Before going to market with a new drug, medical device or test, it’s crucial to know how payers will treat it post-approval. Understanding post-launch coverage restrictions and knowing which payers are likely to publish policy in the first six months to two years allows organizations to design effective marketing strategies. But who has a crystal ball to discern the future? How can anyone predict the response to a launch?

Float like a butterfly, sting like a bee

Enter: Bumblebee, a patented software system that tracks public domain payer policies that are either new or new versions of existing documents. With more than 850,000 such policies in the dataset, Bumblebee is able to aggregate the results of the past eight years of data, which are then handed off to a team of policy analysts to review and interpret, all with the aim of helping predict how a product will perform.

“Our predictive offering leverages both current policy documents as well as historical ones,” explained Drew Gutschmidt, president, Policy Reporter, a TrialCard company. “Once a payer either takes down a policy or replaces an old version with a new one, there is no other way to access it. Our system gives us the ability to investigate, historically, how products were treated when they came onto the market and combine that with what we know is happening in the market today. This is the basis of our predictive model, a tool we have built over many years that has helped support the launch of numerous therapeutics.”

Our system gives us the ability to investigate how products were treated when they came onto the market and combine that with what we know is happening today.

Drew Gutschmidt, Policy Reporter

Consider this: You’re a manufacturer getting ready to launch a novel gene therapy into the marketplace and have the ability to access historical context related to that therapeutic class, i.e., the post-FDA approval timing of a published analog payer policy and its impact based on the number of covered lives.

“All of this information is key to developing appropriate payer marketing strategies,” said Scott Dulitz, chief strategy officer and head of corporate development, TrialCard. “Our goal is to ensure our clients’ teams are knocking on the door of the right medical directors to help them convey a targeted value proposition related to their product.”

The foundation of confidence

Prior to publication, providers cannot access a policy; they don’t know how a particular plan may be treating a new therapeutic until they have treated their first patient and submitted a claim. As such, should a physician use a particular buy-and-bill product without waiting for the policy to be published, they assume a serious amount of financial risk for themselves and the patient.

“Let’s say you’re a provider who paid hundreds of thousands of dollars to purchase a newly approved drug from a manufacturer,” Gutschmidt uses by way of illustration. “After evaluating a patient, you determine the drug is medically necessary for their condition. What you don’t know, though, is whether the patient meets all their health plan’s clinical and administrative criteria, since there isn’t yet a published policy. If it is a buy-and-bill product and the patient does not meet the plan’s criteria, there is a strong probability the claim could be denied, resulting in financial toxicity for both the provider and patient.”

In TrialCard’s estimation, the publication of a policy is the foundation of prescriber confidence. Knowing when a policy is going to be published gives the manufacturer’s customers — the healthcare providers — comfort in utilizing that product. 

“Understanding the restrictions that are likely to be in place on an individual, plan-by-plan basis and where those therapies sit, can help inform the types of patient support programs that biopharma companies need to put in place to facilitate access,” said Gutschmidt, adding, “Ideally, during Phase III clinical trials — 12 to 18 months before launch — is the ideal time to start performing a predictive analysis. If you start too early, the environment may change by the time you go to market; if it’s too close to launch, you run the risk of not having enough time to develop strategies to address the findings.” 

What if you could not only preview the future but have a role in its outcome? This is where Payer Advocacy takes the reins. 

It comes down to individual decision making 

If the goal is to impact coverage, criteria and timed publication, knowing which plans to approach and how to approach them is an important next step in influencing the outcome and access to new therapeutics. The predictive model provides the targets, but hands-on research and direct payer input is key to successful payer advocacy. 

“The core content we put together in our advocacy campaigns is our model policy, which pulls together both administrative and clinical criteria into a recommended policy,” explained Gutschmidt. “This is designed to both speed up the timeline to policy publication, by handing plans a blueprint they can use and encourages them to adopt the criteria which has been fully vetted. Ultimately, it’s in the hands of the medical or pharmacy director to make the decision, but model policy has been shown to be very effective.” 

The model policy includes input from corresponding payer panels — if it is a medical benefit product, then panels of medical directors; if it’s a pharmacy benefit product, pharmacy directors. This kind of robust intel can exponentially accelerate publication and potentially impact restrictions. To date, TrialCard has achieved coverage for policies representing more than 120 million covered lives in the U.S. 

“This payer intelligence has enormous impacts on the performance of brands, when they launch, how they’ll be covered and their go-to-market commercialization and payer strategies,” concluded Dulitz. “More importantly, it has a huge impact in determining when patients may get their medications and how accessible those medications will be for those with unmet medical needs.”

The benefits are clear on the biopharma industry side, but more importantly, on the patient side. Payer intelligence is critical to simplifying access.