Healthcare payer
meets RPA

The automatic claim repair solution for happier healthcare customers

Improved results for
claims processing operations

Like all insurers, health plans must find ways to cut costs, increase quality and improve customer satisfaction, while complying with regulations and supporting new policy products. It should come as no surprise that health insurers scrutinize claims processing operations for money saving opportunities. In fact, 70% of claims process successfullyor ‘auto-adjudicate’on the first attempt, costing the insurer about $3 per claim. Failed claims, requiring manual processing to correct code exceptions or data errors cost the insurer about $28 per claimalmost ten times as much. There’s no question that auto-adjudication has transformed processing and made inexpensive claims possible
for healthcare plans. However, many claims fall outside the scope of business rules limited by the older technology common to many claims processing systems. UiPath encourages healthcare customers to view its RPA solution technology as “claim repair” robots, noninvasively integrating with back-end systems and databases. What's more, bringing intelligent automation to “error and edit” claims that would otherwise fall into slow and expensive manual remediation. Our solutions reduce claim processing turn-around-time and sharply lower operational costs. They help customers quickly incorporate process changes to support new products and stay ahead of the competition.
A real-life scenario

Healthcare payer challenges and solutions

Error release automation

This healthcare insurer found that one to two thousand claims were being stopped each daily for a simple error code associated with missing or incorrect data. These claims had to be worked manually to correct or supplied the claim data from other systems. Although these claims were only around three to four percent of the total, they had a big impact on the claim group because it caused constant bottlenecks.

 

The RPA solution was robots with automation scripts based on the same business rules used by the claims group to manually corrected the errors. Both the manual and the automation solutions were imperfect - the claim was still pending and still being touched for resolution. However, robots removed 25 FTEs from this manual process, which the customer considered significant saving, and bottlenecks of two and three-day durations were reduced to same-day resolution.

 

Minor edits automation

Another payer had a claims platform that held claims for minor front-end edits, such as noncompliant national provider IDs, age, address, etc. This meant anywhere from five hundred to fifteen hundred claims daily required manual processing by the claims team: processing which involved going out to several screens in the claims system to find the information needed to make the edit changes.

 

Now, the claims are pulled into work queues based on their hold codes and robots programmed to automate specific edit changes are assigned to the queues. The robots navigate to the claims system screens; collect the data needed to edit the claim; make the edit changes and resubmit the edited claim back into the claims systems.

 

Manually processing the edit changes took ten to fifteen minutes, whereas robots can do the tasks in one to two minutes or less. The RPA solution completely removed the claims team from this edit work, replacing approximately ten to twelve FTEs with robots. It also provided the ability to handle sudden increases in claims volume with more robots, instead of reassigning claims agents to low-value work.

 

Complex claim adjudication

A healthcare insurer was looking for a more efficient way to process coordination of benefit claims. The adjudication rules for those claims are complicated. Typically, the insured are covered by their health plans and their spouses plans. This means the insured’s COB provisions must be understood and their benefits coordinated between plans—in such a way that everything is covered and payment does not exceed the total claim. Not a job for a robot.

 

However, the claims agent must look up information in many documents to properly process this claim: at a minimum, the attached explanation of benefits (EOB); the summary of benefits (SOB); and the benefits grid. Plus, any other attachments to the claim file.

 

The RPA solution put these claims in a work queue for robots to assemble all the necessary documents, then placed everything in the claims agent’s folder. Taking this assembly work away from the agents and allowing them to focus exclusively on adjudication decisions, shifted about two hours a day from low-level documentation tasks to high-value claims processing workfor each agent.