The Case For AI in the Healthcare Revenue Cycle

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It seems like ages ago when in 1997, IBM’s artificial intelligence (AI) beat world champion chess player, Gary Kasparov. This led to lots of articles that it was only a matter of time until AI replaced humans in all aspects of our every day lives. But that was a myth. Chess has a finite number of pawns, squares and moves. Once the AI model has matured, it can envision and anticipate any scenario on the chess board. And so it began, that every industry looked for applications that could employ AI to automate and gain efficiency.

Some applications have been more successful than others…fraud detection and prevention with credit cards has been a game changer. Most of us have had a transaction declined at some point because it was outside of our normal purchasing patterns. Google’s self-driving car still gets into accidents occasionally because AI doesn’t know how to handle what it hasn’t encountered before. In many cases, the models still need more data and time to mature.

Healthcare has been no exception in looking for ways to employ artificial intelligence. Nature magazine recently reported on 65 trials evaluated in October 2021 studying the clinical benefit of AI. The physicians conducting the study found that there was no clinical benefit in using AI over commonly used statistical risk calculations in 40 percent of the applications. This was the case even though the models performed well during development and after validation. This reinforces that the practice of medicine is still part science and part art. AI can help physicians work smarter, but will always require judgement to best serve patients. IBM’s CEO refers to this concept of AI as “augmented intelligence” which will complement, not replace human cognition.

However, in the administrative functions of healthcare, just like credit card financial transactions, AI is poised to be the next big thing in improving revenue cycle operations. Not only can AI scan through all of your claims and accounts receivable, it can create recommendations for priority on which accounts to work and how to handle them. Similar to how Netflix will make recommendations on what to watch next based on user history, the recommendation engine can use the data available in an organization’s revenue cycle management system recommend specific actions for users to take.

Going one step further, in addition to using internal data, the application can utilize crowdsourced data so that it is continuously updated and matures based on the collective experience of many revenue cycle professionals. This allows everyone to work smarter. Improving revenue cycle efficiency and net patient revenue is every CFO’s goal and using technology to do so is the key to maintaining financial success.

Interested in learning more? The team at VisiQuate is focusing on how we can help hospitals optimize their revenue cycle management. Visit our Revenue Cycle Playbook for step-by-step plays to help you stay on top of the ever-changing landscape of healthcare revenue cycle, or contact us to schedule a demo.

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