Infinx Envisions a Life Cycle Around AI to Improve RCM

Infinx applies AI to revenue cycle management in health care to provide organizations a superior result. Navaneeth Nair, its Chief Product Officer, views AI refinement as a life cycle in which humans constantly monitor and evaluate its results, giving AI feedback so that it keeps up with the evolution of RCM.

Essentially, at Infinx, AI takes on the large volume of low-complexity tasks in order to free human experts to handle the more rare high-complexity tasks.

AI can begin by processing documents: for instance, extracting key information from unstructured fax forms with difficult types of input such as checked boxes. The AI agent can insert an order into a patient record, and even create the record in the EHR. However, AI can also go further, doing the reasoning to process tasks such as understanding denied claims.

Infinx has hierarchies of AI agents. For instance, an initiation agent can determine which payer is responsible for a claim, and hand off a task to another agent that is trained in the rules for that payer.

AI is easier in some ways than human agents to manage. AI tends to reduce variation in handling tasks. Furthermore, it can be improved simply by tweaking some parameter.

Nair works hard to help staff trust AI. He says that they often overanalyze its output and override AI unnecessarily. The life cycle approach builds trust in AI and improves the RCM outcomes for their customers.

Learn more about Infinx: https://www.infinx.com/

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