The Promises of AI & Advanced Analytics

Healthcare IT News reports communicates an AI and analytics path for healthcare organizations, but as you read, there is a bit of a paradox at work…

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Expect next-generation revenue cycle management systems to boast quite advanced analytics, said Kellye Sherbet, president of RCM services at Aprima Medical Software, which markets EHR, practice management and revenue cycle management systems for medical group practices.

“Healthcare organizations require sophisticated analytics to perform a deep dive into their information and look at the margins for ancillary services provided,” Sherbet said. “For example, what is being collected in total from patients and payers for performing labs or injectables versus the cost to offer them.”

And now the paradox – – Futurists want to see AI perform the analytics function. Business Intelligence for analytics has been around for years, and is a great visualization tool, but still requires the user to “locate” actionable data. The grander vision is using AI to present the solutions without all of the “digging”  — and AI should be able to do a lot more than that.

“Leveraging AI, healthcare technology will be positioned to further the work to reduce the cost to collect in registration, scheduling, charge capture, health information management, and billing and collections,” said Jeff Hurst of Cerner.”

This vision is great! The deployment and actualization of this vision are very challenging…

OrboGraph has taken a more practical approach to AI, emphasizing an “operational approach” or hear more from our podcast. Applying AI with Deep Learning technologies to documents like Explanation of Benefits forms, Correspondence Letters and other structured/unstructured documents, OrboAccess allows healthcare organizations, revenue cycle companies and others in the RCM chain to anticipate to drive down costs, reduce customer errors and problems, and support a path to modernization in healthcare payments.

 

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