Heart failure (HF) is a type of heart disease that leads to need of admissions to the hospital during worsening of symptoms. These admissions are expensive and very inconvenient for patients. The investigators have previously shown that monitoring of patients with a using a small wearable sensor combined with a mathematical model can detect worsening of HF before the patient needs medical care. In this study the investigators will test whether the remote monitoring and prediction of HF worsening can be used to find out when patients are at risk, change their treatment and avoid a hospitalization. The study will enroll 240 Veterans with HF and randomly assign half of them to monitoring and communication of the information on HF worsening to their medical teams. The investigators hope to find our how to best use this approach in routine care of HF. The investigators also plan to determine if this approach will indeed led to less admissions to the hospital among these patients, shorter hospital stays and better quality of life.