Study shows economic benefit of AI cardiovascular decision-making tool

Artificial intelligence has great potential to improve patient outcomes. Researcher Dr. Joon Lee, PhD, focuses on developing precision medicine AI tools to help with cardiovascular decision-making. 

He recently published an article in Nature Digital Medicine showing the economic benefits of using Revaz AI, a tool developed by his team that supports treatment decision-making for patients with obstructive coronary artery disease. 

“We found that if clinicians used Revaz AI, 72.4 per cent of actual treatment decisions could have shifted,” says Lee. “That means that many treatment decisions made were likely suboptimal from a health economic perspective.” 

The simulation study, which included 25,942 Alberta patients with obstructive coronary artery disease, considered both projected quality of life and health care costs for each patient over their lifetime. It revealed an average cost savings of $22,960 USD per patient and an average quality-adjusted life year (QALY) gain of $22,439 USD.

There are three main treatments for coronary artery disease: stents, bypass surgery or medication. Choosing between them, while taking into account patient preferences and other complexities, isn’t always straightforward, as it depends on factors like blockage severity, patient health, and long-term risk.

Revaz AI helps solve this problem by supporting clinicians and patients in making more informed treatment decisions. It uses personalized data from patients who have undergone coronary angiography, imaging used to find blockages, to predict short- and long-term adverse cardiovascular outcomes and mortality. 

Lee’s retrospective study simulated 1,500 possible outcomes per patient across the three treatment options to estimate long-term health economic impacts.

Lee is excited about the results and about the potential of AI in healthcare. 

“AI is capable of making complex calculations that no human is capable of, and although it can’t replace physicians, it has the potential to optimize treatment decisions at the health system level by reducing costs from complications and improving patient outcomes,” says Lee.

Dr. Joon Lee is the director of the Data Intelligence for Health Lab and a professor in the Departments of Cardiac Sciences & Community Health Sciences at the Cumming School of Medicine, University of Calgary. He is a member of the Libin Cardiovascular Institute and the O'Brien Institute for Public Health.