Prior authorization, automated.

A Fortune 500 healthcare payer transformed prior auth from a clinician backlog and patient pain point into a triaged, AI-assisted workflow — without making a single clinical decision the system shouldn't be making.

Client

Fortune 500 payer (anonymized)

Industry

Healthcare / Insurance

Scope

Multi-phase

Departments

UM · Clinical Operations

Outcomes

Faster decisions, safer ones.

~70% routine cases auto-approved
~40% reduction in complex review time
Days→Hrs patient wait time on routine cases
Up clinician satisfaction (internal survey)

01 The challenge

Prior authorization (PA) — the insurance-side approval step before a clinician can proceed with a treatment, test, or procedure — is the most painful workflow in US healthcare for clinicians, for patients, and for the payers running it. A Fortune 500 healthcare payer was processing millions of prior auth requests per year, with clinical reviewers buried in repetitive documentation review and policy lookups. Patients waited days for decisions. Clinicians stopped trusting the system. The payer needed AI that could safely automate the routine cases, surface the high-judgment cases to clinicians faster, and never make a clinical decision the system shouldn't be making.

02 The approach

BizzSoftware partnered with the payer's Utilization Management and Clinical Operations teams to design and build an AI-assisted prior authorization application. Three principles drove the design:

Clinical safety first.

AI handles parsing, lookup, and routine approvals. High-judgment cases route to clinicians faster, with all evidence pre-organized.

Auditable end-to-end.

Every AI decision logged with full chain of evidence — supporting regulatory and audit obligations.

Designed for the clinician's day.

UM nurses and physicians use the system thousands of times per shift. Built around speed and clarity.

03 What we built

  • AI-assisted intake and triage

Incoming prior auth requests parsed, classified, and routed; routine cases auto-approved against verified criteria, complex cases pre-prepared for clinician review.

  • Clinical reviewer workspace

UM nurses and physicians work cases with all relevant clinical and policy evidence surfaced in context.

  • Governance and audit infrastructure

Full decision lineage on every output, supporting regulatory, audit, and quality review.