Infrastructure for Prior Authorization Automation

Prior authorization automation requires formal, machine-readable documentation of each payer's PA requirements: which procedures require authorization, what clinical criteria must be met, which forms must be submitted, and what documentation is required as supporting evidence. This cannot remain tribal knowledge held by PA specialists. When the system automatically generates a PA request for an MRI, it must apply explicitly formalized rules—IF (CPT=70553 AND Payer=Aetna AND Diagnosis=G35) THEN SubmitForm=Aetna_MRI_PA WITH RequiredDocs=[Neurologist_Note, Prior_Treatment_Failure]. Generic documented policies are insufficient; machine-readable rule logic is required.

PA automation requires systematic capture of ordered procedures, clinical indications from EHR, PA submission events, payer decisions, and turnaround times through defined revenue cycle workflows. Every PA request must generate a complete record with procedure ordered, clinical criteria documented, submission timestamp, payer response, and outcome. Template-driven capture ensures the AI has complete workflow data to track PA status, trigger follow-up, and identify patterns in approval and denial rates by payer.

PA automation requires formal ontology mapping clinical entities to PA requirement rules: Procedure entities linked to Payer-specific authorization requirements, Diagnosis entities linked to medical necessity criteria, and Patient clinical data fields linked to required documentation elements. Without formal mapping between CPT codes and payer-specific form fields, the AI cannot automatically extract the correct clinical evidence from the EHR and populate payer portal submission forms. This is beyond consistent schema—it requires explicit relationship mapping between clinical data and PA form requirements.

PA automation requires unified API access across EHR (clinical documentation, diagnoses, treatment history), order management (procedure details), scheduling (appointment timing), and payer portal interfaces—all queryable through a single access layer. The AI must assemble complete clinical context from multiple systems and submit to payer portals without human intermediaries at each data retrieval step. Without a unified access layer, the system must separately authenticate and query each system, creating latency and failure points that prevent real-time PA submission.

Payer PA requirements change frequently—new procedures added to authorization lists, clinical criteria updated, form formats revised. When a payer modifies its PA criteria for a procedure category, the automation engine must update within hours, not days. A 24-hour lag means procedures ordered today are submitted with outdated criteria, generating denials that require manual appeals. Near-real-time sync between payer policy updates and the PA automation rule base is required to prevent systematic submission errors.

PA automation requires an integration platform orchestrating data flows between EHR (clinical documentation), order management (procedure details), scheduling (appointment dates), payer portals (submission and status), and the revenue cycle system (authorization tracking). These systems must share context in a coordinated, orchestrated manner—not via point-to-point connections that require separate integration logic for each system pair. An iPaaS layer handles the event-driven workflows: procedure order triggers clinical data extraction, which triggers PA form generation, which triggers payer portal submission, which triggers status monitoring.