For a large health system, we built a claims platform that matches EHR evidence to payer rules, automates routine authorisations and logs every decision. It is built to HIPAA requirements. Claims recovery rose 42%, and staff saved 15k hours.
Industry: HealthcareService: AI & AutomationUpdated
Overview
The challenge
The client's older RCM system depended on manual clinical reviews, and reviewers could not keep up with changing payer policies. Its medical necessity denial rate ran 42% above the national average, leaving millions in claims unrecovered.
Procedures waited 3-5 days for authorisation, and some were cancelled while patients waited. Clinical notes still moved by fax, so nobody could say which evidence had supported a decision.
Incomplete documentation triggered automatic payer denials, permanently losing 5-8% of potential net patient revenue.
Specialists spent 20% of their day on manual peer-to-peer reviews instead of patient care.
Sharing clinical notes by fax and older portals left gaps that auditors could flag under new HIPAA privacy rules.
The solution
We built a secure workflow that pulls clinical evidence from the EHR and strips out any personal information the payer does not need.
AI tools read each payer's medical policy PDFs and match them against the patient's clinical documentation as it is written.
Each automated authorisation is stored with the clinical reason codes behind the decision, giving a clear trail for payer audits.
Before and after
Before
Faxes and PDFs
Staff pulled clinical notes out by hand, so evidence was missed and denials stayed high.
After
Connected health records
Clinical data flows in live and is matched to payer policy automatically, within HIPAA rules.
Before
Reviewer judgement
Each decision depended on one reviewer's experience, with no consistent audit trail.
After
Clear, logged rules
Logs record the exact clinical details used to justify every authorisation.
Before
3-5 Day Lag
Authorisation backlogs led to cancelled procedures and anxious patients.
After
Sub-2s scoring
Automatic scaling keeps responses under 2 seconds, even at peak clinical hours.
Key features
Language AI finds and anonymises sensitive patient data before anything reaches the AI models.
Business impact
Zero patient data leaks
The AI works like an automated clerk, moving through EHR screens to find the exact lab result a payer asks for.
Business impact
94% evidence accuracy
An authorisation request goes out the moment a physician enters an order, with no wait for a person to pick it up.
Business impact
42% recovery lift
Results
42% Recovery Increase
Claims that were often denied for missing information now go in with the right evidence, and recovery is 42% higher.
Before: High-DenialAfter: 42% Higher
15,000 Annual Hours
AI now handles 90% of routine authorisations, so staff can focus on complex appeals.
Before: ManualAfter: Automated
1.8s Response Time
Each automated authorisation check now returns in 1.8 seconds, so clinicians are not kept waiting on paperwork.
Before: < 5sAfter: 1.8s
Faster delivery
Reusing tested components saved about 8 weeks, which went into matching EHR evidence to each payer's policies.
Gave the project a tested, HIPAA-aligned base for pulling EHR data into the client's private cloud.
Gave the AI a tested clinical vocabulary for matching doctors' notes to payer policy wording.
Alerted the team when an EHR connection slowed or failed, before authorisations began to queue.
Tracked the cloud and AI cost of each authorisation as volumes grew.
Trust and control
Each decision carries clinically mapped reason codes, which makes payer and regulatory audits easier.
Audit readyAll patient health information stays inside the client's virtual private cloud, covered by a business associate agreement (BAA).
HIPAAThe cloud platform runs at 99.99% uptime for essential clinical work.
High availabilityOn completion, the client owns 100% of the IP in the AI models and custom health-record connections.
100% ownedIts revenue cycle team checked clinical evidence by hand and could not keep up with changing payer policies. Medical necessity denials ran 42% above the national average, and incomplete documentation cost 5-8% of potential net patient revenue. Specialists also spent 20% of their day on manual peer-to-peer reviews.
When a physician enters an order, the system starts an authorisation request. AI reads each payer's medical policy PDFs, finds the matching evidence in the EHR, such as a specific lab result, and scores the request in under 2 seconds. Every decision is stored with the clinical reason codes behind it.
A language AI layer finds and anonymises sensitive patient data before anything reaches the AI models. All patient health information stays inside the client's virtual private cloud, covered by a BAA. Authorisation records sit in write-once storage with their reason codes, so payer and regulatory audits can trace every decision.
If prior authorisations still depend on manual chart reviews, we can help you match EHR evidence to payer rules automatically and keep a clear audit trail.