The Pieces Revenue Recovery module is an artificial intelligence and machine learning (AI/ML) toolset that is able to identify specific claims that have an underpayment issue. The system is able to quickly identify these claims that would otherwise be unmanageable through human review.

Problem Statement

There is a complexity to hospital reimbursement that is governed by a variety of measures, insurance contracts, products, place of service, providers rendering service, and state variation. Due to the complex nature of the payment system, many organizations end up losing money through unidentified underpayments. Health systems, providers, and revenue cycle management companies have routine diligence for appealing denied claims. However, they lack the technical ability to identify all underpayments efficiently. Our AI healthcare solution has been designed for this specific purpose.

How AI and Machine Learning Technology Addresses The Problem

The RevReCov Module learns the specific nuances of your organization’s contracts for each insurance plan/product. We then are able to overlay our identification model on top of this information and review historical claims. Through this process we will generate an initial underpayment report. This report will provide two outcomes: First you will see the potential underpayments that are occurring from a historical standpoint. Second, we use this process to train and refine the model to your organization’s specifics. Once underpayments are identified, we will partner with you to appeal and get you money that had previously been written off.
Identify the Underpayment
Once a claim has been processed through an organization’s routine billing process, Pieces identifies the claim and runs it through our AI/ML-driven tools. Identified claims are flagged for underpayment.
Work the Appeals Process
Pieces will begin the appeal process with the insurance provider. The Pieces team will provide supporting details on the underpayment identified.
Provide Updates on Claims
As Pieces works on claims, regular reports will be provided to the organization that reflect the status and progress of the identification and appeals processes.
Collect Revenue
Additional revenues are collected and sent directly to the organization’s billing system.

ROI Benefits

7 to 11% in Underpaid claims
Most hospitals have underpaid claims that total 7 to 11% of their revenue. This money is often written off and not claimed by hospital.
50 to 65% Collection Rate
Of the claims appealed in a timely manner, we are able to collect on 50 to 65% of cases.
Very little staff time required
We do the heavy lift and manage the appeals process so there is minimal interruption to existing billing teams.
Parkview Medical Center
“Other companies have completed underpayment analysis for us and found only a fraction of what Pieces found.”

Ready to Learn More?

Our modular solution can be tailored to your needs. We’d love to schedule a demo to more fully walk you through how Pieces can help you achieve better outcomes for your patients and your bottom line.