Accuracy with Intelligence Engine

Enable CMS-0057 — without replacing your UM system.

Intelligence reads. Rules decide. A deterministic prior-auth engine that plugs into the UM ecosystem you already run — so you meet the mandate in weeks, not a rip-and-replace.

  • The CMS-0057 front door — FHIR CRD/DTR/PAS — on top of the system you already run.
  • Plugs into your existing UM system — Jiva, HealthEdge GuidingCare, MedHOK, Evolent & more — via their own APIs.
  • Intelligence scans every document; a deterministic engine built for your policies decides — and never denies on its own.
  • Deploys single-tenant in your own cloud — no member data ever leaves your environment.
Da Vinci CRD·DTR·PASPlugs into Jiva, HealthEdge GuidingCare, MedHOK, Evolent & moreBuilt for CMS-0057-F
How plug-and-play works

One engine that integrates with your existing stack.

The Accuracy with Intelligence Engine sits between your intake and your system of record. It provides the compliant front door, auto-adjudicates against the policies your team codified, and writes the result straight back into the UM system you already run.

Intake

Omnichannel intake

FHIR CRD/DTR/PAS · provider portal · fax OCR · X12 278 · delegated-MCO files — every channel, one front door.

The engine

Accuracy with Intelligence Engine

Intelligence scans; rules decide against your policies and cite every criterion. Auto-approves the clean cases, routes the rest to your clinicians. Never denies on its own.

Your system of record

Your existing UM system

Writes the authorization or opens the case in Jiva, HealthEdge GuidingCare, MedHOK, Evolent or your homegrown UM — via that system's own APIs.

1

Meet the request on any channel

Providers submit via the FHIR prior-auth APIs, your portal, fax, or X12 278 — the engine normalizes it all into one canonical case.

2

Decide deterministically against your policy

Intelligence extracts the clinical facts; the deterministic engine evaluates them against your codified criteria and cites each one. Clean cases auto-approve; anything adverse routes to a licensed clinician — it never denies on its own.

3

Write back into your UM system of record

Pluggable connectors map the outcome — authorization, dates, criteria cited, or a pended case/task — into Jiva, HealthEdge GuidingCare, MedHOK, Evolent or your homegrown system through its own APIs. Idempotent, reconciled, fully audited.

4

Report the mandate metrics

Decision timeliness and the CMS-0057 prior-authorization metrics are captured on every transaction — audit-ready by design.

The fast path

The CMS-0057 front door your legacy UM doesn't have.

Most established UM systems weren't built for the Interoperability & Prior Authorization Final Rule. The engine supplies the FHIR APIs, decision timeliness and reporting the mandate expects — on top of the system you already run.

CRD Coverage RequirementsDTR Documentation RulesPAS X12 278FHIR R4 APIsDecision timelinessPA metrics reportingFull audit trail

Why start with the engine

✓ Compliant in weeks — no rip-and-replace of your system of record.

✓ Your reviewers keep working in the tool they already use.

✓ Straight-through auto-adjudication on the clean cases.

✓ Clinician-in-the-loop — the engine never auto-denies.

✓ Single-tenant in your cloud — PHI never leaves your tenant.

Downstream connectors

Writes into the UM system you already run.

A pluggable connector framework maps the engine's canonical decision into your system of record — over whatever transport that system speaks.

🗂️

Your UM systems

Jiva, HealthEdge GuidingCare, MedHOK, Evolent or a homegrown platform — a connector per system maps auths, statuses, criteria cited, documents and notes.

System of record stays yours
🔗

Any transport

REST/JSON, SOAP, X12 278/275, HL7v2, FHIR or SFTP batch — with RPA as a fallback where a system has no open write API.

Meets legacy where it is
🧭

Configurable mapping

Canonical-to-vendor field mapping and code crosswalks are configured, not coded — the same mapping tooling used for MCO intake.

Configure · test · publish
🛡️

Write integrity

Idempotency keys, downstream IDs stored back on the record, retries with a dead-letter queue, and status reconciliation — nothing is lost.

Reliable · reconciled · audited
Conceptual architecture

How the engine is put together.

A thin, deterministic layer between your intake and your system of record — every part of it running inside your own cloud tenant.

Your cloud tenant · BYOC single-tenant · PHI never leaves
1 · Omnichannel intake
FHIR CRD / DTR / PAS Provider portal Fax OCR X12 278 Delegated-MCO files → normalized to one canonical case
2 · Accuracy with Intelligence Engine
Intelligence scanReads every document; extracts the clinical facts.
Policy libraryYour codified policies as executable CQL & criteria.
Deterministic decisionEvaluates criteria and cites each. Auto-approve or route — never auto-deny.
OrchestrationQueues, worklist allocation and hand-off to your clinicians.
3 · Connector framework
REST / JSON SOAP X12 278 / 275 HL7 v2 FHIR SFTP batch idempotent · reconciled · retried
4 · Your systems of record
Jiva HealthEdge GuidingCare MedHOK Evolent Homegrown UM
Cross-cutting FHIR R4 APIs + SMART Backend auth RBAC / SSO Full audit trail CMS-0057 metrics & reporting Encryption in transit & at rest

The engine is the system of decision; your incumbent stays the system of record. Turn on the full workbench later and the same deployment becomes the system of record too.

Land, then expand

Start with the engine. Grow into the platform.

Because it's the same deployable, the engine is the on-ramp to the full AI-UM Care suite. Meet the mandate today; switch on the workbench, letters, appeals and analytics when you're ready to modernize your system of record — with your data and decisions already in place.

See the engine run against your own policies.

Book a personalized demo — we'll show intake, deterministic decisioning and a write-back into a sample UM system.

Or email salesinfo@aiumcare.com

CMS-0057 FAQ

CMS-0057 & utilization management, answered.

The prior-authorization mandate, the deadlines, and how to comply without replacing your UM system.

What is CMS-0057-F?

CMS-0057-F is the CMS Interoperability and Prior Authorization Final Rule, finalized in January 2024. It requires impacted health plans to streamline prior authorization with FHIR-based APIs, faster decision timeframes, specific denial reasons, and public reporting of prior authorization metrics.

Who has to comply with CMS-0057?

Medicare Advantage organizations, state Medicaid and CHIP fee-for-service and managed care programs, and Qualified Health Plan issuers on the Federally-Facilitated Exchanges.

When is the CMS-0057 prior authorization API deadline?

The FHIR Prior Authorization API, along with the Patient Access, Provider Access and Payer-to-Payer APIs, must be in place by January 1, 2027. Faster prior authorization decision timeframes took effect on January 1, 2026.

What are the CMS-0057 prior authorization turnaround times?

72 hours for expedited (urgent) requests and 7 calendar days for standard requests, effective January 2026.

What FHIR APIs does CMS-0057 require?

Four: Patient Access, Provider Access, Payer-to-Payer, and the Prior Authorization API. The Prior Authorization API uses the HL7 Da Vinci CRD, DTR and PAS implementation guides.

How can we meet CMS-0057 without replacing our UM system?

The AI-UM Care UM Engine plugs in front of your existing utilization management system as a CMS-0057 front door, providing the FHIR CRD/DTR/PAS APIs, deterministic auto-adjudication, and writing decisions back into Jiva, HealthEdge GuidingCare, MedHOK, Evolent or a homegrown system through their own APIs.

What prior authorization metrics must payers report under CMS-0057?

Payers must publicly report metrics each year, including approval and denial rates and average decision turnaround time, and every denial must include a specific reason.

Is AI-UM Care deployed in our own cloud?

Yes. AI-UM Care deploys single-tenant inside your own cloud tenant (BYOC), so PHI, documents and decisions never leave your environment.