Healthcare Claims Processing
Claims verification requires checking clinical codes, coverage eligibility, and medical necessity for thousands of submissions.
82%
Straight-through rate
99.3%
Coding accuracy
<4 wks
Time to deploy
01
The Problem
The Challenge
Your claims team verifies coding accuracy, coverage eligibility, medical necessity, and provider credentials for every submission, but verification at volume is slow. Submitting without verification leads to denials and rework, while manual checks keep teams focused on routine tasks.
02
How It Works
Per-decision verification across the claims workflow
ActionAI runs each claim through a verification pipeline that scores coding accuracy against documentation, checks active coverage for the service rendered, validates medical necessity, and confirms provider credentials. Claims above your confidence threshold process automatically, while those below are routed to a reviewer with the specific issue identified. Compliance documentation is generated as the system runs, rather than reconstructed at audit time.
03
The Outcome
Fewer denials, faster processing, stronger compliance
Denials decrease because errors are caught before submission. Teams focus on cases that require judgment, while compliance documentation is created as part of normal operations.
Results that speak for themselves
82%
Claims auto-adjudicated
No manual intervention required
99.3%
Code verification
Every code checked against payer rules
60%
Code verification
Errors caught before submission
Healthcare
Healthcare documentation is the legal record: file a prior auth against the wrong payer policy and treatment slides two weeks to the right. A procedure code that doesn't match the chart loops the claim through three appeal cycles before anyone catches it. Ground truth is the payer policy and coding guideline controlling the decision in front of you. ActionAI scores every automated claim and prior auth against those controlling rules, and high-confidence decisions release without a reviewer opening the file. Below threshold, ExEx (Explainable Exceptions) pulls the case and routes it to the reviewer with the failed rule and source chart attached, so they open the case knowing what needs attention.
Related Use Cases
Frequently asked questions
Prior authorizations, medical coding, claim denials, and scheduling — any workflow where an AI is scoring against a known truth source. Each automation deploys individually, so a health system can start with one process and expand.
Cases that score below threshold drop out of the automated flow and route to a human reviewer with full context, under the Explainable Exceptions (ExEx) protocol. Nothing below threshold gets auto-submitted.
No. ActionAI runs on top of the systems you already have, through API or data export — no replacement needed. Clinicians and administrators keep the interface they know.
SOC2 compliant with SSO and encryption, deployed in cloud, VPC, or on-premises based on what the environment requires. The deployment model gets set in the initial scoping call.
A 1-2 hour scoping call identifies the highest-ROI process, followed by a free pilot on real data — days to weeks, not months. Impact is measured from your own data during the pilot.