Paul Crowder

By focusing on transformation with a small “t” that addresses measurable performance gaps, health plans and administrators can use claims automation to control costs and risk

A key component of stopping fraud, waste and abuse is to focus on your most productive targets: Who or what should be the focus of your payment integrity program?

The most effective approach to pre-payment prevention of losses is to risk score your claims, post-adjudication, prior to payment, in production-strength software which uses xAI and machine learning.

AI and machine learning have become popular concepts in payment integrity. But how can they help reduce your losses to health care fraud, waste and abuse?

Given the negative impact of fraud, waste and abuse on health care, it’s in every payer’s interest to focus on these problems. 

So how does a health care payer measure success in payment integrity? How much is enough?