Transcript: The Value and Opportunity in Individualized Cancer Care: Part 2

Gordon: Hi, my name is Gordon Kuntz. We're back with part two of the value and opportunity in individualized cancer care. Today we have Dr Brian Loy, who is the physician lead for oncology, laboratory, and personalized medicine at Humana.

We also have Tushar Pandey, who is the CEO of SimBioSys, a precision medicine company using a novel simulation technology to enable individualized treatment planning. If you haven't already watched part one, please catch up with that. Otherwise, we're going to jump in with part two of the value and opportunity in individualized cancer care.

Let's shift the conversation a little bit towards the reimbursement and business side of the topic. Bryan, if you could tell us about the reimbursement landscape and payer perspective on precision medicine, diagnostics especially, and especially as it relates to clinical decision support?

Dr Loy: Let me, again, preface by saying if we're talking about laboratory and diagnostics, that's largely still in the fee-for-service world. You perform a test, we pay you for it. We have policies to say where we think it's medically appropriate or medically necessary versus not.

Nothing really innovative there. We've had conversations with innovators. We've had conversations with well-established companies on what could that look like. The payment model today basically was established in such a way that if you do something, you demonstrate that you've done it, we agree, you get paid for it.

If you were to turn that on its head and then began to ask, "Okay, so what could a different payment model look like and what would that solve for," that really demands that you identify what problems you're solving for.

In some cases, and I'll call out first-line metastatic non-small cell lung cancer, for example, we've got pretty good evidence out here that folks should be tested for EGFR, ALK break-apart before we start an IL, for example. Preventing harm might be a very laudable goal just in making sure that those types of tests are performed.

In a fee-for-service model, you really don't have the opportunities to influence that. Health plans typically don't call up folks and say, "Why didn't you do something?" We're answering the question of, "Is it covered? Is it not covered? Will you pay my claim?"

If we're thinking about solving for the adoption problem, meaning shouldn't all candidates for metastatic non-small cell lung cancer therapies get that test, then we've got to think about differently putting some of the accountability out into the ecosystem and perhaps across the team up here to be able to say, "What are we doing to make sure that our members are getting the appropriate testing?

Are they getting it the right time? Are they getting good technology? Are the results getting back to the right hands? Are they acting on those results rationally?" We don't have those mechanisms in fee-for-service. It becomes very difficult for us to be able to apply those.

If you've got a payment model in mind, or some iteration, there's an infinite number of hybridizations and iterations of payment models, then you can get to "How does that payment model help you solve for those problems?" You have to clearly identify the types of problems that you're looking for to begin with.

Gordon: Personalized medicine, obviously, there's an expense of the testing. Sometimes it's not a small expense. The therapies that are often directed by the testing are very targeted, and sometimes very, very expensive.

In terms of that testing and that additional analysis that would go on prior to defining a treatment plan, how did you think about that as a payer in terms of those highly personalized diagnostics, in terms of value to you? You were talking about different payment models and that sort of thing.

Even in today's world, how do you assess the value of a particular test vis-à-vis the potential for it coming back to say, "This treatment would not be effective or might be more effective for a particular patient, and if we determine that it's unlikely to be effective, we might be able to avoid that ultimately unsuccessful and unnecessary cost"?

How do you that math, if you will?

Dr Loy: If you're looking for the price of the test, how do we arrive at that? Many of those methodologies are presented to us and we get to react to them.

Or, if there are payment methodologies, say from already recognized spaces like the Clinical Lab Fee Schedule, for example, shows up and we're contracted to pay in accordance with, again, a recognized fee schedule like Medicare, there's methods around that.

What you're really asking from the essence of your question is what might we do differently and how might that be valued? Again, for the sake of discussion, let's all agree that there's something clinically meaningful that happens here that wouldn't otherwise be gotten to from the existing, I'll call it, determinants.

In cancer, for example, if I can look under the microscope, and I can do a few cell surface markers on a protein assessment and get my answer, I don't need molecular diagnostics to answer that question. If I'm using a comparator, then I might not be willing to pay more than what already works for me.

Similarly, if I've got other nonlaboratory tests, and I can get that information through some risk assessment, risk stratification, through patient history or other comorbidities, for example, and this incrementally doesn’t really inform my decision, probably not willing to pay for it as much.

If I've got an unmet need, or if I have a situation where I have a lot at stake in terms of toxicity or making sure that I've got the patient on the right therapy the first time and they're more likely to benefit, and they've got poor performance status, I might only get one bite at that apple. It becomes very valuable, especially in a setting where, again, I've got high toxicity profiles.

Much of my answer would be predicated on what does the clinical utility look like from a total member experience, because it's not all about the drug. If we can use these tests to keep people out of a hospital and avoid complications and deterioration, that becomes valuable from a total experience perspective.

All things being equal, if I'm just talking solely about the drug, then I began to say, "What does this bring to me in selecting or deselecting versus what alternatives I might have and use those alternatives as my basis?" Finally, if there's utility in deciding whether to treat or not to treat at all, will the patient benefit for treatment? I think you have a whole different discussion.

We've got pretty good history where folks have relied on, "What was the value of the chemotherapy regimen that was foregone and that we spared the patient?" as a basis. Those are some of the thought processes underlying that.

Gordon: I see. I guess what I'm hearing you say in part is your decision is maybe not as simple as I had laid out the question, which is sort of an ROI calculation. If we do this test on 10 patients and the test costs $5000, that's $50,000 we've invested in finding out more about these patients.

If we think we can save because of that, avoid $100,000 treatment for one of those patients, that sounds like a good deal to me as a payer. It sounds your calculus is not ignorant of costs but really around the quality.

If you're able to reduce toxicities, that's good quality, which also implicates savings. Also, if you're able to avoid therapies that, again, would have been ineffective, that's good quality, too, that reduces cost.

Dr Loy: I'm really reflecting somewhat from an idealistic perspective. I would just tell you. Again, we live in a fee-for-service world. Some of what I'm saying, we don't have tangible examples of what we're doing today, but I'm really reflecting on a lot of conversations that I've had with folks who've thought creatively of, "How do we get the maximum amount out of the test and the correct adoption and accelerate the appropriate adoption once we're convinced that we've gotten good utility here?"

My thinking becomes, "Tell me what, first and foremost, value does this bring to the patients?" If I have a disease process, of which there are a lot, and I have a test—you can put a dollar value on it, but thousands of dollars—and it's only going to pick up 1% of the patients. That 1% is going to tell me that they're eligible for a drug that's going to give them either no survival benefit or uncertain survival benefit.

It's really not compared to a standard of care where I know a little something about it. Why do we test at all? Unless you can demonstrate some value, why would we want to pay for it?

That same test in a different tumor type might provide me more informative and valuable information that would in a different scenario help me avoid toxicity or I might not have an alternative. I think there's a number of situations that we're still exploring, but I think that we've got to bring those types of topics to the innovators and try to find out where we need to go explore and solve the problems that exist in our current treatment regimens.

Rather than just saying here is a mutation profile for a tumor and do what you might do with the results. We've got druggable targets now. I think we've got to be much more thoughtful and aimed towards meaningful end points.

Gordon: Got it. Tushar, how does SimBioSys do its role in creating value? Let's define that simplistically as better quality at lower cost around cancer care.

Tushar: It's threefold. Prior to founding SimBioSys, I spent a decade debunking the myth that better care is more expensive. That's the thought process. You spend more, that means care is better. That's absolutely not true.

Better care is actually financially more efficient and cheaper on all fronts from a patient, payer, and provider perspective. That was part of the inspiration in applying similar value-based methods to the work that we're doing. If you think about a novel drug comes out and that gets given to everybody versus a specific population where that benefits. There's that the direct cost associated with that drug.

Eliminating the ineffective care, the ineffective cost for that particular patient has value across the financial ecosystem. You flip that. You give a drug, a toxic drug to a patient that didn't need it. You're still going to have a response from a tumor perspective, so you can't just purely measure that from an OS or EFS perspective, but the patient is going to need supportive treatment to get that drug. There's cost associated with that.

There's going to be potential admission or re-admissions associated with that. There's the cost associated with that. Really, what's at the heart of what we do, and it's hard to put a dollar value on it, is the patient experience.

Did the patient actually have the right expense? Did the patient play a role in the treatment planning process? Did the doctor collaborate more efficiently with the patient? That's hard to quantify from a dollar perspective. That's easy to qualify from a value perspective, especially as you start measuring quality of care.

It's really interesting, we did a survey of about 50 cancer survivors who've gone through their treatment. We ask them, "Tell me the most uncertain part of your treatment process was? What was the most discomforting part of your journey?"

A naive guess for me would have been when you heard the words you have cancer. Interestingly, it wasn't that. Majority of patients said the treatment planning process, before the treatment was initiated, that part of the journey was the most uncertain for them.

That part of the journey, if they were say, "How would we improve quality of care purely from a patient perspective?" That part of the journey could be made less uncertain for the patient and they felt that uncertainty from the physician too, that would transform the patient experience entirely.

We're looking at both the quality and the cost because those have to go hand in hand in a value-based world or even in a semi-value-based world that we're in today.

Gordon: Bryan, one last question for you. What is the payer perspective on supporting tools that help clinicians would increase specificity, accuracy and individualization in treatment planning, and what do you see the payers' role in that to be?

Dr Loy: We touched on that a bit, and I would say that getting a tool to market—being an unmet need and we're all convinced that tool is ready for primetime—it's getting out of the way. It's getting out of the way to make sure that the policies are clear. It's getting out of the way for pre-authorization processes. What we all agree is good quality care.

The payer role is to make sure that there's access from the provider for good quality care. That just raises a number of difficulties that we don't really get to know about.

Unfortunately, when we're getting into this type of testing, much of it's not FDA approved. There are laboratory developed tests, etc, so trying to ensure the quality becomes a bit more complicated and with other technologies that are FDA approved. There's a role the payer can play. I don't think it's completely defined, as of yet.

As I said earlier, ensuring that the appropriate testing has been done before we prior-authorize a drug or drug regimen, and at least beginning to ask the questions of, "Did you consider something else if testing wasn't done?"

There are a number of roles that are processes that we can play to nudge and not say no to and further along the adoption and the education to the provider community because this is a space that continues to blossom, and I just don't see it stopping anytime soon.

Gordon: Yeah, super.

Tushar: That's incredibly comforting, not just for us as an aspiring product, but everybody that's doing work in precision medicine with that goal because, one, is the elimination of the uncertainty associated with it. Two, knowing the payers are willing to support technologies that can prove clinical benefit that are good for the patient is incredibly comforting. Appreciate that, Brian.

Dr Loy: Thank you.

Gordon: Excellent. Thank you both. That's going to wrap it for today. I want to thank my panelists, Dr Bryan Loy, and Tushar Pandey for your time and for your insights. This has been a lot of fun. I want to do it again sometime.

Thanks again to the Journal of Clinical Pathways. Thank you to our audience for your time watching this. Until next time, thanks a lot.