In January, we published a modular content piece on artificial intelligence in cardiovascular care. Shortly after, we saw Cigna remove prior authorization for HeartFlow Fractional flow reserve-computed tomography (FFR-CT). Similarly, the National Health Service (NHS) in England and NHS Improvement mandated the adoption of HeartFlow Analysis to fight coronary heart disease. This mandate will begin on April 1st and aims to provide medical devices and software to NHSE patients faster. This mandate is a key attempt to improve patient care and reduce costs. The program seeks to accelerate the uptake of digital healthcare innovations by removing financial barriers.
Access NHS England and NHS Improvement’s mandate and more information about HeartFlow here.
Why is this important?
Like many artificial intelligence (AI) applications in clinical care, FFR-CT has traditionally been held back from widespread adoption by lack of proven quality outcomes and reimbursement. These two announcements signal that FFR-CT has proven outcomes and that providers can make the investment with greater confidence that they will be paid.
Additionally, cardiac imaging volumes have declined as a result of Covid-19, and many patients aren't receiving necessary care, which can adversely affect outcomes in the near future. Patients will be steered to interventional procedures more quickly because of avoided care challenges. FFR-CT can more accurately diagnose if a patient requires an intervention for blocked arteries, reducing the need for diagnostic cath or percutaneous coronary intervention (PCI) in many patients.
The software in turn limits redundant non-invasive diagnostic testing, reduces patient time in the hospital and face-to-face clinical contact, and helps ensure that hospital visits for those who do need them are streamlined, which is particularly crucial during the Covid-19 pandemic.
Because FFR-CT has higher diagnostic capabilities and allows for earlier screenings, we hope to see better outcomes and lower episodic costs as more insurance plans move towards coverage.
What does this mean for CV imaging leaders? This could just be the beginning.
Through large amounts of imaging data, AI machines can discover hidden patterns to show imaging derived traits that can be used as predictors for cardiovascular diseases and conditions. FFR-CT is just one way AI enabled technology can improve or impact cardiovascular care. AI can be used for risk stratification, diagnoses and chronic care management, remote patient monitoring, and more.
CV leaders need to prepare and position themselves for a future where these technologies are more prevalent, as well be able to prove quality outcomes with these technologies to appeal to payers. In the coming years, we’re likely to see continuing improvements in cardiovascular imaging and the way it generates clinical information through AI.