degree of asthma control. Through an AHRQ-funded study, we recently created the ASTHMAXcel PRO (patient-reported outcome) mobile app for outpatient settings to promote asthma self-management through the collection of PROs, animated videos, goal setting, personalized algorithms, and push notifications. The present study will further enhance our mobile platform’s capabilities to implement PROs by creating ASTHMAXcel Voice. This mobile platform will include a respiratory symptoms risk score based on vocal biomarker technology, facilitate shared decision-making and SDoH screening and referrals, and enable self-management and remote care coordination. We will adapt, test, and refine ASTHMAXcel Voice (R21 phase) for the outpatient setting (Aim 1). We will remotely conduct pre-adaptation focus groups with patients, healthcare providers (HCPs), social workers (SWs), community health workers (CHWs), and expert stakeholders on how to best adapt ASTHMAXcel Voice. We will test the adapted platform with 30 patients, 6 HCPs, 2 SWs and 2 CHWs and conduct formative and summative evaluation of the platform’s functionality and usability, and iteratively refine it based on feedback. We will repeat this process for a second round. We will then remotely conduct an RCT (R33 phase) among outpatient primary and specialty care sites from Montefiore Medical Center to compare the adapted and refined ASTHMAXcel Voice (n=100) to usual care (n=100) on clinical outcomes (asthma control as primary endpoint, asthma emergency department (ED) visits), process outcomes (patient and provider satisfaction and usage, degree of shared decision-making), SDoH screening and referral rates, asthma quality of life (QOL), medication adherence, and self-efficacy (Aim 2). Assessments will occur at baseline, 2-, and 6-month follow-up. We will evaluate the process of ASTHMAXcel Voice implementation within the outpatient setting using the RE-AIM framework (Aim 3). Future enhancements of the mobile platform will include other chronic diseases, risk prediction, and widespread dissemination.

导致哮喘少数族裔患者效果不佳的因素包括贫困和其他社会 确定健康（SDOH），药物依从性和自我管理能力不佳以及环境 暴露。在门诊环境中提供哮喘教育存在挑战，例如时间限制 并确定急性症状或最近的恶化。缺乏基于指南的经验性，以用户为中心的 促进自我管理和共享哮喘患者决策的移动平台是一个 重要的未满足需求。使用机器学习的人声生物标志物技术可以评估患者的呼吸系统 功能障碍，可推广到多种呼吸系统疾病。根据6秒的语音样本， 声带生物标志物技术已显示可检测患有哮喘的患者，同时与 哮喘控制。通过AHRQ资助的研究，我们最近创建了Asthmaxcel Pro（患者报告） 结果）用于门诊设置的移动应用程序，以通过收集专业人士来促进哮喘自我管理， 动画视频，目标设置，个性化算法和推送通知。本研究将进一步 通过创建Asthmaxcel语音来增强我们移动平台实施专业的功能。这个手机 平台将包括基于人声生物标志物技术的呼吸症状风险评分，并促进共享 决策和SDOH筛查和推荐，并实现自我管理和远程护理协调。 我们将为门诊设置（AIM 1）适应，测试和完善哮喘声音（R21阶段）。我们将 与患者，医疗保健提供者（HCP），社会工作者（SWS），远程适应焦点小组， 社区卫生工作者（CHW）和专家利益相关者如何最好地适应asthmaxcel声音。我们将 用30名患者，6个HCP，2个SWS和2个CHW测试适应的平台，并进行操作格式和总结 评估平台的功能和可用性，并根据反馈进行迭代完善。我们将重复 这个过程进行了第二轮。然后，我们将远程在门诊初期进行RCT（R33阶段） 以及来自蒙特菲奥尔医疗中心的专业护理网站，以比较适应和精致的Asthmaxcel声音 （n = 100）在临床结局（哮喘控制作为主要终点，哮喘紧急情况）的常规护理（n = 100） 部门（ED）访问），过程成果（患者和提供者满意度和使用，共享程度 决策），SDOH筛查和转诊率，哮喘生活质量（QOL），药物依从性和 自我效能感（目标2）。评估将在基线，2个月和6个月的随访中进行。我们将评估该过程 使用RE-AIM框架（AIM 3）在门诊设置中的Asthmaxcel语音实现。未来 移动平台的增强将包括其他慢性疾病，风险预测和宽度 传播。