Payer Medical Policy Extraction

Ingests complex, multi-format payer bulletins—including PDFs, HTML, and scanned faxes—and reconstructs the logical document hierarchy. This process identifies distinct policy sections, such as Coverage Criteria, Exclusions, and Billing Guidelines, by analyzing visual layout cues and heading semantics rather than relying on brittle template matching.

• Detects multi-column layouts and nested tables
• Preserves the semantic relationship between a policy header and its subordinate criteria
• Handles embedded images and unstructured text blocks

Transforms free-text clinical conditions into a structured, queryable format by mapping them to standard terminologies. A policy stating 'Patient must have NYHA Class III or IV heart failure' is parsed to extract the logical operator (OR), the clinical concept (Heart failure), and the value set (NYHA Class III, NYHA Class IV).

• Maps textual descriptions to ICD-10-CM, CPT, and LOINC codes
• Resolves synonyms like 'hypertension' and 'high blood pressure'
• Structures complex boolean logic (AND/OR/NOT) for a rules engine

Identifies and structures quantitative limits and time-bound requirements embedded in policy text. This includes extracting statements like 'failure of a 3-month trial of conservative therapy' into discrete duration (3 months) and therapy type (conservative) constraints.

• Parses age restrictions, frequency limits, and lab value thresholds
• Normalizes relative time expressions ('recently', 'within the last year') to absolute ranges
• Captures dosage and quantity limits for pharmaceutical policies

Automatically identifies differences between successive versions of a payer's medical policy to maintain an up-to-date rules repository. The system performs a semantic diff that highlights not just textual changes, but modifications to the underlying clinical logic.

• Flags additions, deletions, and modifications to coverage criteria
• Timestamps and archives superseded policy versions for audit trails
• Triggers alerts for rules engineers when a critical clinical constraint is altered

Aggregates and aligns coverage criteria from hundreds of distinct payer policies into a unified, normalized data model. This allows a provider's authorization system to query a single interface for a specific procedure rather than navigating disparate payer-specific formats.

• Creates a canonical data model for a clinical service (e.g., knee arthroplasty)
• Maps each payer's unique phrasing to the common model
• Exposes a single API endpoint for real-time coverage verification across payers

Translates the extracted, structured logic into a human-readable and auditable format alongside the executable code. For every automated decision, the system can cite the exact source paragraph and payer policy document that justified the determination.

• Generates plain-language summaries of complex boolean rules
• Links each executable rule back to its source document and page number
• Provides a full audit trail for compliance and appeals processes

The algorithmic process of comparing a patient's structured clinical data against the machine-readable rules extracted from a payer's policy. This is the core engine that determines if coverage criteria are met.

• Ingests FHIR resources representing patient diagnosis, labs, and medications
• Evaluates extracted policy rules as a decision tree against patient context
• Outputs a determination: Met, Not Met, or Insufficient Data

The essential preprocessing step that maps diverse clinical terms to a single standard terminology, enabling consistent matching. Without this, 'high blood pressure' in a note won't match 'essential hypertension' in a policy.

• Maps free-text mentions to SNOMED CT for diagnoses
• Normalizes drug names to RxNorm for medication criteria
• Translates lab tests to LOINC codes for value comparison

An automated process that identifies the specific delta between the clinical evidence provided and the requirements defined in the extracted policy. It pinpoints exactly what is missing before submission.

• Compares available patient data against all required policy elements
• Flags missing documents, labs, or prior treatment history
• Generates a provider-facing checklist to close documentation gaps proactively

A deterministic software system that consumes the structured output of policy extraction to automate decisions. It applies if-then logic without probabilistic variation, ensuring auditable, repeatable outcomes.

• Encodes extracted criteria as executable business rules
• Integrates with real-time eligibility verification
• Auto-approves straightforward cases, routing only complex exceptions for human review

The centralized repository and execution environment that manages the lifecycle of encoded medical policies for a health plan. It is the operational backbone for scaling automated clinical review.

• Versions and tracks changes to policy-derived rules over time
• Supports rapid reconfiguration as payer bulletins are updated
• Provides an audit trail linking every automated decision back to the source policy text