Is your Prior Auth logic ready to scale?
You will answer for what prior-auth automation decides — to regulators, your board, and the providers in your network — but you didn't write the medical-necessity logic, and the vendor that built the system never tested whether it's right. The PA Logic Readiness Scan tests that logic against clinically validated synthetic cases — your real policies, no PHI, no security review to clear — before CMS-0057 automation goes live. We don't sell PA software and we didn't write your rules — we test them.
Your vendor moves the request. Ground Truth Systems tests the reasoning.
Scan at a glance
What goes wrong
Automation doesn't fix flawed policy logic. It scales it.
Today, a defective criterion produces wrong determinations one reviewer at a time. The moment your rules engine executes without a human in the loop, it produces them every time: a missing red-flag override that delays urgent imaging, an undefined term that denies adequate care. The failure is silent until it surfaces as an appeal cluster, a provider revolt, or a wrongful-denial story with your plan's name in it.
what payers are spending per implementation to make prior auth computable — with logic testing almost never a line item
of appealed Medicare Advantage prior-auth denials were overturned — evidence the underlying logic fails at scale
CMS-0057 deadline — the date your policy logic starts executing without a human reading the PDF
full or partial Medicare Advantage prior-auth denials in a single year — 4.1M of 52.8M total determinations
The scan
One question, answered with evidence: is this policy logic ready to automate?
We take 3–5 of your highest-risk policies. Using our physician-validated clinical knowledge graph, we break each policy into its explicit criteria, build 25–50 clinically validated synthetic test cases, run them deterministically through the policy's decision logic, and have a licensed clinician decide the correct outcome. Then we show you exactly where the logic agrees with the clinician — and where it doesn't, and why.
How it works
A deterministic engine, not a language model guessing at your policies.
GTS PA Harness treats prior authorization criteria as structured logic, not natural language. We parse your policies into explicit decision trees, build clinically grounded test cases, and run each case through the engine deterministically. The result is a machine-readable verdict with a cite-able rationale, not a probability score — reproducible and auditable, every run.
01
Prior Auth Request
CPT, ICD-10, modifier, place of service, clinical notes — the inputs your engine receives on day one.
02
GTS PA Harness
Clinical knowledge graph + deterministic decision engine + physician adjudication. The layer no vendor sells.
03
Structured Verdict
Approve / deny / pend with cite-able policy rationale and confidence score.
Physician-validated criteria graph
Every CPT code mapped to its coverage conditions, clinical context, and policy exceptions.
Deterministic test runner
No probabilistic hallucination. Same input yields same output, every time, fully auditable.
Explainable output
Every verdict references the exact policy clause and clinical rationale that drove the decision.
What you get
Five deliverables. Zero ambiguity about what to do next.
PA Logic Readiness Report
A policy-by-policy verdict on automation readiness — pass/fail verdict, exact criteria that failed, test cases that exposed the failure, and plain-English business risk. Reproducible, cite-able, board-ready.
Criterion-level test case suite
25–50 clinically validated synthetic patient scenarios per policy, each mapped to the clinical criteria they exercise. Runnable against your vendor's system on day one.
Gap remediation roadmap
Prioritised list of policy rewrites, ambiguity resolutions, and clinical edge cases to address before go-live.
Implementation vendor briefing
A structured handoff document your vendor's engineering team can action — no translation required.
30-day re-test option
After your team addresses the gaps, we re-run the test suite and issue an updated readiness verdict.
The path forward, not just the problem
Every finding comes with a remediation action. You leave the engagement knowing exactly what to fix, in what order, and how to verify the fix worked.
How long it takes
Two to three weeks from intake to verdict. No procurement, no pilot, no security review.
Policy intake & criterion decomposition
We receive your 3–5 policy PDFs. Our clinical team decomposes each policy into its explicit, computable criteria: coverage conditions, required documentation, ICD-10 and CPT mappings, modifier rules, and edge cases.
Test case construction
For each policy, we build 25–50 clinically validated synthetic patient scenarios — no PHI, nothing that needs to clear your security review. Each test case is annotated with the expected correct outcome, the policy clauses it exercises, and the clinical reasoning behind the expected verdict.
Deterministic test run & gap identification
We run every test case through a deterministic simulation of your policy's decision logic. Failures are categorised: missing criteria, undefined terms, conflicting rules, or inadequate clinical rationale.
Report & briefing delivery
You receive the full Readiness Report, the test case suite, the gap roadmap, and the vendor briefing document. We walk your team through the findings in a 90-minute review session.
The missing layer
Every vendor promises automation. Nobody tests whether your policy logic can support it.
Your EHR integration works. Your rules engine is configured. Your vendor has signed off. And your policy logic still contains undefined terms, missing clinical rationale, and criteria that no physician would consistently interpret the same way. This is the layer no vendor sells — and the one that determines whether automation helps or harms.
"The clinical knowledge graph is the hardest part of this problem. Most vendors bought a computable guideline database. That is not the same thing as a physician-validated, CPT-mapped, exception-aware criterion graph built for deterministic evaluation."
— GTS Clinical Advisory Board
Clinical knowledge graph
CPT→criteria mapping with physician-validated edge cases. Vendors sell you the EHR integration. They don't sell you this.
Deterministic test harness
A test runner that evaluates policy logic the same way every time, with no probabilistic variation, so failures are reproducible.
Physician adjudication layer
A licensed clinician decides the correct outcome for each test case. This is the ground truth the test suite is calibrated against.
Who it's for
Built for the executives accountable when automation goes wrong — even though they didn't write the logic or build the system.
Platform & integration · Go-live risk
You delivered the integration and the rules engine. The medical-necessity logic running on them — the part your vendor didn't build — determines whether automation helps or harms.
Systems & audit · Defensibility
You own the systems of record and the audit trail. When a determination is challenged, you need a reproducible, versioned account of the logic that produced it.
Clinical systems · Clinical fidelity
You bridge clinical policy and the systems that execute it. Before the logic runs automatically, you need evidence it decides the way a physician would.
Operations · Exposure
Wrong determinations at scale become appeal volume, provider abrasion, and regulatory exposure — and they land in operations.
NEXT STEP
Which policies are you least confident will hold up the day they execute without a human?
That's the conversation. Thirty minutes, your policy list, and we'll tell you whether a scan makes sense — and if it does, what it will cost and how fast we can move.
SET UP A MEETING →