Crowe Healthcare Exceptions Resolution

What If We Could Resolve Most of Your Exceptions Using Machine Learning?

 

Welcome to the workforce of the future.

Resolving denials, credits, and other revenue cycle exceptions has evolved. Is your organization ready for the claims collector of the future?

Crowe Exceptions Resolution proprietary algorithms have identified solutions for 60 percent of clients' credit accounts* and 40 percent of amount owed, allowing thousands of accounts to be automatically resolved with minimal human interaction.

Are you ready to improve accuracy, reduce costs, and optimize staff productivity?

*Findings for the 0-30 days past-due population  

Before Exceptions Resolution

Your healthcare organization has likely faced revenue cycle exceptions arising from bad debt, credit balances, denials, small balances, and underpayments.

  • 2002
    Manual
    Review

    15 minutes spent per account-touching every account; volume drives staff numbers

  • 2006
    Data
    Analytics

    Logic-based themes using fewer resources, 30-40% resolution

  • 2014
    Machine
    Learning

    Incorporating data science using minimal resources, 60-70% resolution

HOW IT WORKS

How Machine Learning Can Transform Your Revenue Cycle

This iterative process can move your organization toward a "zero defect" approach to exceptions cost-effectively and automatically.

HOW IT WORKS

How Machine Learning Can Transform Your Revenue Cycle

This iterative process can move your organization toward a "zero defect" approach to exceptions cost-effectively and automatically.

  • Craft

    Determine best resolution paths (via best performers, plus other organization data) to establish performance standards.

  • Standardize

    Institute best-practice pathways into work processes (via education and new monitoring structures) and align performance management metrics.

  • Systematize

    Integrate best-practice resolution pathways into technology workflows, including predictive analytics for clustered accounts (e.g, write-offs).

  • Automate

    Transition to automated (no-touch) work steps within resolution pathways, with defined groups to manage/update the machine for continuous improvement.

 

What if every business office collector performed at the level of your best collector, every day?

Supercharge your team with the power of machine learning.

Crowe Exceptions Resolution "learns" the most consistent, successful tasks and actions and continuously improves its performance in resolving account exceptions. You can increase cash recovery and significantly reduce the number of exceptions requiring human intervention.

Using machine learning models to create preferred patterns of account resolution, accounts are automated and the technology continuously learns. Over time, fewer tasks for account resolution require human intervention. This tool enables your revenue cycle department to categorize and process accounts more effectively and is designed to help you be able to quickly reduce accounts receivable improve staff efficiency, and increase revenue.  

But it's more than staff augmentation - choosing Crowe Exceptions Resolution is choosing both productivity and accuracy. Our machine learning models identify the most efficient pathway that leads to the highest collection rate, resolving 60-70% of accounts using zero resources.

Before Exceptions Resolution

Your healthcare organization has likely faced revenue cycle exceptions arising from bad debt, credit balances, denials, small balances, and underpayments.

 
 
 
 
 
 
 
Manual
Review
15 minutes spent per account-touching every
account; volume drives staff numbers
 
Data
Analytics
Logic-based themes using
fewer resources, 30-40% resolution
 
Machine
Learning
Incorporating data science using
minimal resources, 60-70% resolution
2002
2006
2014
 
   
A u t o m a t e C r a f t S t a n d a r d i z e S y s t e m a t i z e  
 
 
 
 

What if every business office collector performed
at the level of your best collector, every day?

Supercharge your team with the power of machine learning.

Crowe Exceptions Resolution "learns" the most consistent, successful tasks and actions and continuously improves its performance in resolving account exceptions. You can increase cash recovery and significantly reduce the number of exceptions requiring human intervention.

Using machine learning models to create preferred patterns of account resolution, accounts are automated and the technology continuously learns. Over time, fewer tasks for account resolution require human intervention. This tool enables your revenue cycle department to categorize and process accounts more effectively and is designed to help you be able to quickly reduce accounts receivable, improve staff efficiency, and increase revenue.  

But it's more than staff augmentation - choosing Crowe Exceptions Resolution is choosing both productivity and accuracy. Our machine learning models identify the most efficient pathway that leads to the highest collection rate, resolving 60-70 percent of accounts using minimal resources.

 

Improve Account Resolution to Increase Revenue and Efficiency

 
Accuracy On-Target Results
Accuracy
On-Target Results
Control Performance Governance
Control
Performance Governance
Validity Strong Predictability
Validity
Strong Predictability
Reliability Consistent Measurements
Reliability
Consistent Measurements
Standards Comprehensive Output Models
Standards
Comprehensive Output Models

Calculate Your Exceptions Resolutions ROI

 

With Crowe Exceptions Resolution, you can improve accuracy, reduce costs, and optimize staff productivity. Validate your return on investment with the performance of Exceptions Resolution using our detailed ROI Calculator

Calculate Your ROI
Contact Us
ruiz-ken-150
Ken Ruiz
Principal
sanderson-brian-150
Brian B. Sanderson
Managing Principal, Healthcare Services

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