By not performing coordination of benefits (COB) and data mining on their pharmacy claims, healthcare payors may be missing a significant opportunity to recoup overpayments. In 2023, Americans spent $722.5 billion on prescription drugs, up almost 14% from 2022.¹ That number is likely to increase. According to the Centers for Medicare and Medicaid Services (CMS), prescriptions are the fastest-growing healthcare category and will continue to be for at least the next decade. In addition, approximately 43 million Americans have coverage through more than one insurer or plan. When members have more than one plan, the likelihood of inaccurate payments – whether for medical or pharmacy claims – increases.  

Use Coordination of Benefits (COB) and Data Mining Solutions That Cover Both Medical and Pharmacy Claims

The truth is, if healthcare payors are identifying overpayments on their medical claims through COB and data mining, they most likely will find overpayments on their pharmacy claims as well. Expanding coordination of benefits (COB) and data mining to include pharmacy claims maximizes potential recoveries and ensures a more comprehensive approach to payment integrity.  

Payors who analyze medical and pharmacy claims separately may miss opportunities to detect cross-claim discrepancies. For example, a holistic data mining approach can identify cases where drugs were paid in duplicate between a medical and pharmacy benefit.  

Why Aren’t COB and Data Mining Being Performed on Pharmacy Claims?

Some payors might mistakenly believe that when they verify eligibility for medical benefits, the verification automatically applies to the pharmacy benefit as well. Others have interest in performing COB and data mining for pharmacy claims but don’t have the staff resources and expertise to do it themselves. Additionally, many payors struggle to find vendors that offer pharmacy-specific services due to limited availability in the market.  

Many vendors who offer COB and data mining for medical claims don’t offer the services for pharmacy claims because of significant rule differences between the two claim types.  

How Pharmacy and Medical Data Mining Differ

In terms of data mining, unique edits apply for pharmacy claims that don’t apply for medical claims, and some vendors may not have the appropriate knowledge about these edits. Without knowledge of pharmacy-specific edits, vendors may fail to identify duplicate payments, excessive refills, or billing errors unique to pharmacy claims.  

Additionally, there are significant differences in medical and pharmacy coding structures. Medical claims use standardized current procedural terminology (CPT), healthcare common procedure coding system (HCPCS), and International Classification of Diseases (ICD) codes, making data mining more straight forward. Pharmacy claims rely on National Drug Codes (NDCs), days’ supply, refill limits, and dosage information, which require specialized auditing logic and expertise to identify inappropriate billing practices.  

Pharmacy claims also have higher transaction volumes. Unlike medical claims, which often have significant charges, pharmacy claims have lower charges but are far more frequent. This high volume requires specialized data mining algorithms that can efficiently process millions of transactions and detect discrepancies that may seem minor but add up significantly.  

Duplicate billing in pharmacy claims is also more complex. Duplicate billing for a medical claim is usually easy to identify by matching procedure codes, providers, and dates of service. For pharmacy claims, duplicate billing may occur because of refill loopholes, early refills, split claims, or multi-source drugs (brand vs generic) that are harder to detect without advanced analytics.  

Pharmacy claims are processed in real-time. Unlike medical claims, which can take weeks to process, pharmacy claims are often adjudicated in real time at the point of sale. This limits the window for detecting and preventing errors before payments are made.  

Collection of Recoveries Is a Major Difference Between Medical and Pharmacy Claims

The most crucial difference is that collection of recoveries for incorrectly paid pharmacy claims is more complicated than collection for medical claims. Instead of offsetting future claims, which is done for typical medical payor overpayments, collections from pharmacy benefit managers (PBMs) involve outreach and must occur within specific timelines while being sensitive to not causing member abrasion. 

Lack of due diligence relating to providers can also cause issues. Members sometimes mistakenly believe that when they pick up a prescription and give the pharmacy their ID card, the pharmacy will make sure the right payor is getting charged, but this is not the case. Pharmacies may continue to bill under the same coverage as past prescriptions without verifying whether the coverage is appropriate or confirming that it is active and the primary coverage.   

Another difference that affects both coordination of benefits (COB) and data mining is that the technology platforms used by PBMs for pharmacy claims is different than the platform used for medical claims. This complicates the process of finding overpayments and errors. The person looking for the overpayments has to have knowledge of both platforms, and both the platforms need to be compatible with the other systems being used. 

While many vendors lack the knowledge or expertise to offer coordination of benefits (COB) and/or data mining for pharmacy claims, Claritev is happy to say that we do. 

You Asked for Pharmacy COB and Data Mining and Claritev Delivered

In response to clients asking us for help with their pharmacy claims, we have enhanced our Payment Integrity solutions so that they can now help you identify pharmacy claims that shouldn’t have been paid and recover the funds for them when paired with our medical Coordination of Benefits (COB) and Data Mining services. 

Claritev has sophisticated technology that enables us to review data across medical and pharmacy platforms, allowing us to identify duplicate payments as well as incorrect payments. Our team is able to recoup overpayments from the correct party and limit any member engagement. We utilize the information from our medical COB and data mining reviews, along with the Rx data file, so you receive the full benefit of our investigations.

Learn more about our Payment and Revenue Integrity services.

¹ Eric M Tichy,  James M Hoffman, Mina Tadrous, Matthew H Rim, Sandra Cuellar, John S Clark, Mary Kate Newell, Glen T Schumock, National trends in prescription drug expenditures and projections for 2024, National Library of Medicine, July 8, 2024