Tackling three common concerns
Payers, at-risk providers and PBMs (collectively, ‘payers’) are focused on strategies to ensure beneficiary access to clinically and cost-effective medications. Payers are continuously looking for ways to advance their strategies to use the best evidence to support their pharmacy benefit design strategy. Oftentimes, they face challenging questions, such as:
- How should I cover novel, high cost and targeted therapies?
- How should drugs with limited evidence (i.e., new-to-market via accelerated approval) be covered?
- What strategies are most effective to leverage our own organization’s data and external data sources for ongoing utilization management decisions?
There is a tremendous opportunity for payers to partner with pharma to answer these questions. However, collaboration to date has been limited by usefulness, relevance and trust, as described below. Through an ecosystem of collaborative regulators, payers, pharma, and others, paired with a scientifically rigorous multi-stakeholder research platform, Aetion is addressing these challenges directly.
#1: Usefulness – When insights aren’t actionable or don’t align with payer priorities
One of the most common issues is the meaningfulness of pharma-selected endpoints. Manufacturers often use surrogate endpoints (e.g., tumor shrinkage instead of progression-free survival) in clinical trials when more clinically meaningful endpoints are not feasible to measure or would significantly increase the time required for the trial. According to its website, the FDA approved 45 percent of new drugs based on a surrogate endpoint from 2010-2012. However, payers struggle to directly tie surrogate endpoint results to treatment value, as they want to understand how therapies impact total cost of care and healthcare resource utilization. As a result, payers often use their own criteria based on their interpretation of available evidence to determine appropriate coverage guidelines.
Potential solution: Leverage clinical data from trials and real-world data (RWD) to study payers’ key endpoints. Through the use of Aetion Evidence Platform® (AEP), Aetion enables pharma to develop evidence around payer-focused endpoints to support their value story. Pharma and payers can collaborate to identify gaps in current treatments and to generate and validate hypotheses on payer-focused endpoints using RWD.
#2: Relevance – When analyses aren’t applicable to payer’s population
Payers have to focus on their populations in their settings of care. So when pharma presents its RCT data, the payers do not find them overly relevant. According to statistics from Syneos, while ethnic minorities represent 39 percent of the U.S. population, they account for only 2-16 percent of clinical trial participants. One prominent example of ethnicity-driven differential outcomes is the reduced response of African-American populations to beta blockers, which result in 40-50 percent lower reduction of hospitalization or mortality. Due to both the clinical trial’s controlled environment and often distinct patient population, payers will want to understand the relevancy and application of results in their own populations.
Potential solution: Aetion partners with payers to facilitate safe and secure access to de-identified data for specific research that pharma can conduct to ensure the analysis is specific to the relevant population. By replicating analyses in payer-specific populations, stakeholders can ensure that they are translatable from one population into their own.
#3: Trust – Payers may be too quick to discredit analyses generated externally
There is a natural inclination to mistrust analyses conducted by an external party participating in commercial negotiations with payers. They may think the data shared presents pharma’s product in a particularly favorable light. However, this represents a missed opportunity for pharma-initiated collaboration that can help payers collect and implement valuable insights on their population. Payers should be inclined to focus on the quality of evidence rather than evidence generation authorship.
Potential solution: Co-create the research, with third-party expertise, to create trust through transparency and validation. AEP is designed to support multi-stakeholder collaboration for RWE studies. For example, AEP gives payers a transparent view of all the research assumptions and measures.
To learn more about how Aetion supports its customers in the payer and health economics & outcomes research space, please contact us: https://aetion.com/contact-us/.