Dynamic Heart Failure Prediction With Real-time Functional Status Data in the Ambulatory Setting
| Status: | Not yet recruiting |
|---|---|
| Conditions: | Cardiology |
| Therapuetic Areas: | Cardiology / Vascular Diseases |
| Healthy: | No |
| Age Range: | 18 - Any |
| Updated: | 10/12/2018 |
| Start Date: | May 2019 |
| End Date: | December 2020 |
| Contact: | Katherine Ramsey |
| Email: | katherine.ramsey@ucsf.edu |
| Phone: | 415-476-1000 |
Dynamic Prediction of Heart Failure Using Real-time Functional Status and Electronic Health Record Data in the Ambulatory Setting
Heart failure is the number one cause of hospital readmission in those over 65 years of age
and the current standard-of-care of weight self-monitoring is inadequate to predict
exacerbation. This project aims to improve the monitoring of heart failure disease
progression through the use of real-time, up-to-date data obtained both from a smart
phone-based tool and from the electronic health record. The goal is to develop a low-risk,
clinically validated method to estimate dynamic heart failure risk to enable the provision of
earlier, more effective outpatient interventions that decrease hospitalization.
and the current standard-of-care of weight self-monitoring is inadequate to predict
exacerbation. This project aims to improve the monitoring of heart failure disease
progression through the use of real-time, up-to-date data obtained both from a smart
phone-based tool and from the electronic health record. The goal is to develop a low-risk,
clinically validated method to estimate dynamic heart failure risk to enable the provision of
earlier, more effective outpatient interventions that decrease hospitalization.
Inclusion Criteria:
- Hospitalized for decompensated heart failure
- Age >=18 years
- Owns a smart phone
- Willing to measure self assess 6 minute walk test weekly
Exclusion Criteria:
We found this trial at
1
site
San Francisco, California 94143
Principal Investigator: Geoffrey tison, MD
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