Ryan Haumschild, PharmD, MS, MBA: Based on some of the discussion we’re having from a payer’s perspective, when I think of [multiple myeloma] as a cancer center leader, I use real-world evidence. I use EMR [electronic medical recording] data. I use some of the claims data. I look at trends. I pull an ICD-10 [International Classification of Diseases, 10th revision] code and look at total cost of care. I look to see which patient is most appropriate, based on a frailty score, to go to CAR [chimeric antigen receptor] T cells vs a BCMA therapy in the relapsed/refractory stage. That’s some of the decision-making we bring forward as part of our formula approval. But as I start to look at the payer landscape, I don’t want to say the buck stops with you, but a lot of these agents are using the community center. Sometimes you’re the one who has to make this determination if you’re going to restrict use because they may not make that same decision. They may not have that total cost-of-care implication. How do you go about it? Do you leverage real-world evidence from some of your claims data to stratify patients based on these treatments? Or if you don’t do that now, do you see it in the future?

Jay Weaver, PharmD, MPH: That’s a great question. It’s funny. As we were having this conversation, I was going through evidence-based medicine training years ago. At that time, this survey—gathering observations and objective research—was thought of a little lower in the hierarchy of evidence. Here we are, finally having a sober dialogue around it. The foundation of these data is that we would trust a health care provider to ask a patient a piece of information and to tell us that information on assessment. That’s reliable. But we wouldn’t trust asking the patient directly. It’s an interesting evolution. If you think about it that way, we’re probably diluting the data sometimes. We have thoughtful, smart clinicians who are able to be more precise with the answer they’re digging into. But at the end of the day, we’re still playing a telephone game when we start taking information and dropping off a bunch of places.

To answer your question, yes, we’re doing some work to begin digging through some of the information we see. How many people stay on these regimens? Do they complete them? Do we put together a database of all the people seeking certain types of therapy, including CAR T being? What therapies are they receiving? What are the diagnoses? What other therapies are they taking? What centers are they receiving them at? Are we seeing readmissions? Are we seeing other things on the back end? We’re beginning to gather our own data sets.

Meanwhile, we’re keenly interested in the data sets coming out of more structured places, larger data pools, and our plan. They come from the manufacturer or other like-minded organizations that may be larger than us. We’re probably in the infancy of it, but we’re excited about our ability to pull this in and understand what’s happening and then cycle that information back to our decision-making. We’ve put into our P&T [pharmacy and therapeutics] and business committee process a loop in which we’re going to look at how these therapies are performing, how people are doing. Then we bring that back and say, “Do we need to rethink these decisions?”

We talked about the stratification and utilization management and cycling those decisions back. “We made this decision. What happened? Was that good?” Maybe we’re having several appeals of decisions. It’s not our position to create administrative burdens. If someone is going to get the therapy anyway, then let’s move it further up and get it to them faster. We’re trying to learn from all those pieces of information, both administrative and real-world evidence, to make better decisions faster around this. Then we’ll know when we need to pivot and rethink our strategy.

This transcript has been edited for clarity.