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Noninvasive Adherence-independent Longitudinal Remote Chronic Disease Monitoring and Exacerbation Inference

无创、不依赖依从性的纵向远程慢性病监测和恶化推断

基本信息

批准号：
9896693
负责人：
Kevin R King
金额：
$ 23.63万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-02-20 至 2022-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9896693
关键词：
Acute Acute myocardial infarction Adherence Affect Ambulatory Care Area Atrial Fibrillation Back Beds Biological Markers Body Weight Changes Cardiac Cardiopulmonary Chronic Chronic Disease Chronic Obstructive Airway Disease Clinical Trials Communication Congestive Data Development Disease Management Diuresis Dyspnea Effectiveness Exertion FDA approved Family Feedback Floor Friends Goals Guidelines Health Health Insurance Portability and Accountability Act Heart Heart Diseases Heart Rate Heart failure Home environment Hospitalization Hospitals Hour Implant Intravenous Learning Leg Length of Stay Liquid substance Lung Lung diseases Measurement Measures Medicare Methods Monitor Nature Notification Outpatients Paroxysmal Dyspnea Patient Care Patients Persons Pneumonia Prevention strategy Pulmonary Heart Disease Pulmonary artery structure Recommendation Recurrence Reporting Respiration Risk Self Care Shortness of Breath Specialist Spouses Symptoms System Tachyarrhythmias Technology Testing Text Text Messaging Underserved Population Visualization Vulnerable Populations Weighing patient Weight Weight Gain base clinical biomarkers cloud storage cohort cost estimate data exchange design falls feeding force sensor high risk hospital readmission implantable device improved innovation monitoring device pressure sensor programs prototype readmission rates respiratory sensor tool transmission process web portal

项目摘要

Abstract: The 30-day hospital readmission rate in the U.S. exceeds 3 million patients per year with cost estimates exceeding $40B. More than 10% of these hospitalizations are considered preventable. Chronic and recurrent cardiopulmonary diseases (heart failure, pneumonia, COPD, cardiac dysrhythmias, acute myocardial infarction) are among the most common causes of rehospitalization. Heart failure alone affects more than 6 million US patients, is responsible for >1 million hospitalizations annually, and is associated with remarkably high hospital readmission rates (~25% at 30 days; ~50% by 6 months). Intense focus has centered on improving outpatient disease management using remote monitoring during vulnerable periods (immediately after hospital discharge) and in vulnerable underserved populations. Despite its promise, the utility of remote health monitoring has been limited by lack of adherence to patient self-measurement and data transmission. Even implantable devices often require patient-initiated data transmission. We propose a noninvasive and fully adherence-independent in-home monitor of cardiopulmonary clinical biomarkers with fully automated data transmission. By overcoming the compliance barrier, the sensing platform enables reliable longitudinal measurement with potential to infer signatures of impending hospitalizations. The proposed R21 will 1) deploy the technology into the homes of patients discharged after a hospitalization for heart failure exacerbation with volume overload, and 2) perform longitudinal monitoring to generate data that will be used for inference and patient feedback. If successful, this real-world pilot data will inform design of a formal observational trial to infer signatures of chronic disease decompensation and impending need for hospitalization.

摘要：美国每年30天的再入院率超过300万患者，费用估计超过400亿美元。其中超过10%的住院被认为是可以预防的。慢性和复发性心肺疾病（心力衰竭、肺炎、COPD、心律失常、急性心肌梗死）梗塞）是再住院的最常见原因。仅心力衰竭就影响超过6 每年有超过100万的美国患者住院，并且与较高的再入院率（30天约为25%; 6个月约为50%）。集中精力集中在在脆弱时期利用远程监测改善门诊疾病管理（立即出院后）和服务不足的弱势群体。尽管它的承诺，远程健康监测由于缺乏对患者自我测量和数据传输的坚持而受到限制。即使是植入式设备也经常需要患者发起的数据传输。我们提出了一种非侵入性且完全具有全自动数据的心肺临床生物标志物的非依从性家庭监测器传输通过克服合规性障碍，传感平台能够实现可靠的纵向测量具有推断即将住院的特征的潜力。拟议中的R21将1）部署该技术进入因心力衰竭恶化住院后出院的患者家中，容量过载，以及2）执行纵向监测以生成将用于推断的数据，患者反馈。如果成功，这些真实世界的试验数据将为正式的观察性试验设计提供信息，慢性疾病失代偿的特征和即将需要住院治疗。