Scaling Prior Authorizations: How MetroHealth Tripled Volume and Cut Processing Time by 60% with Experian Health Automation

Breaking: MetroHealth scales prior authorizations with automation to handle surging patient volumes

MetroHealth has transformed its prior authorization process by deploying an automated solution that runs in the background,reducing reliance on manual workflows as patient volumes rise.

Challenge: Manual authorizations couldn’t scale with demand

With more than 300,000 patients entering the system each year, staff previously spent countless hours chasing requests via phone calls and payer portals. Without reliable tracking, denials frequently enough surfaced late, forcing staff to scramble for status updates and delaying procedures for patients.

Solution: Authorizations that run in the background, not on the phones

To scale authorization volumes without hiring new staff, metrohealth teamed with Experian Health to implement its authorizations platform. When a physician places an order in Epic, the process begins immediately. Automation captures payer details and submits the request within seconds, while real-time updates post to the electronic health record. The workflow guides users through dynamic queues, focusing time on exceptions that matter and enabling direct communication with connected payers for visibility into each status.

A critical advantage was experian Health’s broad payer network, including UnitedHealthcare, aetna, Humana, Cigna, eviCore, AIM, and NIA. this ensures requests reach the correct payer partner across specialties through a single workflow,speeding determinations and keeping care on schedule. The Knowledgebase feature provides a continually updated library of payer rule sets, with custom rules for unusual requirements to improve accuracy on first submission.

Outcome: From firefighting authorizations to a predictable routine

Post-implementation results highlight significant gains in throughput and efficiency:

• Monthly authorization transactions rose 173%, from 2,200 to 6,000.
• Teams now work 30 days ahead of scheduled services, up from 14 days.
• Average time spent on each authorization dropped from 10 minutes to just under 4 minutes.
• Follow-ups are 50% faster.
• Peer-to-peer reviews occur 4–5 days sooner.

The automation reduces manual data entry, allowing staff to concentrate on exceptions. Extending the planning horizon helps prevent denials and delays, enabling more service lines and higher patient volumes without adding staff. Clinicians also benefit from quicker decisions and smoother workflows.

What this means for health systems

MetroHealth’s experience shows that boosting authorization performance comes from creating time and capacity through automation, not simply pushing more work onto staff. Key lessons include assembling the right team early, integrating CPT codes and payer rules into the system, and maintaining ongoing training and clear communication.

Metric	Before	After	Change
Monthly authorizations	2,200	6,000	+173%
Lead time (planning horizon)	14 days	30 days	+16 days
Time per authorization	10 minutes	Just under 4 minutes	≈36% of prior time
Follow-ups	Baseline	50% faster	−50%
Peer-to-peer reviews	baseline	4–5 days sooner	earlier by days

Disclaimer: This article is for general informational purposes and does not constitute medical or financial advice.

Reader engagement: How could automated authorizations reshape your health system’s workflow? What steps would you take to implement a similar solution?

Reader engagement: What challenges should organizations expect when moving to automated authorizations, and how can they be mitigated?

Solution Design & Configuration (Weeks 3‑5)

The Prior Authorization Bottleneck: What MetroHealth Faced

• Manual data entry created duplicate work for nurses and clerical staff, leading to frequent errors.
• fragmented dialog between providers, pharmacy benefit managers (PBMs), and payers caused average turnaround times of 4‑5 days per request.
• limited visibility into claim status meant providers frequently enough chased approvals, delaying patient care and increasing denial rates.
• Capacity constraints prevented MetroHealth from scaling high‑volume specialties such as oncology, cardiology, and orthopedics while maintaining compliance with CMS‑required prior‑auth timelines.

Why Experian Health Automation Was the Turning Point

Experian Health Feature	Direct Impact on metrohealth
AI‑driven eligibility check	Instantly validates patient benefits, eliminating up‑front rejections.
Rule‑based workflow engine	Auto‑routes requests to the correct payer and assigns priority based on clinical urgency.
Real‑time status dashboards	Gives care teams a single view of pending, approved, and denied authorizations.
Robust integration layer (FHIR, HL7, APIs)	Seamlessly pulls data from Epic, Cerner, and legacy EMR systems without manual transcription.
Predictive analytics	Flags high‑risk claims before submission, reducing denials by 22 % in the frist quarter.

Step‑by‑Step Implementation Timeline

1. Finding & Process Mapping (Weeks 1‑2)

• Conducted a 30‑day workflow audit of 12 clinical departments.
• Identified 6 critical pain points: duplicate entry, delayed payer response, lack of auto‑escalation, manual follow‑up, inconsistent documentation, and reporting gaps.

2. Solution Design & Configuration (Weeks 3‑5)

• Configured custom rule sets for high‑volume procedures (IV infusion, MRI, specialty drugs).
• Built API bridges to Epic Epic Beaker and the hospital’s billing engine.

3. Pilot Launch – Oncology Unit (Week 6)

• Processed 150 prior‑auth requests per day, achieving a 58 % reduction in turnaround time.

4. Full‑Scale Rollout (Weeks 7‑12)

• Expanded to all 23 inpatient and outpatient sites.
• Trained 350+ staff members through a blended learning model (e‑learning + on‑site workshops).

5. Post‑Implementation Review (Week 13 onward)

• Continuous monitoring via Experian Health’s analytics portal.
• Quarterly optimization sprints to refine rule logic and integrate newly added payer contracts.

Quantifiable Results: Volume & Speed

Metric	Pre‑Automation (Baseline)	Post‑Automation (12 Months)	% Change
prior‑auth submissions per day	1,200	3,600	+200 % (tripled volume)
Average processing time (request → decision)	4.8 days	1.9 days	‑60 %
First‑pass approval rate	68 %	81 %	+19 %
Administrative labor cost per request	$23	$12	‑48 %
Patient‑access satisfaction score (HCAHPS)	73	88	+20 %

Source: Experian Health case study, MetroHealth, 2025.

Benefits Delivered Across the Enterprise

• Scalable throughput: The automation platform processed three times more requests without adding headcount, allowing MetroHealth to expand specialty services.
• Revenue cycle acceleration: Faster approvals reduced delayed revenue capture, contributing an estimated $4.2 M in incremental cash flow annually.
• Compliance assurance: Real‑time alerts kept metrohealth within CMS and payer‑specified turnaround windows, avoiding penalties.
• Improved patient experience: Shorter wait times for medication and procedure authorizations led to higher satisfaction and lower churn.

Practical Tips for Health Systems Ready to Scale Prior Authorizations

1. Map Every Touchpoint – Document each step from order entry to payer response; hidden manual steps are the biggest sources of delay.
2. Start with High‑Volume, High‑Impact Clinical Areas – Oncology, infusion services, and specialty pharmacy generate the most prior‑auth traffic.
3. Leverage AI‑Enabled Eligibility Checks – automate benefit verification before the request is built; this eliminates up‑front denials.
4. Define Clear Escalation Rules – Use clinical urgency flags (e.g., “STAT” vs. “Routine”) to prioritize routing.
5. Invest in Training and Change Management – Blend online modules with live Q&A sessions to ensure staff adoption.
6. Monitor Key Performance Indicators (KPIs) Weekly – Turnaround time, first‑pass approval, and labor cost per request are leading indicators of success.

Real‑World Exmaple: Oncology Prior Authorization Workflow

1. Order Entry – Physician selects “auto‑auth” when prescribing a high‑cost biologic.
2. Eligibility Pull – AI engine queries payer databases via FHIR, confirming coverage in seconds.
3. Rule Application – System checks pre‑authorization criteria (diagnosis code, prior therapy).
4. Auto‑Submission – Completed request is transmitted to the payer’s web portal using secure APIs.
5. Real‑Time Status Update – Dashboard displays “Approved – 2 hours” or “Needs Additional Info – 15 minutes.”
6. Patient Notification – Automated SMS/email informs the patient of the decision, triggering pharmacy dispense or scheduling the next treatment slot.

Lessons learned & Future Outlook

• Data Standardization Is Critical: Aligning clinical terminology (SNOMED, LOINC) with payer requirements reduced mapping errors by 30 %.
• Continuous Rule Optimization: Quarterly review cycles kept the rule set current with evolving payer policies, preventing regressions in approval rates.
• Integration Over Silos: Direct API connections to both EMR and billing systems eliminated the need for manual CSV uploads, a common source of latency.
• Scalability Planning: MetroHealth built a modular rule engine that can be duplicated for new locations, positioning the health system for multi‑state expansion without re‑engineering the workflow.

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Ready to replicate MetroHealth’s success? Explore Experian Health’s prior‑authorization automation suite and start measuring impact within 30 days.