Real-World Evaluation of Eko Murmur Analysis Software in a Point of Care Setting
Purpose
The purpose of this research is to evaluate the impact of Eko AI plus EMAS (Eko Murmur Analysis Software) on a clinician's referral decision in a real-world primary care setting. There is an additional objective of understanding patient outcomes when patients are referred for cardiology follow-up and/or echocardiogram.
Conditions
- Murmur, Heart
- Innocent Murmurs
- Heart Murmurs
- Pathologic Murmur
Eligibility
- Eligible Ages
- Over 50 Years
- Eligible Genders
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- Patient verbally consents to participation - Patient is willing to have heart sounds recorded with an electronic stethoscope - Patient is age 50 years or older
Exclusion Criteria
- Patient is unwilling or unable to give verbal informed consent - Patients experiencing a known or suspected acute cardiac event - Patient is under the age of 50 years old
Study Design
- Phase
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Arm Groups
| Arm | Description | Assigned Intervention |
|---|---|---|
| Prospective cohort | Patients who are at least 50 years of age during their primary care exam will undergo SENSORA™ screening if they provide consent. |
|
| Retrospective cohort | Patients who saw participating providers in the 6 months prior to study start date, and who were referred to echocardiogram and/or cardiology, will be included as provider self-control for patient outcomes and referral rates. |
|
Recruiting Locations
Washington, District of Columbia 20010
Theresa Moriarty, MSN, RN
More Details
- Status
- Recruiting
- Sponsor
- Eko Devices, Inc.
Detailed Description
Eko has developed a platform to aid in screening for cardiac conditions using a digital stethoscope and machine-learning algorithms to detect the presence or absence of heart conditions such as heart murmurs and atrial fibrillation. In June 2022, the US Food and Drug Administration (FDA) granted Eko a 510(k) clearance for the marketing of "Eko Murmur Analysis Software" (EMAS), a set of machine learning algorithms that are able to screen signal quality and identify fundamental heart sounds, distinguish structural murmurs from absent or innocent murmurs, and provide a structural murmur's timing in the cardiac cycle. This study sets out to evaluate the impact of EMAS on a clinician's referral decision in a real-world primary care setting, with the additional objective of understanding patient outcomes when patients are referred for cardiology follow-up and/or echocardiogram. Providers will receive access to the EMAS screening tool, called the SENSORA™ Disease Detection Platform, which features the FDA cleared 3M™ Littmann® CORE stethoscope paired with the FDA cleared SENSORA™ enterprise application and EMAS AI running on an iPad, which is mounted on a Tryten stand. SENSORA™ will be used by medical assistants or equivalent as part of the initial patient intake process (e.g., during vitals acquisition). EMAS influence on individual providers will be assessed by reviewing each provider's number of referrals to cardiology and number of echocardiogram orders for the 6 months preceding study start. These values will be compared to cardiac referral and order rates at the end of the study. Patient outcomes data (e.g., cardiology appointment notes, echocardiogram findings, follow up visits scheduled) will be pulled 6 months after the patient is seen by their primary care provider. Secondary objectives include the continued assessment of algorithm performance on a point-of-care population.