Even though just four health insurers control 50% of the U.S. market, there are more than 900 payors in the country. And for each payor, there are often multiple phone numbers for different plans (Commercial, Medicaid, Medicare Advantage, etc.), different groups, and so forth. 

This complexity is compounded by the lack of a standardized naming system for payors. While it may not, at first, seem like a big deal, this lack of standardization is a major challenge in the benefit verification process.

In this post, we’ll explore what makes payor mapping so hard, and how Infinitus has approached the challenge: with automated payor resolution, which handles the complex work of matching how a customer lists a payor to how the payor is documented in Infinitus’ system, ensuring tasks are accurately routed from the start.

Why is payor mapping so hard in the first place?

As mentioned above, there’s a lack of standardization. Different healthcare organizations often track the same payor with varying names. For example, while we may refer to “Florida Blue” as “Florida Blue,” other companies might call it “BCBS Florida,” “Blue Cross Blue Shield Florida,” or “Blue Cross Blue Shield of Florida.” 

Some organizations forego the concept of payors entirely and rely on patient ID card phone numbers. But even within a single company, manual entry leads to discrepancies and a lack of standardization, which complicates interoperability and data exchange. These issues create inefficiencies in onboarding new vendors and require ongoing maintenance as payors are added or changed. 

This is a problem, because even small mismatches in data can trigger a domino effect of issues – treatment delays, and costly manual rework. And despite its importance, payor alignment has remained largely unsolved at scale, in great part because of the complexity of the systems involved. 

Automated payor resolution: a game-changer

We recognized an opportunity to approach this challenge and streamline the payor-mapping process by developing an AI-driven system to automatically and accurately identify, map, and resolve healthcare payors at the time of task creation or ingestion into the Infinitus system.

Our payor resolution feature improves operational efficiency, reduces onboarding time for our customers, and minimizes administrative overhead. Here’s how it works:

  • Infinitus knowledge graph: Our knowledge graph has identified rules from 5M+ calls utilizing customer-provided information such as phone numbers, member ID patterns, or group numbers to resolve to the right payor and assigns the appropriate Infinitus Payor ID.
  • Best match algorithm: If our knowledge graph is unable to find an exact payor match, our task management platform uses an advanced algorithm to determine the most likely payor based on available data.
  • Fallback process: In cases of uncertainty, we default to the customer-provided phone numbers and payor name to ensure the task is completed accurately.

By leveraging the automatic payor resolution feature, customers can experience faster integrations, fewer errors, and improved task success rates. Additionally, our relationships with payors are strengthened by ensuring we’re using dedicated lines they’ve provided, further boosting compliance and task resolution efficiency.

The future of payor resolution

With automated payor resolution, we’re not just tackling a long-standing challenge; we’re building a foundation for improved interoperability, reduced administrative burden, and faster, more accurate results for our customers.

As the healthcare landscape continues to evolve, we’re committed to refining and scaling this solution to meet the needs of our customers and partners. At the end of the day, our mission is simple: to help simplify and expedite the process of getting patients on, staying on, and affording medications.

If you’re a current customer interested in learning more about how to enable this for your organization, please contact your account team or email us at support@infinitus.ai. If you’re not yet a customer but would like to learn more about Infinitus, contact us here.