- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Outpatient Reimbursement to Increase 65 Percent for EchoGo Heart Failure Platform in 2024
Reimbursement for use of the artificial intelligence (AI)-powered EchoGo Heart Failure platform in hospital outpatient settings for Medicare and Medicaid patients is expected to increase from $99.81 to $284.88 in 2024.
Use of an FDA-cleared artificial intelligence (AI)-enabled system, which reportedly facilitates earlier detection of heart failure with preserved ejection fraction (HFpEF), will generate higher outpatient reimbursement in 2024, according to newly issued coding updates from the Centers for Medicare and Medicaid Services (CMS).
In an update to the ambulatory payment classification (APC) for the Healthcare Common Procedure Coding System (HCPCS) code C9786, the CMS has increased reimbursement from $99.81 to $284.88 for use of the EchoGo Heart Failure system, according to Ultromics, the manufacturer of the platform. The increased reimbursement for the device will go into effect on January 1, 2024.
The EchoGo Heart Failure platform, which received FDA 510(k) clearance in December 2022, reportedly diagnoses HFpEF through analysis of a single echocardiogram view. An August 2023 study noted a 95 percent area under the receiver operating characteristic curve (AUC) in validation testing for HFpEF detection.
“Approximately 50 percent of non-invasive cardiac imaging tests are performed in office-based settings so there is exciting potential for this reimbursement decision to unlock new opportunity to further broaden adoption of our technology,” added Ross Upton, the CEO and founder of Ultromics.
Study: AI Boosts Ultrasound AUC for Predicting Thyroid Malignancy Risk by 34 Percent Over TI-RADS
February 17th 2025In a study involving assessment of over 1,000 thyroid nodules, researchers found the machine learning model led to substantial increases in sensitivity and specificity for estimating the risk of thyroid malignancy over traditional TI-RADS and guidelines from the American Thyroid Association.
Can CT-Based AI Provide Automated Detection of Colorectal Cancer?
February 14th 2025For the assessment of contrast-enhanced abdominopelvic CT exams, an artificial intelligence model demonstrated equivalent or better sensitivity than radiologist readers, and greater than 90 percent specificity for the diagnosis of colorectal cancer.
