Client Overview
A large publicly traded insurance payor was serving those enrolled in publicly funded healthcare programs such as Medicaid and Medicare coverage.
“We were excited to partner with OZ when we learned of their extensive expertise in healthcare industry software development as well as in streamlining business processes.” – J. Anderson, Director of Claims Department.
Client Challenges
As a multi-billion-dollar insurance company offering its 1.7 million members a network of 68,000+ providers in 11 states, a modern Intelligent Automation architecture comprised of Enterprise Application Integration, RPA, and Data Analytics were needed to help ease the stress caused by the costly errors of their claims rejection process. The company received between 70,000-80,000 paper insurance claims per day. Of which, 1,000-3,000 were immediately rejected and dismissed by the system due to Optical Character Recognition (OCR), data processing, or completion errors. Providers were left unknowing to 528,000 rejected claims (per year) resulting in a huge cost deficit of no payment collections from the payor.
This large insurance payor “business rules engine” was used to validate basic claim information. The system was generating a high percentage of non-matches, which resulted in repetitive, clerical manual work for their claims team to match an average of 15,000 physicians per day. Additionally, the engine did not consider the varying state requirements for NPIs, NDCs, and other required data, resulting in several costly errors.
OZ’s Solution
OZ’s solution team conducted an in-depth analysis of the current system and developed an Intelligent Queuing system by leveraging the latest Microsoft and other technologies to implement a state of the Intelligent Automation architecture using an RPA framework of communication and Data Analytics for reporting between claims processing systems and other ancillary systems. OZ created an on-demand Rejected Claims Report with links to review individual claims. Upon review, claims processors were able to quickly make corrections to claims errors and reprocess those claims for payment immediately.
To increase the accuracy of data selections, upgrades were made to the Intelligent Automation business rule engine and new rules were added to optimize physician, NPI, and NDC validations, as well as variations in state requirements.
Solution Results
After the new Intelligent Queuing / Automation solution was implemented, turn-around time for work processes decreased by 50% with 100% error-free outcomes. 80% of manual processes were automated. The new solution has become a useful tool to complete daily routine tasks and quickly process and adjudicate claims.
- With rejected claims enhancements in place, this large insurance payor can now reprocess an average of 800 claims, effectively reducing unnecessary provider follow-up and frustration by more than 200,000 claims each
- Eliminated hundreds of thousands of follow-up calls from providers with automated rejection letters sent within 10 days of submissions.
- Faster claims processing with a high-quality RPA selection process raised the provider matchup rate to 90%; 10% more than the old process’ rate.
- Achieved higher match rates by optimizing the Intelligent Automation business rules engine for the selection of required data such as NPIs and NDCs by state with 100% accuracy.
Why Intelligent Automation?
OZ leverages Intelligent Automation to accelerate processes for Insurers to turn their data into information, optimize processes, and make their businesses more competitive. With 99% accuracy and years worth of work saved, Intelligent Automation can optimize the way organizations derive business insights to achieve outstanding ROIs.