As drug development becomes more complex, payer organizations need internal operational and coding alignment between medical and drug benefit teams.
Drug development and investments are evolving at an unprecedented rate. In 2023, overall pharmaceutical expenditures in the US grew to $722.5 billion, up 13.6% from the previous year, and specialty drugs are adding new complexities to the industry.
As payer organizations seek to understand and address whole-person health among their members, they may need to adjust operations to meet these new challenges. This is particularly crucial regarding coding operations and alignment between medical and drug benefit teams.
A tale of two health plan benefit teams
Historically, medical and drug benefit teams have operated in silos because the delineations between the two policy teams had more defined spaces. That separation resulted in distinctly different organizational processes, communications, and operations with some inefficiencies and inconsistent decisions—a 2023 study showed that in 14% of instances, medical and pharmacy policies were different for the same drug and could complicate member access to care.
With the recent advent of more specialty drugs and complex medical procedures, lines have blurred between the teams and increased the need for more interoperable processes. In 2023, specialty drugs accounted for less than 5% of claims volume, but accounted for 54% of spending. Complicating this is that 40% of specialty drugs fall under medical benefits, especially portable and self-injectable medications and at-home infusions. Inconsistent decisions around these therapies can become very costly for all involved.
However, separate coding systems for the different medical and pharmacy claims can don’t make it easy. For example, indications from medical coding systems like ICD-10 and HCPCS don’t always neatly map to NDC codes in pharmacy claims. Additionally, pharmacy prescription claims also come in real-time, whereas medical claims are in arrears, leaving pharmacy benefit teams trying to decipher the need for a drug, understand policy implications, and balance quality control.
This leaves benefit teams trying to understand the whole-person but with information coming in various forms and timeframes, and without a full picture of the member.