SCC-PG: Just in Time Intervention for Patients with Chronic Heart Diseases in Arizona tribes

SCC-PG：对亚利桑那州部落慢性心脏病患者进行及时干预

• 批准号: 2125643
• 负责人: Fatemeh Afghah
• 金额: $ 15万
• 依托单位: Northern Arizona University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-10-01 至 2022-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2125643&HistoricalAwards=false
• 关键词: SCC; PG; Just; Time; Intervention

Cardiovascular diseases are the leading cause of death in the United States. Cardiovascular diseases are often chronic conditions that involve several costly emergency visits or long hospitalizations for the patients. Limited access to medical facilities in rural communities can result in worse health outcomes for these patients, in particular, the American Indian (AI) patients living in remote and rural areas. A considerable number of Arizonan AIs with cardiovascular conditions may be at risk of missing the window of opportunity for effective treatment and experiencing a lower chance of survival because of living far away from medical service providers. Arizona has the third largest population of Indian Americans who live in rural, tribal and often extremely isolated areas. The cardiac patients living in these areas do not have the required timely access to care, in particular to specialty services like cardiologists. Therefore, an important challenge related to these conditions for rural patients is the ‘early detection of deterioration in symptoms’, which is critical for ‘just in time’ interventions. This planning project is a collaborative effort among the Northern Arizona University (NAU) and University of Michigan (UM) as well as community leaders in rural and tribal health to discuss the best strategies to utilize an integrated remote heart monitoring system to benefit the patients with chronic heart conditions who live in rural, remote and isolated tribal areas.This planning project offers several innovative approaches by working with the tribal AI community to begin(i) Developing a new remote heart monitoring technology to predict the deterioration of the symptoms and occurrence of critical heart conditions in patients with some common chronic cardiac conditions such as atrial fibrillation and congested heart failure. Several remote heart monitoring systems have focused on reliable detection of such events, however by the time that the device alerts the patients or their family, it is already too late to seek medical help for the patients who live in rural and remote areas. Hence, our early prediction framework can give the patients enough time to seek medical assistance. This system can also help caregivers control severe symptoms, reduce readmissions, and reduce the cost associated with care; (ii) Developing deep learning-based and Markov-based prediction methods; and (iii) Developing on-device prediction methods that can work independently of the cloud in order to service the patients with no access to broadband internet. This study can be replicated for a wide range of other diseases and medical conditions and in different geographic regions.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

心血管疾病是美国死亡的主要原因。心血管疾病通常是慢性疾病，涉及多次昂贵的紧急就诊或长期住院治疗。在农村社区获得医疗机构的机会有限，可能会导致这些患者的健康状况较差，尤其是居住在偏远和农村地区的美洲印第安人（AI）患者。由于远离医疗服务提供者的生活，因此有大量具有心血管疾病的亚利桑那州AI可能会丢失有效治疗的机会之窗，并经历较低的生存机会。亚利桑那州是居住在农村，部落和通常非常孤立的地区的印度裔美国人第三大人口。居住在这些地区的心脏病患者无法及时获得护理，尤其是心脏病专家等专业服务。因此，与这些条件相关的重要挑战是“早期检测症状的检测”，这对于“及时”干预至关重要。该计划项目是亚利桑那大学（NAU）和密歇根大学（UM）的一项合作努力，以及农村和部落健康的社区领导者，讨论利用综合远程监测系统的最佳策略，使他们在农村，远程和孤立的部落中生活的慢性心脏病的患者受益于遥远的部落计划，以开发新的计划，以开发一些Innov nignalive Innove Innove Innoveration Innove nii（I I Innove nii），这是Inove Innove nii（I I Innove nii nii），这是II（I I Innov），这是Inove Innove nii（I I Innove nii norke nii nii），这是II（I I Innov）。预测患有某些常见慢性心脏疾病（例如心房颤动和拥挤心力衰竭）患者的症状定义和关键心脏病的发生。几个远程心脏监测系统的重点是对此类事件的可靠发现，但是到设备提醒患者或其家人时，为生活在粗糙和偏远地区的患者寻求医疗帮助已经为时已晚。因此，我们的早期预测框架可以为患者提供足够的时间寻求医疗援助。该系统还可以帮助护理人员控制严重的症状，减少再入院并降低与护理相关的成本； （ii）开发基于深度学习和基于马尔可夫的预测方法； （iii）开发可以独立于云的设备预测方法，以便为无法获得宽带互联网的患者提供服务。这项研究可以针对多种其他疾病和医疗状况以及不同地理区域进行复制。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为通过评估被认为是宝贵的支持。