Rule-Based Authorization Engine

Translates unstructured payer medical policies into machine-executable rules. Each rule represents a discrete coverage criterion—such as age limits, diagnosis-to-procedure pairings, or frequency caps—encoded as if-then logic. This ensures every decision is auditable and reproducible, with zero probabilistic variance. The engine ingests structured clinical data and evaluates it against thousands of rules in milliseconds, returning a definitive approve, deny, or pend outcome.

Performs deterministic matching between extracted patient data and policy requirements. The engine validates:

• Diagnosis-to-procedure alignment: Does the submitted ICD-10-CM code satisfy the policy's covered indications?
• Quantitative thresholds: Are lab values, BMI, or staging criteria within required ranges?
• Temporal constraints: Has the required waiting period or conservative therapy trial been completed? Mismatches trigger a pend with a specific evidence gap notification.

Enforces non-clinical requirements before clinical evaluation begins. The engine validates member eligibility, benefit limits, network status, and referral requirements against real-time payer data. It also checks for duplicate requests, valid CPT/HCPCS code combinations, and required attachments. Administrative failures result in immediate rejection with a clear reason code, preventing unnecessary clinical review cycles.

Maintains a temporally versioned repository of all payer policies. When a payer updates a medical policy—such as lowering the age threshold for a procedure—the engine activates the new rule version on the effective date while preserving historical versions for retrospective audit. This ensures decisions always apply the policy in effect at the time of service, a critical requirement for compliance and appeals.

Handles scenarios where multiple rules apply to a single request. The engine employs a priority hierarchy: payer-specific rules override general guidelines, clinical rules supersede administrative ones, and explicit exclusions take precedence over inclusions. When conflicts cannot be resolved deterministically, the request is flagged for human adjudication with a detailed conflict trace showing which rules collided and why.

Produces a complete, immutable record of every evaluation step. For each authorization decision, the engine logs:

• Which rules were evaluated and in what order
• The specific data elements tested against each rule
• The outcome of each rule evaluation (pass/fail/skip)
• The final determination and the rule that drove it This audit trail supports compliance reporting, appeals, and payer-provider transparency requirements.

A specialized application of natural language processing designed to parse, interpret, and structure the complex clinical logic contained within payer medical policy documents. This technology converts unstructured PDFs and policy bulletins into the machine-readable rules that populate the authorization engine. It handles complex boolean logic, nested criteria, and clinical terminology to automate the otherwise manual process of translating policy into code.

A centralized software component that encodes and manages the complex, frequently changing clinical and administrative logic used by a health plan to adjudicate authorizations. While a rule-based authorization engine executes decisions, the payer rules engine is the broader system of record that governs the lifecycle of those rules. It handles version control, rule conflict detection, and the deployment of updated medical policies into the production authorization workflow.

The automated process of comparing the clinical evidence provided in a request against the specific requirements of a payer's policy to identify missing or insufficient documentation. The rule-based engine performs the initial match, but the gap analysis module interprets a 'non-match' result to generate actionable feedback. It tells the provider exactly what is missing—such as a required lab value or a failed conservative therapy trial—rather than simply returning a denial.

The systematic, automated check that confirms a requested procedure or service aligns with evidence-based guidelines and payer-specific criteria for the patient's documented diagnosis. This is the core function of the rule-based engine. It evaluates structured clinical data against deterministic logic to produce a binary or categorical output: Medically Necessary, Not Medically Necessary, or Pend for Clinical Review. This validation is the definitive step before an authorization is approved or escalated.

The coordination of automated and human tasks across the prior authorization lifecycle, routing requests based on AI confidence scores, queue priorities, and staff availability. The rule-based engine serves as a decision node within this larger orchestration layer. When the engine returns a 'Pend' or 'Not Medically Necessary' result, the orchestrator routes the case to a human reviewer, attaching the specific policy rationale and evidence summary generated by the engine for efficient adjudication.