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Availity Launches New eBook to Shift Healthcare from Reactive Payment Integrity to Upstream Accuracy

By Lauren Towner · 30 July 2026

In brief: Availity has introduced a new payment accuracy model to replace reactive payment integrity, aiming to reduce $18 billion in annual claims rework by shifting error detection upstream in the revenue cycle.

Key facts
Annual Rework Cost$18 billion
Payer ConnectivityOver 95% of payers
Provider ReachMore than 3 million providers
Press Release: Availity Launches New eBook to Shift Healthcare from Reactive Payment Integrity to Upstream Accuracy | Featured Image by FF News

Quick Summary

Availity is tackling healthcare payment integrity friction by introducing a new payment accuracy model. By shifting error detection upstream to the point of submission, organizations can eliminate $18 billion in annual rework costs, reduce provider abrasion, and leverage AI-driven insights to prevent denials before they occur.

How Does Payment Accuracy Reduce Healthcare Administrative Burden?

Payment accuracy solves the problem of downstream claims rework by embedding payer-managed rules and clinical logic directly into the provider's workflow. Instead of waiting for a post-payment audit or a denial, providers receive real-time actionable edits before a claim ever reaches the payer's system. This proactive approach addresses the $25 billion spent annually on claims adjudication, a significant portion of which is tied to preventable errors.

  • Real-time identification of eligibility issues and coding mismatches.
  • Reduced recoupment risks by ensuring payments are correct the first time.
  • Improved cash flow for providers by eliminating long-tail recovery cycles.

By moving these checks upstream, the industry can mitigate the friction identified in the 2026 Availity Abrasion Index, where 70% of payers cited payment integrity as a major pain point.

What Results Can AI Deliver for Denial Prevention?

AI-driven analytics are central to the shift toward payment accuracy, allowing healthcare organizations to scale their denial prevention strategies. By analyzing massive datasets across the Availity network, AI can predict recurring errors and identify patterns that human reviewers might miss. This technology enables a seamless exchange of clinical and administrative data, ensuring that policy guidance is applied at the most effective moment.

  • Predictive error sourcing to stop denials before they are triggered.
  • Pattern recognition to help teams prioritize systemic workflow fixes.
  • Automated interoperability across 95% of U.S. health payers.

This shift allows payment integrity teams to move away from "cleaning up" simple coding errors and instead focus on high-value activities like fraud detection and complex medical necessity analysis.

FF NEWS TAKE:

The shift toward payment accuracy is a necessary evolution for the fintech and healthtech intersection. By addressing the $18 billion rework problem, Availity is moving the needle on operational efficiency. This isn't just a technical update; it's a fundamental change in how healthcare capital flows. Reducing provider-payer abrasion through upstream prevention is the only way to make the revenue cycle sustainable in an era of rising administrative costs.

Frequently asked questions

What is the difference between payment integrity and payment accuracy?

Payment integrity is traditionally a reactive process involving post-payment recovery and lookbacks to ensure claim legitimacy. In contrast, payment accuracy is a proactive model that moves clinical and policy guidance upstream, allowing providers to resolve errors in real time before a claim is submitted to the payer.

How much does the healthcare industry spend on reworked claims?

The healthcare industry spends an estimated $25 billion annually on claims adjudication. Of that total, approximately $18 billion is tied specifically to reworked claims that are eventually paid, highlighting a massive opportunity for cost savings through upstream prevention.

How does AI improve the healthcare revenue cycle?

AI improves the revenue cycle by enabling early identification of claim errors at scale. It helps organizations predict recurring sources of error, provides real-time guidance to providers during submission, and identifies patterns in data to help teams prioritize systemic fixes, ultimately preventing avoidable denials.

About the companies

Availity

Website · 1 story on FF News since 2026

Companies in this story: Availity

People in this story: Megan Smith, Russ Thomas

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