How Claims and Lab Data Helps Pharma Generate Real-World Evidence
In our last blog on this subject, we asked three clinical experts to explain how integrated real-world and market access data helps pharma companies go to market. In this blog, our experts weigh in on how integrated data helps pharma brands identify patients, correct payer/IDN misalignment, and make better predictions to improve patient care.
We hear a lot about the “whole picture” of market access. Can you explain?
Lance Wolkenbrod, Sr. Director of Commercial Solutions, MMIT: Pharma companies basically have three kinds of customers—patients, physicians, and payers/PBMs. Real-world data (RWD) gives pharma a 360-degree view of all the different touchpoints of the healthcare system and how those customers interact.
It allows manufacturers to understand where their potential patients are, and what are their unmet needs. What challenges are physicians trying to overcome when they don’t have the tools they need to make informed decisions? And how do payers make decisions on covering certain types of products? RWD sheds light on all these interactions and roadblocks.
Ted Search, General Manager and CEO of RWD, Norstella: Essentially, what real-world data does is enable pharma brands to make better predictions. Taken together, integrated claims, lab and market access data gives manufacturers the evidence they need to ultimately improve the patient’s care. You can start to ask bigger, more potent questions, like when is the right time to prescribe? Why is one medication better than another in certain situations—what is our exact patient profile?
As pharma companies dive deeper into what’s happening with actual patients, they can better understand what the next steps should be to increase patients’ quality of life or even longevity of life, in certain disease states. When you look at it that way, that’s pretty powerful—not just for market access, but for research and development, too.
Dr. Robert Petit, CMO/CSO of OS Therapies & EVP of Commercial Operations, RWD, Norstella: Absolutely. Drug development is ultimately about solving problems, and RWD can show you what those are. Are there patients who are getting re-treated with the same drugs because there’s no new drug in the space? Are some patients that are missing the opportunity to benefit from a new drug because they aren’t being diagnosed and processed quickly enough? Where are the gaps in the market—what are your opportunities for growth?
Access to qualitative data is really critical too. As companies are determining how to bring a product into the market, they want to identify who’s at risk of becoming a patient in the future. You need a multifactorial assessment of where patients are, what products they’re on, what the comorbidities are, what side effects or abnormal lab readings are coming up. By looking at integrated RWD for all these things, you can actually figure out where these patients are coming from and how many there will be. That’s invaluable.
How has patient identification changed over the years, and how does RWD help?
Lance Wolkenbrod: In the past, we always looked at market access by seeing which payers had the most insured lives; that’s how pharma companies chose their contracting opportunities. But today, it’s not just about the number of lives managed—it’s about seeing if those lives include the patients that are right for your brand. That becomes a very different scenario, especially when you look at diseases that are more genetic in nature, which affect certain populations quite differently.
For example, when you look at the population of patients with a rare disease, it doesn’t always follow that coverage with the largest payers will provide the most access for diagnosed patients. Post-launch, one of our rare disease clients struggled to get the traction they were looking for. We did an analysis and found that their patients were insured by a lot of smaller regional plans. Integrated data can show pharma companies exactly where those population pockets are out there.
Dr. Robert Petit: Identifying the size and location of your patient population helps you every step of the way, from getting funding to commercializing the therapy you’ve created. With OS Therapies, we were treating a very rare cancer, and our number one question was: where are the patients? Who treats these individuals? We used RWD to find those physicians and figure out their catchment areas, which helped us make smart choices for the location of our clinical trial sites.
Ted Search: With my clinical background, I find it most exciting to see how real-world data can be used to identify patients and ultimately improve patient outcomes. Marrying claims and lab data can help us see those patients who will benefit most from a new medication. When you see what lab result will be indicative of a patient’s success on therapy B versus therapy A—that is truly impactful for patient care.
Does RWD help pharma companies influence payers’ decisions on coverage?
Lance Wolkenbrod: Definitely! With empirical data, pharma companies can really engage all the different channels, from Medicare and Medicaid payers to all the commercial payers out there. Payers want proof of efficacy, and they want to know that covering a drug is going to improve patients’ overall quality of life. They do extensive healthcare resource utilization analyses before making those coverage decisions. RWD gives market access teams evidence to educate payers about how the disease progresses, the drawbacks of less efficacious therapies, and the benefits of their own product.
Another thing that pharma companies use real-world data for is to clarify the gap between what a payer’s policy says and how that policy is applied in reality. If a patient is right for therapy but the provider’s prior authorization request is rejected by the payer, what’s driving those rejections? How restrictive is the payer being with that policy and why? Are certain payers making specific decisions that enable more streamlined access for patients to get on a given therapy?
Integrated data also shows misalignments between payer coverage and clinical pathways at academic hospitals and IDNs. When we know where patients are actually being treated, we can see the additional layer of which internal pathways are guiding provider choices. If patients are treated at this location, the pathway may be more restrictive than payer coverage, or the payer’s policies may be more restrictive than the pathway.
Either way, a misalignment opens up an opportunity for contracting for pharma teams. Manufacturers can work with the institution or the payer to say, here’s a group of patients who are right for our brand, but this policy or pathway is too restrictive.
What should pharma companies be looking for in a data partner?
Ted Search: To start with, it’s critical that the data vendor makes the data actionable for your company’s specific needs. Do they have a clinical team that understands the therapeutic area, and will they apply that knowledge to the data in a way that generates impactful evidence in your specific disease state?
A data partner should look at what your company is trying to solve and work backwards—not just throw you some files and tell you “hey, there’s some good stuff in there, good luck!” Ideally, you want a partner that has multiple data sets with strong clinical and data science teams in place to make it actionable and relevant. Not to be too salesy, but that’s what our Bridging as a Service does – we provide a custom bridging file and services to maintain it, so you always have a single source of truth and you can answer your questions with 100% of your data, already integrated.
Dr. Robert Petit: The longitudinality of the data is also really important. When you’re using a data set to make decisions, it’s important to know how far back it goes. The bottom line is that new treatments come out frequently, and therefore the landscape changes frequently. Being able to have a historical perspective of those changes in your therapeutic area is key.
You need the ability to adjust quickly to an evolving marketplace. If a new publication comes out that shows that a genetic subtype of a disease reacts differently, how will you identify those patients? Having data sets that go back a few years helps you pivot based on changing circumstances in both the patient journey and the market.
Lance Wolkenbrod: To all of that, I’d add two things: Is the data representative of what we’re trying to solve for, and can the vendor support my current and future needs? Many times, a pharma company seeks out an engagement because they have one specific question to answer. But each question leads to more exploration; it’s like peeling an onion.
Can that data drive additional insights? And also, does the vendor have enough clinical knowledge to drive the desk research that goes into some of these equations? You need a business partner with the expertise to quickly pivot and answer tomorrow’s queries—not just what you’re interested in today.
Learn how MMIT’s integrated claims, lab and market access data can help your team improve utilization and uptake. For more on how MMIT can make your real-world data sets perpetually actionable, learn about our Bridging as a Service solution.
