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directly matching 340B chargeback data to Medicaid claims, a process that is supposed to be confirmed by using an outdated and often inaccurate Medicaid Exclusion File that applies to only a small portion of claims or “coded” modifiers that have unfortunately proven to be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.
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