Medical science and technology are advancing at a rapid pace, opening doors to improvements in care delivery, yet clinicians and patients are both excited and frustrated by the complexity of those changes. Larry A. Allen, MD, FACC, will use today’s Kanu and Docey Chatterjee Keynote to explore how artificial intelligence (AI) and implementation science could be used to improve the delivery of health care.

“I want to talk about AI and machine learning as it relates to broader technology and how that affects scientific discovery, medical innovation and, particularly, implementation – or how we get those discoveries to people in regular practice,” explains Allen, the Kenneth Poirier Endowed Chair and division head for cardiology at the University of Colorado School of Medicine.

Addressing Health Disparities

Despite leading the world in spending on medical care, the U.S. lags behind many other countries in its quality of outcomes, Allen says. While college-educated Americans receive good health care, other groups, particularly Black men and people living in rural areas, have less access to health care and suffer worse health outcomes.

“Ideally, with good implementation and medical science supported by technology, we could do a better job of helping all groups have access to good medical care. I think the rural group is interesting because it is a pretty clear example of how technology could help span that divide,” he says. “With technology, it is possible to reach those patients in ways they previously could not have been reached.”

Using everyday technology supported by implementation science, health care providers could share treatments and knowledge through the internet, video visits or even telerobotics for subspecialty high-end care, Allen says.

Simplifying Complexities of Treatment

AI is a subgroup of technology that could be used to offer more efficient ways to troubleshoot the delivery of health care, Allen says. For example, the average patient with heart failure takes 11 medications a day and often has additional medications for comorbidities such as diabetes, atrial fibrillation, vascular disease or chronic obstructive pulmonary disease.

“If you start thinking about that complexity and trying to navigate it with traditional technology, it becomes pretty mind-boggling,” Allen says. “The promise of AI is that the various machinery and algorithms may be able to tackle some of that complexity automatically.”

AI and implementation science can be used to develop coordinated plans of care that are simpler and more efficient than many treatment plans being used today, he adds.

“It is my hope that through the keynote we will see that AI and other technologies offer some promise for us to do a better job of leveraging the new advances that we have and make sure more Americans can get them – especially those people who are disadvantaged,” Allen says.

Keywords: Cardiology Magazine, ACC Publications, ACC25, ACC Annual Scientific Session