Exploring AI’s Impact on Oncology Payment Reform and Health Equity

In an interview with Pharmacy Times® at the Community Oncology Alliance (COA) 2024 Payer Exchange, Glenn Balasky, executive director at Rocky Mountain Cancer Centers in Colorado, spoke about the potential for AI to influence payment reform, health care disparities, and the transition to a value-based care model.

Pharmacy Times: What were the most significant discussions in your session AI?

Glenn Balasky: The biggest discussion we had about AI at this morning's meeting was that it's a new subject. So, there's a lot to happen, a lot to evolve. Dan Lodder, my colleague, who I've known for a number of years, has worked with technology that I think is going to bring more intelligence and information to us that comes from the payers. Another presenter had a much more consumer aspect and is looking forward to how AI can impact consumer access and what's going on with the practice. I think it's a little bit of a wait and see what happens, as far as what will influence how AI can impact and enhance the work we do in a large oncology practice.

Pharmacy Times: What aspects of payment reform do you think will be most influenced by AI technologies?

Balasky: My hope would be, and with an uncertain future, is that payment reform will come about by AI starting to see and show what treatments, which providers, who's doing the right things to deliver the best medicine. Not only is it economically viable, hopefully it'll be demonstrated to be what's most clinically viable. I think whether the payor has that story, or a large provider that's part of a large network like we are. If we have that story, if we have that information, then it can be used to definitely improve the value of the cancer care that we deliver, but ultimately should improve the clinical effectiveness of it as well.

Pharmacy Times: What are some key challenges to implementing AI?

Balasky: What we talked about a little bit towards the end of the panel, I think the number one challenge is going to be can you put information to make decisions in the hands of the physician when they need to make the decision. We were very used to treatment guidelines today, where our doctors are prompted what treatments to use based on established guidelines, but that information is static. It doesn't tell us that 50% or 60% of a treatment are being used over another treatment. So hopefully we can get more dynamic as AI evolves, that they can keep up with the ongoing changes that happen in cancer care, literally daily.

Pharmacy Times: How can AI help oncology care providers move from fee-for-service to value-based care?

Balasky: I think AI would help in 2 ways today. I think those of us that have gotten sophisticated in value-based care are doing all the right things to make more positive treatment choices based on economics and clinical effectiveness. But could AI make us even that much better so that we're taking out some of the guesswork we have in medicine out of some of our care choices. I think AI could also help with when is treatment not working, and [when we] should we pivot to something different. If we make that pivot sooner, that's less expensive, or if treatment is not working at all, can we work with the patient as far as providing the right glide path for end of life, if that's what's appropriate, the sooner, the better. Those are some of our tougher challenges in value-based care today. Are we really optimizing our initial treatments, and are we best managing what goes on and the end of life?

Pharmacy Times: What role can AI play in addressing healthcare disparities in oncology?

Balasky: I think AI could help in healthcare disparities, if the right intelligence and algorithms and information are applied to help discern from the data. Unless you go through a very timely interview with a social worker or somebody of that skill set with a patient, you won't know about their disparities. It doesn't show up necessarily on a patient enrollment form or the initial come to clinic type of information that we provide. So the idea that AI could screen data, just like we've talked about clinically, it would be great if it could screen data to know what's going on. But in this area, I think there could be an opportunity to find those disparities and those issues by bringing everything from zip codes, addresses, as well as certain aspects of the patient's perspective on care that otherwise would be very complicated for even a talented human being to read through, and find a given volume of patients and the number of people we see, I do think AI is going to help in helping to manage and identify symptoms.

Pharmacy Times: Looking ahead, what do you see as the future of AI in oncology payment reform, and what innovative solutions are on the horizon to better support cancer care?

Balasky: I do think we will get to a world where people using their phone will report what's going on and, and that might help determine they got to go to their pharmacy. They need to call us and help nudge that decision making to [remain close] with the patient. If patients report their outcomes that will go into our care story, along with the medicines and the treatments and how they're performing. And then I could see a lot of help and support on the business side. We're dealing with high-cost drugs and high-cost treatments. Can AI make sure that we're making the best and most appropriate economic choices when it comes to those areas?