Payment Integrity Compass Case Study

The Challenge

Inefficient Underpayment Recovery

Large healthcare systems routinely experience significant underpayments from insurance providers, but lack efficient systems to identify and recover these lost revenues. Traditional claim identification and recovery processes are time-intensive and resource-heavy, making it impractical to pursue smaller-dollar underpayments despite their cumulative impact.

Traditional Recovery Process

📊

Manual Claim Review

Staff manually reviews each claim for variances

9 minutes per claim

❌

Low-Value Claims Ignored

Small dollar amounts not worth manual effort

68% abandoned

💰

Revenue Lost

Millions in recoverable funds left unclaimed

$28M annually

Research & Insights

User Interviews: Conducted one-on-one interviews with healthcare executives, revenue cycle managers, and business office staff across multiple health systems including Cleveland Clinic Foundation. Mental models for primary and secondary personas
Process Analysis: Mapped existing claim review workflows and identified why hospitals don't pursue "small-dollar" underpayments due to manual appeal costs. 68% of claims ignored due to manual review costs
Mental Model Development: Created mental model diagrams based on Indi Young's methodology to understand how revenue recovery specialists and executives think about maximizing contract value. Tasks, goals, and beliefs mapped for primary users
Opportunity Analysis: Analyzed historical underpayment patterns to identify bulk appeal opportunities and define algorithms for the "opportunity engine". $28M annual underpayments identified at alpha partner

Design Process

Design Challenge

How do we make "small-dollar" underpayments ($200-$2,000) worth pursuing when manual review costs $85 per claim? Our solution: Automated detection + bulk processing + predictive recovery scoring = 90% reduction in review time, making even $200 claims profitable to appeal.

1

Mental Model Development

Created comprehensive mental model diagrams based on user interviews to understand how revenue recovery specialists and executives think about underpayment identification and collection processes.

User interview transcripts and recordings
Mental model diagrams for primary and secondary personas
Task, goal, and belief mapping

Mental Model: Revenue Recovery Specialist

Tasks & Actions

Identify

Review claims, flag variances

Validate

Check contracts, compare line items

Prioritize

Calculate ROI, rank by value

Appeal

Prepare docs, submit to payer

Pain Points

"Manual review is too slow—9 minutes per claim"

"Can't afford to pursue small underpayments"

"No visibility into total recovery opportunity"

Design Opportunity

What if we could automate variance detection?

What if bulk processing made small claims profitable?

What if we could predict recovery likelihood?

2

Data Visualization & Interface Design

Translated the $28M opportunity into understandable visualizations for revenue cycle specialists. Designed the Variance Explorer to make line-item comparisons intuitive and actionable, with interactive filtering that helps users identify high-value recovery opportunities at a glance.

Interactive variance dashboard wireframes
Line-item comparison interface design
Recovery probability visualization system
A/B testing with revenue cycle staff

3

Workflow Integration & Automation

Designed streamlined appeal workflows that integrate with existing revenue cycle systems. Created bulk processing capabilities that made pursuing "small-dollar" claims economically viable for the first time, enabling one-click appeal generation from variance detection.

Appeal workflow mapping & optimization
Bulk claim processing interface
Integration with Epic/Cerner revenue cycle modules
User testing with Cleveland Clinic business office staff

4

Executive Dashboard & ROI Reporting

Designed executive-facing dashboards that translated recovered revenue into strategic insights. Created real-time ROI tracking that helped C-suite leaders understand the platform's value and make data-driven contract negotiation decisions with insurance providers.

Executive dashboard wireframes
ROI calculation and visualization
Contract performance analytics
Pilot success tracking metrics

Solution

Intelligent Revenue Recovery Platform

Payment Integrity Compass transforms revenue cycle management from a reactive, manual process to a proactive, data-driven operation. The platform automatically identifies recoverable underpayments while eliminating claims with low recovery potential.

PIC Variance Explorer Dashboard - showing claim variance detection with recovery probability scoring — Variance Explorer Dashboard

Side-by-side view of Expected vs. Actual payments with color-coded probability indicators. Advanced filtering enables revenue cycle specialists to identify high-value recovery opportunities at a glance, while bulk processing capabilities make pursuing small-dollar claims economically viable for the first time.

PIC Appeals Management Dashboard - showing bulk appeal generation and status tracking — Appeals Management Dashboard

Streamlined appeal workflow with bulk processing capabilities. The automated detection and one-click appeal generation reduced review time from 9 minutes to 54 seconds per claim, making pursuing "small-dollar" underpayments ($200-$2,000) economically viable for the first time. Status tracking and recovery probability scoring help prioritize high-value appeals.

Impact

$28M

Cleveland Clinic Recovery

Alpha partner success

75

Health Systems Adopted

Following successful pilot

$350M

Total Platform ROI

Cumulative recovery

90%

Efficiency Improvement

Reduced manual review time

"This application literally prints money!" — Managing Director of Contract Management, Cleveland Clinic Foundation

Payment Integrity Compass (PIC)