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.
Chronic diseases of the heart and lungs (e.g. heart failure) are responsible for a tremendous number of hospitalizations and hospital readmissions. This proposal aims to perform real-world testing of our recently developed non-invasive fully adherence-independent outpatient under-bed sensors. Our long term goal is to improve outpatient management of chronic diseases by learning the changes that characterize chronic disease exacerbation leading to hospitalization and hospital readmission.
