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.
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.
Study Type
OBSERVATIONAL
Enrollment
103
Recording of heart sounds using electronic stethoscope
MedStar Washington Hospital Center
Washington D.C., District of Columbia, United States
Impact of EMAS on echocardiogram order rates
Echocardiogram order rates before and after SENSORA implementation, for individual providers and aggregated for the site as a whole
Time frame: 01/17/2022 - 11/30/2023
Impact of EMAS on cardiologist consult order rates
Cardiology consultation referral rates before and after SENSORA implementation, for individual providers and aggregated for the site as a whole
Time frame: 01/17/2022 - 11/30/2023
Impact of EMAS on provider decision-making
Impact of EMAS on provider decision to refer to echocardiogram, cardiologist, or other workup related to cardiac murmur. Measured via a survey administered to each provider after each patient is screened, which asks if SENSORA AI influenced their decision to refer or not to refer. Measured for individual providers and aggregated for the site as a whole.
Time frame: 01/17/2022 - 11/30/2023
Impact of EMAS on patient outcomes
VHD discovery rates before and after SENSORA platform implementation, for individual providers and aggregated for the site as a whole
Time frame: 01/17/2022 - 11/30/2023
Sensitivity and specificity
EMAS' accuracy (sensitivity and specificity) in detecting structural murmur, compared to an annotator panel
Time frame: 01/17/2022 - 11/30/2023
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