Prior auth automation: what works, what doesn't

Prior authorization costs the US healthcare system an estimated $35 billion annually in administrative expense. It delays care, demoralizes physicians, and generates an enormous amount of clerical work that produces no clinical value.

AI-powered prior authorization tools are one of the clearest ROI cases in healthcare AI. They work. But not everywhere, not always, and not without investment.

What works

Electronic prior authorization platforms that integrate directly with payer portals can automate submission for a significant portion of requests, typically between 40 and 70 percent of cases, depending on the payer mix and the specialty.

AI tools that predict prior authorization requirements, identifying which orders are likely to require authorization before the order is placed, can reduce the number of delayed authorizations by enabling earlier submission.

What doesn't work

Automation that handles the easy cases and creates more work on the hard cases than a manual process would. If your AI platform automates 60 percent of requests but increases the complexity of the remaining 40 percent, your net productivity gain may be zero.

Point solutions that do not integrate with your EHR, your revenue cycle system, or your payer contracts. Prior auth automation that lives outside the workflow is not automation, it is an additional workflow.

The procurement question

Ask vendors: what is your automation rate for our specific payer mix? What happens to requests your system cannot handle? And how does your system handle the edge cases, the denials, the peer-to-peer review requests, the appeals?

The vendors who answer these questions with specificity are the ones worth talking to.