Evaluation of Home-based Sensor System to Detect Health Decompensation in Elderly Patients With History of CHF
Feasibility of Home-based, Ambient Passive Sensor Technology to Provide Early Warning of Health Decompensation by Detecting Deviations in Activities of Daily Living (ADLs) of Elderly Subjects With Diagnosed Chronic Heart Failure
1 other identifier
observational
20
1 country
1
Brief Summary
Sensorum Health (Sensorum) is conducting a pilot study to determine if Sensorum's proprietary passive sensor network can be used to identify signals of early health decompensation in subjects prior to a hospitalization for chronic disease exacerbation or other ambulatory care sensitive conditions. Successful early detection would provide a window of opportunity to intervene outside of the acute setting in future interventional studies.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for all trials
Started Nov 2022
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
Click on a node to explore related trials.
Study Timeline
Key milestones and dates
Study Start
First participant enrolled
November 28, 2022
CompletedFirst Submitted
Initial submission to the registry
May 9, 2023
CompletedFirst Posted
Study publicly available on registry
May 18, 2023
CompletedPrimary Completion
Last participant's last visit for primary outcome
August 1, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
September 1, 2024
CompletedJanuary 16, 2024
January 1, 2024
1.7 years
May 9, 2023
January 12, 2024
Conditions
Outcome Measures
Primary Outcomes (2)
Recall of AI in passive sensor system
Evaluation of AI ability to prospectively detect hospital utilization event
6 months
Precision of AI in passive sensor system
Evaluation of AI ability to precisely predict hospital utilization event
6 months
Secondary Outcomes (2)
Recall of sensor data review by trained nurses
6 months
Precision of sensor data review by trained nurses
6 months
Study Arms (1)
Passive monitoring
No intervention
Interventions
Data collection of clinically relevant signals using home-based sensor system
Eligibility Criteria
Current Patient of PI's clinic at Weill Cornell Medicine
You may qualify if:
- Current Patient at Weill Cornell Medicine
- Aged 55 years or older
- Able to consent
- Documented diagnosis of congestive heart failure (CHF)
- At least 1 of the following prior hospital utilization events in the past 12 months
- Inpatient admission for any reason
- Facility observation stay for any reason
- Emergency Department visit for any reason
You may not qualify if:
- Significant cardiac valvular disease
- End-Stage Renal Disease (ESRD)
- End-Stage CHF
- End-Stage COPD
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Weill Cornell Medicine
New York, New York, 10021, United States
MeSH Terms
Conditions
Interventions
Condition Hierarchy (Ancestors)
Intervention Hierarchy (Ancestors)
Study Officials
- PRINCIPAL INVESTIGATOR
Parag Goyal, M.D., MSc
Weill Medical College of Cornell University
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
May 9, 2023
First Posted
May 18, 2023
Study Start
November 28, 2022
Primary Completion
August 1, 2024
Study Completion
September 1, 2024
Last Updated
January 16, 2024
Record last verified: 2024-01
Data Sharing
- IPD Sharing
- Will not share