Specialty drug complexity is outpacing payer policy
Healthcare payer services in the US are projected to grow from roughly $80 billion in recent years to more than $155 billion by 2034. This type of accelerated growth can create more operational challenges for benefit management teams at health plans working within a healthcare system that is already stretched thin. Nowhere is this more apparent than in specialty drug coverage. Among 287 specialty drugs with paired policies at large commercial health plans – meaning they are managed under both drug benefits and medical benefits – up to 40 have coverage criteria that differ. This is just one example of how challenging it can be to keep policy consistent once it transitions to daily workflow execution across access, benefit, formulary, and utilization management teams.
When medical and drug management teams work from separate systems, standards, and data, policy intent can get lost before it ever reaches a coverage decision. The more embedded those separate workflows become, the more likely inconsistencies can develop and create gaps in quality, cost control, and member trust. These types of discrepancies highlight where a policy’s intent and a team’s application of it are different, and each one is a potential point of risk in an audit or appeal.
“There are so many drugs coming to market, and these drugs are increasing in cost and complexity. Payers are asking themselves, how do we manage them all?” says Allison Combs, Head of Payer Product, Strategy and Innovation for Wolters Kluwer Health. “And then, how do we make sure we have the appropriate drugs for members’ conditions? It creates this underbelly in payer decision-making of confronting how to solve for volume and for precision at the same time.”
Limited distribution drugs put policy to the test
Specialty medications and limited distribution drugs can be a useful test of payer and PBM policy. When payers struggle to track them, it often signals inconsistencies that tend to show up wherever specialty, medical, and pharmacy benefit workflows intersect, leaving no unified view of a member's therapy history across benefit types.
Why more data alone will not close the gap
Many payers look to real-world evidence (RWE) to help close these gaps. But interest in RWE far outpaces its use: 80% of payers want to use it more, while only 18% currently apply it regularly in decision-making. This is likely due to the fact that payers are selective about quality. In a separate survey, 86% of payers said rigorous, unbiased data curation was an important factor in choosing a decision-support tool.
Deborah Pasko, PharmD, MHA, Associate Director of Technology Product Management for Payer/PBM at Wolters Kluwer Health, describes payer decisions as shaped by three interconnected three layers:
- A basic data foundation built on standardized, well-mapped terminology.
- Clinical knowledge and intelligence built on top of that foundation.
- Increasingly, agentic AI models on top of that to support decisions at scale.
Without a well-mapped data foundation, she notes, the layers above it have little to stand on, no matter how sophisticated the analytics or AI applied to them.
Bringing consistency into workflows
Creating alignment between policy and execution means bringing trusted medication and clinical intelligence directly into the workflows where specialty drug decisions get made, rather than treating that intelligence as a separate lookup.
- Medi-Span® drug data has supported payer and PBM workflows for more than 50 years, giving formulary and utilization management teams a shared, consistent view of medication data as they manage prior authorization, benefit design, and policy determination for complex specialty therapies.
- UpToDate® clinical decision support complements that foundation with evidence-based clinical context that can inform coverage and prior authorization decisions and can support the documentation payers need if a coverage decision is appealed.
Steps for reducing decision variability
Some health plans now conduct 120 to 150 clinical reviews a day. As that volume grows, payers can start narrowing decision variability with three steps:
- Identify where paired-policy discrepancies create the greatest financial or clinical risk.
- Strengthen the basic data foundation so terminology mapping can support future AI-driven workflows.
- Move medication and clinical intelligence into the workflow itself rather than treating it as a separate step.
Together, these steps can help payer teams apply their own policies more consistently and defend the decisions that follow, even as specialty drug coverage continues to grow in volume and complexity. For payers navigating that shift, decision consistency is no longer a back-office concern. It is a strategic requirement for cost control, member trust, and long-term growth.
Explore evidence-based solutions for payers and PBMs. To learn more about how integrated medication and clinical intelligence can help payer teams improve efficiency, consistency, and defensibility across coverage decisions, read the whitepaper, Balancing volume and precision in payer decision-making.