Diagnostics, MedCity News eNewsletter, Payers

Why do many IVD companies face an uphill battle with payers for reimbursement?

Despite the relative paucity of peer-reviewed studies for IVDs in general, several companies are taking steps to publish their data, which can ultimately lead to positive coverage decisions by payers

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The demise of Courtagen Life Sciences earlier this year brought increased attention to a long-standing problem for the in vitro diagnostic (IVD) industry, particularly for genetic tests: getting reimbursement from third-party payers is challenging. A well-developed reimbursement strategy is an essential component of the IVD development process. Far too often, reimbursement is considered too late in the process, leaving a company to hope that payers will respond as product adoption increases and often subsidizing patient costs in the interim.

But as Courtagen and other genomic testing companies have found, it can take years before payers reliably cover the costs of their tests, and in many cases, reimbursement may never come. As the digital health industry expands, it faces a similar challenge. While telemedicine can be seen as a natural extension of the standard office visit, at some point the question arises, “Who will pay for connected devices, specialty software, and other digital health tools?”  

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To understand why so many companies have faced an uphill battle with payers for reimbursement of their products, it’s essential to consider how these decisions are made. FDA approval or clearance is just one factor influencing payer decisions. Others include competitor coverage policies, clinical guidelines and physician support, employer or advocacy group demands, cost/benefit analyses, and the results of health technology assessments (HTAs). Of these factors, cost/benefit analyses and HTAs are where IVD and digital health companies have the greatest ability to influence payers.

HTAs, also referred to as technical assessments, are often performed by the government or specialty companies, though they may be performed in-house for self-insured health organizations or for large insurers with dedicated resources. HTAs may also be performed by utilization management (UM) companies as part of their pre-authorization services, which are increasingly being adopted for the complex world of genetic testing. Specialty companies that perform HTAs include ECRI, Blue Cross Blue Shield Association’s Evidence Street, Hayes, and Evicore, among others. Their HTAs typically are purchased by insurers or used as part of their UM services (e.g., Evicore) and their proprietary methodology and results are generally not made publicly available. Government or government-affiliated organizations like the Agency for Healthcare Research and Quality (AHRQ), the U.S. Preventive Services Task Force (USPSTF), and Medicare contractor Palmetto GBA perform their own studies that are accessible by the general public.

Though the methods used by the myriad organizations that perform HTAs differ, several components are typically included and all are considered evidence-based. These include safety and effectiveness, clinical outcomes, risk/benefit analyses, and economic outcomes. But what evidence the HTAs include depends on the organization performing the analysis. Some include only what is available in peer-reviewed literature, so conference abstracts, company white papers, and even the results of studies that are published on company websites would not be considered. Some may not reach out to manufacturers for additional information that the company could be maintaining privately. This is an incredibly important point to consider, as many IVD and digital health companies stop short of publishing their evidence in peer-reviewed journals. Consequently, though the evidence from internal documents may be compelling, the companies performing HTAs would instead find a lack of evidence to support the product’s use. The end result? Insurers label the devices “experimental” and “unproven,” and refuse to reimburse for their use.

So what can IVD and digital health companies do to improve their odds for reimbursement? What kind of evidence should be published?

To begin, companies should be assessing their product’s analytical validity (AV) and clinical validity (CV) as part of their development process. For diagnostics, the validation and verification phase of design likely include studies that already capture that information. But most companies tend to not publish that data, perhaps assuming (wrongfully) that doing so would put them at a competitive disadvantage. But when this information is a critical part of an assessment for reimbursement, it’s not difficult to see that the perceived advantage of keeping this data private actually puts the company at a disadvantage in the long-term, because reimbursement will remain unlikely. In addition, comparisons between a company’s device/product are useful for continual improvement programs and can be used to highlight differences from the competition.

Importantly, while CLIA standards address AV, CV and clinical utility are not assessed under the program, so IVD companies which assume a lab with CLIA certification takes care of these issues are mistaken. Similarly, while the process to obtain FDA approval or clearance for an IVD may require AV and CV data be shared with the Agency, it does not mean that payers will automatically cover or reimburse for the product. The joint FDA/CMS Parallel Review Program is an exception; devices that complete the program successfully obtain FDA approval or clearance and a concurrent CMS coverage determination. Foundation Medicines FoundationOne CDx successfully completed parallel review by the Agencies. The FDA’s recent formation of a program for digital health is anticipated to clarify the Agency’s position and requirements for digital health products, and companies are encouraged to stay abreast of developments.

Clinical utility (CU) and health outcomes studies are growing in importance as the healthcare system looks toward value-based pricing models. What kind of outcomes are important in a value-based reimbursement system? For diagnostics companies, it might be direct outcomes such as a change in the patient’s clinical management based on the results of the test. Indirect outcomes like improvements in survival or reduction of adverse events that follow from the specific treatment selected based on the test’s results can also be considered. Indirect outcomes for IVDs for hereditary cancer syndromes might also include the results of cascade screening; that is, the results of further testing of a patient’s at-risk family members. Similarly, digital health companies may assess direct or indirect outcomes for patients, such as medication adherence, or changes in control of a disorder, like measuring blood glucose levels for diabetes.

Getting the AV, CV, and CU data that serve as the basis for HTAs can be done through a variety of study designs. Though randomized-controlled trials and meta-analyses have been held up as the pinnacle of study design hierarchy for drug studies, they may not be the best choice or even practical to implement for IVDs and digital devices. Retrospective and prospective observational studies, case-control studies, and large case series are other options that should be considered as appropriate.

Increasingly, real-world evidence (RWE), which is loosely defined as data derived from a variety of databases, such as insurance claims, digital devices, and electronic health records, is being assessed and integrated into clinical studies. A guidance document released by the FDA, which outlines the Agency’s recommendations for RWE, lists several potential uses for RWE, including for historical controls and for biomarker identification and clinical validation. Although there is still uncertainty among those performing HTAs about the use of RWE because it is not collected in strictly regulated clinical trials, RWE may more closely mirror how a product performs in clinical practice, ultimately making it easier for companies to demonstrate the CU and value of their device.

Despite the relative paucity of peer-reviewed studies for IVDs in general, several companies are taking steps to publish their data, which can ultimately lead to positive coverage decisions by payers. Genomic Health, for example, used observational studies that were later used by payers in coverage and reimbursement decisions.

Myriad Genetics has published numerous studies about the AV and CV of their tests, including a recently published study of the AV for their 12-gene assay to predict distant recurrence of a type of invasive breast cancer. Notable Labs made headlines by raising $10 million to support new clinical trials for their diagnostic for people with certain blood cancers. The evidence supporting digital health technologies is only emerging, but industry players like Evidation Health are working with digital health companies to collect the RWE that could be essential for payers looking to calculate the value of these products.

Although there are multiple influences that inform the ultimate coverage and reimbursement decisions for a device/product, the results of HTAs and cost-benefit analyses can be helped, or hindered, by choices about performing clinical trials and the publication of that data. Understanding what types of data will be considered in an HTA can be useful information during the design of the product, to ensure the appropriate clinical studies are undertaken.

Companies that use the FDA/CMS Parallel Review Program may be at advantage, but even those which are ineligible for the Parallel Review Program or choose not to pursue that pathway can request CMS and/or certain private payers provide input at pre-submission meetings. Further, publishing the results of these studies, in peer-reviewed journals should be a priority for IVD and digital health companies. In the competitive IVD and growing digital health industries, it’s essential that companies seeking reimbursement for their products from payers (public and private) understand the process that will be used to assess their product and use that information to their advantage.

Harry is the author of two related books: Commercializing Novel IVD’s; A Comprehensive Manual for Success and MoneyBall Medicine: Thriving in the New Data-Driven Healthcare Market.

Photo: BrianAJackson, Getty Images