Chronic Obstructive Pulmonary Disease Clinical Trial
Official title:
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 Disease
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.
Status | Recruiting |
Enrollment | 100 |
Est. completion date | June 6, 2024 |
Est. primary completion date | June 6, 2024 |
Accepts healthy volunteers | No |
Gender | All |
Age group | 65 Years and older |
Eligibility | Inclusion Criteria: - Aged 65 years or older - Able to consent - Documented history of diagnosis of chronic obstructive pulmonary disease (COPD) and/or congestive heart failure (CHF) - Currently admitted to JSUMC for observation or as an inpatient with any diagnosis =1 prior hospital utilization events with any diagnosis (inpatient admissions, facility observation stays, or ED visits) in the past 12 months Exclusion Criteria: - Significant cardiac valvular disease - End-Stage Renal Disease (ESRD) - End-Stage CHF - End-Stage COPD |
Country | Name | City | State |
---|---|---|---|
United States | Jersey Shore University Medical Center, Hackensack Meridian Health | Neptune | New Jersey |
Lead Sponsor | Collaborator |
---|---|
Sensorum Health Inc. |
United States,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Recall of AI in passive sensor system | Evaluation of AI ability to prospectively detect hospital utilization event | 90 days | |
Primary | Precision of AI in passive sensor system | Evaluation of AI ability to precisely predict hospital utilization event | 90 days | |
Secondary | Recall of sensor data review by trained nurses | Evaluation of nurse ability to prospectively detect hospital utilization event | 90 days | |
Secondary | Precision of sensor data review by trained nurses | Evaluation of nurse ability to precisely predict hospital utilization event | 90 days |
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