Claims intake and clinical documentation automation.
60%
Less admin time
3.2M
Claims/yr
8 wks
To production
99.4%
Field accuracy
Where operations were breaking down.
Care teams across 18 facilities were spending up to 40% of clinical hours on documentation: patient intake forms, prior-authorization paperwork, and claims adjudication. The administrative tax was eroding patient-facing time and contributing to clinician burnout.
Claims processing was particularly painful. A typical claim moved through six handoffs before reaching the payer, each one introducing transcription errors that caused downstream denials. Rework cycles were running at 14% of total volume.
Leadership needed a system that could ingest both structured (EHR) and unstructured (faxes, scanned forms, handwriting) inputs, normalize them, and route them through the existing claims pipeline, without forcing clinicians to change their documentation habits.
How Aelix Nexus was deployed.
Multi-modal document AI
OCR and handwriting models handle scanned intake forms, faxed referrals, and prior-auth letters. Structured data flows directly from the EHR via FHIR connectors.
Clinical NLP extraction
Named-entity recognition pulls diagnosis codes, procedure codes, and supporting documentation from free-text physician notes with confidence scoring.
Claims routing agents
AI agents validate completeness against payer-specific rules and route claims down the right pathway. Exceptions queue for human review with full context.
Audit-grade trail
Every extraction and routing decision is logged with model version, confidence, and reviewer ID, meeting HIPAA audit and payer dispute requirements.
From source data to operational action.
Stage 01
EHR + documents
FHIR streams from the EHR plus scanned intake forms, faxes, and prior-auth letters.
Stage 02
OCR + NLP
Document AI extracts structured data; clinical NLP pulls diagnosis and procedure codes.
Stage 03
Validation agents
AI agents check completeness against payer-specific rules and flag exceptions.
Stage 04
Submission + audit
Validated claims submitted to payers; every decision logged with model version and confidence.
Stage 01
EHR + documents
FHIR streams from the EHR plus scanned intake forms, faxes, and prior-auth letters.
Stage 02
OCR + NLP
Document AI extracts structured data; clinical NLP pulls diagnosis and procedure codes.
Stage 03
Validation agents
AI agents check completeness against payer-specific rules and flag exceptions.
Stage 04
Submission + audit
Validated claims submitted to payers; every decision logged with model version and confidence.
Operational gains after going live.
0%
Less administrative time
Across clinical and revenue-cycle teams, time freed up for patient-facing work.
3.2M
Claims processed annually
Across 18 facilities, with consistent accuracy regardless of intake source.
14% → 4%
Claim denial rate
Upfront validation catches errors before submission instead of after rejection.
8 wks
From kickoff to production
FHIR-native integration with existing EHR meant no clinician workflow changes.
0.0%
Field-level accuracy
On structured fields across both typed and handwritten document sources.
$4.6M
Annualized recovery
Combined denial-rate reduction, faster reimbursement cycles, and rework elimination.
See what Aelix Nexus would do for your operations.
Talk to our team about the bottlenecks slowing you down, and the system we'd deploy to remove them.