How to Automate Prior Authorization: Eligibility, Clinical Criteria, Documentation and Payer Response

Before anything else, verify (via eligibility check, Da Vinci CRD where supported, or a maintained payer-requirements reference) that this specific procedure requires prior authorization for this specific patient's specific plan. Skipping this and assembling a full authorization request for a service that doesn't need one wastes clinical staff time reviewing something unnecessary - this step should be cheap and fast, and should short-circuit the rest of the workflow when authorization isn't required.

Retrieve the payer's specific medical necessity criteria for the requested service (from a maintained policy reference, since these aren't always available programmatically) and extract supporting evidence from the patient's record against each criterion, flagging gaps. This is the step where AI-assisted extraction adds the most value, but its output should be reviewed, not auto-submitted - the review step is a checkpoint, not a bottleneck to design around.

Package the reviewed clinical evidence into whatever format the payer accepts - a structured Da Vinci PAS submission where supported, a portal form or fax where it isn't - and record the submission with enough detail (what was sent, when, to whom) to support tracking and, if needed, an appeal. Design this step to be payer-agnostic at the workflow level even though the actual submission mechanism varies significantly payer to payer; the workflow orchestration shouldn't need to change every time a new payer with different submission requirements is added.

Track the request through pending, approved, denied, or 'additional information requested' status - via structured API response where available, or staff-updated status where the submission channel is manual. A denial or additional-information request should route back into the workflow at the appropriate step (usually documentation gathering, if more evidence is needed) rather than becoming a dead end that requires starting the whole process over manually.

Given how unevenly Da Vinci standards are adopted across payers, full end-to-end automation isn't realistic for every payer yet - the practical goal is automating and accelerating each step as much as the payer's own systems allow, with a reliable human-assisted path for the steps (often submission, sometimes status tracking) that still require it for a given payer. A workflow designed this way gets meaningfully faster and less error-prone even before every payer supports full API-based automation.