RCM Intelligence Platform Reduces Cost per Collected Dollar for Multi-Location Healthcare Provider

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Client Details: Healthcare Provider Managing High-Volume Claims

A growing healthcare organization operating across multiple locations and payer networks faced increasing operational complexity within its revenue cycle. As billing, AR management, and payer interactions expanded across systems and teams, the cost of revenue cycle execution continued to rise despite stable collection performance.

Project Challenge: Rising Cost of Collections Across Fragmented RCM Workflows

The organization’s revenue cycle operations were optimized for individual tasks such as billing accuracy or AR recovery but lacked a system that optimized the economics of the revenue cycle end-to-end. Fragmented workflows across billing teams, AR teams, and multiple systems increased operational friction and raised the overall cost of collections.

Key Challenges

  • Fragmented revenue cycle workflows
  • Rising labor cost per collected dollar
  • Repeated denial and rework loops across claims
  • High volume of low-yield AR follow-ups

Deliverables Requested

  • Revenue Cycle Orchestration Platform
  • Billing Intelligence for denial prevention
  • AR Intelligence for recovery prioritization
  • Workflow orchestration across systems and teams
  • Cost-per-collection performance visibility

Solution Delivery: Deploying an RCM Intelligence Control Plane

Flatworld implemented RCM Intelligence, a revenue cycle control plane designed to orchestrate billing intelligence, AR prioritization, and workflow coordination across existing healthcare systems. Rather than replacing EHR or billing systems, the platform created a decision and orchestration layer that optimized how work is generated, prioritized, and executed across the revenue cycle -

1

Revenue Cycle Diagnostics & System Mapping

The engagement began with analysis of claim flows, denial patterns, collector activity, and cost drivers. This assessment identified upstream billing risks and downstream recovery inefficiencies impacting the economics of collections.

2

Billing Intelligence Implementation

RCM Intelligence analyzed CPT-payer denial patterns, authorization mismatches, documentation risks, and first-pass yield failures. These insights helped prevent avoidable denials and reduce downstream rework before claims entered AR.

3

AR Intelligence & Work Prioritization

Recovery probability scoring and yield-weighted follow-ups were introduced to prioritize high-value recovery opportunities. Collector effort was dynamically allocated based on payer behavior and recovery likelihood.

4

Workflow Orchestration Across Systems

The platform coordinated activity across EHRs, clearinghouses, payer portals, RPA tools, and operational teams. This orchestration reduced fragmented worklists and ensured coordinated execution across the revenue cycle.

5

Closed-Loop Revenue Cycle Optimization

Denial outcomes and recovery results were continuously fed back into billing and AR workflows. This closed-loop system improved claim quality, optimized collector effort, and reduced repeated operational friction.

Case Study1

Transforming Revenue Cycle Operations into a Cost-Optimized System

By introducing an orchestration layer across billing intelligence and AR operations, the organization transitioned from fragmented revenue cycle workflows to a coordinated, cost-optimized operating system. Through its RevOps Transformation engagement, Flatworld.ai applied the RCM Intelligence approach to reduce operational friction, improve workforce productivity, and control the cost of collections while preserving revenue integrity.

If revenue cycle costs are rising despite stable collections, explore how Flatworld.ai’s RevOps Transformation can optimize your cost of collections.

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