How generative AI and RPA are transforming claims appeals
Building a faster, stronger,
better revenue cycle
Managing clinical claims appeals is a costly and convoluted function of the healthcare revenue cycle, requiring the time and attention of clinicians and support staff who otherwise could be focusing on higher-priority tasks.
Introducing generative artificial intelligence (AI), or GenAI, into the claims appeals process can reduce the administrative burden on clinicians and staff and improve the efficiency and accuracy of appeals.
From automation to AI in the revenue cycle
AI builds upon the foundation set forth by robotic process automation (RPA)
Despite some shortfalls in its capabilities, RPA technology has made great strides in reducing inefficiencies in health systems’ revenue cycles and reducing administrative friction with payors.
RPA
Eliminates human error
AI
Leverages existing RPA, technology, and security infrastructure
RPA + AI
Alleviate the administrative burden on highly credentialed providers
1
Payor denies claim
2
RPA receives denial and prompts AI to understand the cause
3
RPA securely gathers key info from the electronic health record (EHR)
4
RPA prompts
AI to summarize key information from EHR
5
RPA sends summarized information and cause for denial to AI
6
AI drafts appeal letter
7
RPA creates a document for review
8
Appeal is sent to a human approver for final review
9
The appeal document is sent back to the payor
AI and healthcare claims appeals
How does it work?
Combining human intelligence with automation, generative AI draws on RPA capabilities and clinicians’ clinical expertise to draft timely claims appeals with less administrative effort from providers.
What are the benefits?
To address rising healthcare costs and complexities, healthcare organizations need solutions that provide value across the organization and to their patients and their families.
Click to explore the benefits
Patient and provider experience
Patient and provider experience
Revenue and cost-savings
Quality
Lower the cost to collect.
Improve the accuracy and timeliness of claims appeals, reducing friction with payors.
Leverage innovative technologies to improve dated systems and processes.
Key considerations
As healthcare organizations consider AI use cases, an enterprise strategy is essential to ensuring they have the infrastructure, governance, and people to support and seamlessly integrate the technology.
Strategic alignment
Data
Ethics
End user design
Change management
Metrics and reporting
Strategic alignment
Click to explore the key considerations
Clinicians:
Administrative staff:
Strategic alignment
Data management
Ethics
End user design
Change management
Metrics and reporting