By Peter Joseph – Artificial intelligence (AI) is a concept that has moved very quickly from the realm of science fiction into real and practical utility in a number of different industries—including healthcare.

One of the most effective applications for AI-powered tools is in the field of revenue cycle management. Sophisticated AI technologies can sift through vast amounts of data and parse nuances in ways that can make tasks such as claims and denials management vastly more efficient and effective. Understanding how those tools work—and best practices associated with their introduction and optimization—should be a priority for healthcare professionals.

When it comes to using AI to maximize workflow in revenue cycle management systems, one of the most important requirements understanding your core challenges. Use outcomes-based analytics that add context to the data and determine what is and isn’t working.

Payer denials of submitted claims, for example, involve a rich set of data that could indicate a wide range of potential problems. The issue could be in the claims process itself, the documentation, the training, or the execution. But if you don’t understand the root of the problem, you won’t be able to design an effective solution—or even determine if an AI tool could be a productive remedy. AI-driven support is likely to be most effective when implemented throughout high-touch processes, or those processes that are regularly problematic and require frequent and continued intervention. Read On: