prior-auth-review-skill

Automating prior authorization reviews requires collecting PA request details, validating provider credentials and codes, and generating a formal decision package with policy-aware reasoning. This skill processes intake, validates evidence against coverage policies, and outputs APPROVE, PEND, or DENY recommendations with supporting documentation.

AI-assisted prior authorization validation extracts clinical data from PA requests, checks provider credentials and codes via parallel MCP validation, and evaluates evidence against CMS coverage policies. It generates rubric-driven outcomes with audit trails and human review support for consistent decision-making.

Yes, MCP validation runs in parallel during the intake and assessment phase to verify provider credentials and codes. The skill uses MCP to support policy-informed recommendations, ensuring prior authorization requests meet compliance requirements before generating a formal decision.

Generating audit trails for prior authorization decisions involves producing final decision content, provider notifications, and supporting documentation through the decision and notification workflow. The skill creates structured authorization packages with rationale, ensuring every APPROVE, PEND, or DENY outcome is traceable.

Prior authorization review evaluates extracted clinical evidence against CMS coverage policies to generate policy-driven decisions. The skill validates request details, applies configurable rubrics, and produces recommendations with documented rationale aligned to CMS requirements.

AI-assisted prior authorization review generates draft decisions and recommendations that require human review before finalization. It supports configurable rubric-driven outcomes but does not replace clinical judgment, serving as a decision support tool with audit trails for payer organizations.