Over the years, IQVIA has a built a strong reputation for its subject matter expertise and in-depth understanding of the In-Vitro Diagnostics (IVD) market. IQVIA is passionate about driving healthcare forward, and demonstrates its passion by supporting industry in accelerating advances in IVD and achieving recognition for the value it provides within the healthcare continuum and throughout the patient journey.

Michaela Miller, leader of IQVIA’s U.S. MedTech Technology and Analytics practice, recently had the opportunity to sit down with market access expert Lena Chaihorsky, co-founder and vice president of Payer Innovation at Alva10, to discuss the IVD market’s development in more detail.

Alva10 is an innovative precision medicine company that decreases payer and employer pharmacy and medical spending through the development and implementation of novel, fit-for-purpose diagnostic tests. In this way, Alva10 bridges the gap between payers and the diagnostic industry, which Lena argues is critical to turn the tide of healthcare overutilization. Lena is also a task force member for Pharmacogenomics at the American Society of Pharmacovigilance, and a noted speaker on concepts of diagnostic value and the need for redesign of financial incentives in our healthcare system.

MM:  Lena, briefly explain the difficulty diagnostic companies have as they approach payers with their value propositions? Why is there seemingly misalignment in reimbursement, or a lack of recognition of the value of Dx tests and the role they play in driving better patient outcomes?

LC: The first issue – the lack of recognition of the value of Dx tests – propagates the second issue, which is misalignment in reimbursement.  And the lack of recognition of Dx value occurs for two key reasons. First, there was a historically low volume of diagnostic companies going to payers with really strong value propositions – which we at Alva10 would define as value propositions that enable payers to bypass costly interventions or inefficient workflows that slow patient care. Second, diagnostic companies are not approaching payers with sufficiently robust evidence to prove their value propositions. Many companies try to construct a so-called “chain of evidence” in lieu of running the ultimate clinical utility study design, which is the prospective, randomized trial. So, payers get the sense that diagnostic companies aren’t answering the right clinical and economic questions, and aren’t doing a good job of proving their value propositions in any case. The misalignment in reimbursement continues to be an issue – therapies are priced at value-based rates and diagnostics are priced at cost-plus based rates in accordance with the CMS Clinical Laboratory Fee Schedule. But within the existing confines of the Fee Schedule, there are still many opportunities to bring payers valuable tests that they would cover and pay for. The key is to nail the tests’ value proposition and evidence structure.

MM: In the past you have shared that large oncology panels have “lost the payer’s attention.” Can you explain? Where do you see opportunities for better diagnostic and payer collaboration to address unmet need?

LC: Payers and diagnostic companies have been engaged in coverage discussions around oncology panels since Foundation Medicine launched its first LDT in 2012. For the past decade payers have been learning about the utility of DNA and RNA from the diagnostic industry, and trying to wade through the differences in technology, targets, tumor types, and clinical indications to make coverage decisions on oncology products. And, as critical a need and as high cost as oncology is, it is only one of the many costly, chronic conditions payers pay for daily. If we employ customer-centric thinking, we see that payers are the economic customers of the healthcare system – they pay for patient treatment. As the diagnostic industry, we need to recognize that our economic customer has needs outside of oncology (as of course, do patients) and we need to develop solutions to meet those needs.

I see huge opportunity for payer collaboration in other chronic conditions – particularly in the areas of specialty drug spend, where drug prices are high and continuing to climb. Pharmacy spend and medical spend are siloed within insurance companies, but this is starting to change. And we have spent a lot of time with payers showing them the vast potential of the diagnostic industry to optimize their specialty spending – for example, by providing advance knowledge of which patients will respond to which drugs prior to those specific drugs being assigned and paid for. I also see huge need for diagnostics to stratify patients according to disease severity in order to more concretely determine i) which patients are candidates for drugs and ii) in which period of their illness these drugs will have the most positive impact. Decreasing spending in payers’ greatest cost areas – that is how you get insurer attention.

MM: Based on your experience, what do you observe as the biggest struggle for Dx companies when communicating their value proposition to payers?

LC: The greatest issue is a failure to recognize insurers for the actuaries that they are. This is why so many stories centered on ‘the value of knowing’ don’t hit their mark with payers. As actuaries, payers want to understand what the clinical and cost implications will be of that ‘knowing’, so to speak, and they want to see that proven out through robust studies. I don’t want to dismiss the patient-centered work that insurers do in the quest for better outcomes, but payers at large are not healthcare providers. They are actuaries, they assess risk. It is possible to have many productive conversations with payers on that plane, but it isn’t the patient care plane that diagnostic companies are accustomed to in their dealings with clinicians, hospitals, laboratories, and the patients themselves.

MM: There is no general “prescription” on what data needs to be provided to payers to secure reimbursement rates that better reflect a test’s value. What general recommendations can you provide to Dx companies on the type of data collection to focus on to demonstrate clinical utility?

LC: The best clinical utility data comes from prospective studies, with appropriate consideration given to how close the patient population in question is to the real-world patient population that payers cover and physicians serve. Study design must also account for the full definition of clinical utility, and here is where I think many diagnostic companies misunderstand how payers define clinical utility. Clinical utility is not proof that the clinician in question will order your test or use the results of your test, although that is a contributing factor of clinical utility. Clinical utility is the proof that when the clinician uses your test to treat a patient in an appropriate population, the clinical outcome of that population will be markedly improved at an appropriate economic cost. This is why we also see the term ‘economic utility’ come into play when we discuss clinical utility – again, payers are actuaries.

MM: We recently spoke on a panel together citing the ‘COVID-19 headwind’ in the diagnostics industry. What other market forces do you see that will provide net benefit to the diagnostics industry?

LC: I see two big driving forces for diagnostics in the near- to mid-term. The first is the ever-increasing presence of employers pushing their vendors (carriers, PBMs) to decrease cost of care – and taking on larger operational roles within their healthcare ecosystem if and when they feel that the traditional carriers and PBMs cannot meet their needs. Employers pay for healthcare decisions twice – once via the cost of care, and again, in productivity cost associated with each healthcare journey. Carriers do not factor productivity into their value calculations, and that has led to missed opportunities to serve employers.

Second, the market pressures on the PBM industry are forcing that sector to innovate. PBMs today are coming to market with new business models that replace the classic drug volume rebate with a subscription, service-based model. They are increasingly talking about wrapping their pharmacy optimization in clinical decision-making. Using clinical tools to optimize pharmaceutical spend? That’s the language of diagnostics.

MM: Thank you, Lena. As with the panel discussion, you’ve shared many valuable insights regarding market access and reimbursement for diagnostics. Hopefully this resonates, and some of your concrete takeaways can drive additional positive momentum and success in this area.