Angie Franks

How drug manufacturers can reduce revenue leakage with digital tools

February 19, 2024
By Angie Franks

Revenue leakage due to misapplied discounts represents a vexing problem for drug developers, creating financial pressure and barriers that make it more difficult for pharmaceutical companies to hold drug prices down.

In 2022, the gross-to-net (GTN) gap for patent-protected, brand-name drugs reached $223 billion, a 33.5% increase from 2018, according to Drug Channels. The GTN gap refers to the difference between a drug’s list price and its net price, which takes into account rebates, reductions, and price discounts. Misapplied discounts are a major contributor to the GTN gap.

In the future, the GTN gap may grow even larger. Several recent factors have intensified the impact of misapplied discounts on drug developers, including an expansion of the 340B program. The program was created by Congress in 1992 to require that manufacturers provide discounts to certain safety net providers, but has soared in popularity since 2010 when the federal government issued guidance permitting an unlimited number of contract pharmacies.

Additionally, a federal ruling this past November in a case involving Genesis Healthcare is being seen by some in the covered entity community as support for expanding the number of claims that are eligible for a 340B discount. Separately, while the Inflation Reduction Act prohibits Part B and Part D inflation rebates on the same claims that are subject to 340B discounts, the prohibition on Part D inflation rebates and 340B discount duplicates is not scheduled to take effect until 2026 due to operational challenges of identifying such discounts.

Given this new reality on the ground, key stakeholders in drug discount programs, such as manufacturers, covered entities, and state Medicaid authorities, would be wise to explore new tools that help them mitigate the growing compliance challenges presented by misapplied discounts.

Inside the problem of misapplied discounts
Duplicate, or even triplicate discounts, may result when different rebate programs intersect. For example, a duplicate discount occurs when a claim subject to the 340B program discounts overlaps with rebates from either the Medicaid Drug Rebate Program or from commercial insurance plans.

Additionally, it is possible that overlapping programs result in a triplicate discount, which may occur when a single dispensing of a drug involves a PBM rebate, a Medicaid rebate, and a 340B discount from one or more covered entities. Such possibilities can compromise the integrity of discount programs, ultimately harming patients.

The reasons behind these misapplied discounts often are driven by an onerous and archaic system that relies on manual data uploads to function, resulting in fragmented data and issues with data integrity. For stakeholders of the drug discount system, the challenge of acquiring, ingesting, and analyzing the right data at the right time is costly and daunting.

One particular challenge involves directly matching 340B chargeback data to Medicaid claims, a process that is supposed to be confirmed by using an outdated and often inaccurate Medicaid Exclusion File that applies to only a small portion of claims or “coded” modifiers that have unfortunately proven to be inconsistent. Modifiers are codes added to claims data to help stakeholders identify discounts at the point of dispense.

However, by definition, a “modifier” is created to modify an existing system, and thus, has not been built into the original system. As a result, modifiers have fallen short in practice.

Often, modifiers are not representative of what really occurred at a drug dispense and may be added later in time due to the complexities of the 340B replenishment model. For example, some pharmacies do not include modifiers on patients’ 340B eligibility, while others do, but these codes may not be visible to other stakeholders in national data sets as the claim moves through the payment system.

A better, data-driven solution to discounts
With drug discount programs growing, the threat of misapplied discounts that lead to revenue leakage has also risen commensurately. To respond, manufacturers and other stakeholders are exploring data-driven technology solutions that do not rely exclusively on modifiers.

However, these solutions must include the following three essential elements:

Scalable data acquisition and ingestion: To be successful, a solution must be capable of ingesting and unifying data from multiple sources to create a “single-source-of-truth” that breaks down system-wide silos.

Timely data analysis and decisioning: Without the proper context, data alone has little value. The right solution must be able to normalize, transform, and validate data for actionable insights, regardless of file types and formats.

Confident effectuation and audit trail: Drug developers need technology that accurately documents and tracks disputes through resolution to effectively contest duplicate discounts when necessary.

Revenue leakage imposes a significant cost on drug makers, leading to higher prices passed on to patients. With digital tools that enable compliance and do not rely solely on modifiers, drug developers can begin fixing our broken and outdated drug discount system.

About the author: Angie Franks is the chief executive officer of Kalderos, a data infrastructure and analytics company, and creator of the world’s first Drug Discount Management platform.