DENVER, June 14, 2018 /PRNewswire/ -- Revenue cycle departments in hospitals of all sizes and types continue their mass migration to automation, Recondo Technology reported today. The company noted that climbing rates of claims and prior authorization complexity and requests, paired with patients struggling to understand and pay for medical services, are accelerating the industry shift from manual to automated revenue cycle. In response, the company is further investing in its already powerful automated solutions with advanced machine learning and other AI capabilities.
"We've already seen expansion within our customer portfolio as word is getting out among health systems that revenue returns from automating revenue cycle management are in the tens of millions," said Jay Deady, Recondo CEO.
New customers include a large integrated care delivery networks, several major universities and an affiliated large physician group. Existing customers are expanding bookings for additional automation products, specifically for AuthInitiate™, an automated prior-authorization offering, and SurePayHealth™, Recondo's patient estimation solution.
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In total, Recondo has secured close to $5 million in new SaaS booking contract value in 2018 to date, with direct bookings up by 70% year-over-year and channel bookings up 50% year-over-year.
Advancing hospital revenue cycle management
With Recondo's AI-driven, automated solutions, hospitals end the need to assign armies of staff to communicate with payers about patient cost estimates, authorization requests and claim status. The company's patented ReconBotsTM perform the vast majority of this work instead, including routing the insurer's answers to assigned systems and routing accounts needing remediation to specialized staff. In short, automation moves toward near "touchless" revenue cycle management transactions.
"Recondo was the pioneer of robotic process automation in revenue cycle management. Now we are making it even smarter. Our machine learning-enhanced engines now get the most accurate information with even fewer requests, yielding direct savings for our clients," noted Eldon Richard, Recondo's Chief Technology Officer.
He continued, "We have also applied machine learning to improve patient estimates, reducing errors by as much as 33 percent while learning the impact of downstream practice and billing patterns to improve predictions."
