AI opportunities are opening up for healthcare operations

Presented by Change Healthcare

AI is an important tool for healthcare providers today, from revenue cycle management to operational efficiency etc. Don’t miss this VB On-Demand event to see how AI is doing changing the way clinics deliver patient care.

Watch for free on demand here!

AI is changing the way clinics deliver healthcare, at every point of the healthcare revenue cycle, with the precious amount of data healthcare clinics generate, plus maturity and capabilities of AI products on the market today. Not only does it bring about an increase in efficiency in the back office, but it also helps healthcare providers better serve patients.

“Everybody expects good healthcare, but when it comes to management,” said Tina Eller, Vice President of Transformation Supported Revenue Cycle Management (RCM) technology, Change Healthcare. revenue cycle and billing process, that’s the specialty of patient surveys. “Automation and technology have been able to help us do our jobs better, understand and connect points in the cycle. The patient experience is something we can focus more on, while keeping profits and cashing in. That is the main function of RCM.”

From the point of registration and scheduling, to the back-end claims resolution and arbitration point, brings AI into existing workflows and algorithms, helping healthcare providers expand their capabilities Their capabilities go far beyond what is possible with repeatable static bots or processes. The other major benefit is how AI can help reveal deeper trends in user behavior and in the workforce. Critically analyze the data clinics generate that can drive improvement and optimization, uncover areas of opportunity for standardization, and even show where one-off projects can solve problems. business topic.

“The impact of AI is being felt throughout the entire revenue cycle,” said Kaushik Roy, Vice President of AI Product Management at Change Healthcare. For instance, he explains, pre-authorization “is a market opportunity worth hundreds of billions of dollars in terms of how much it could save.”

Increase revenue without increasing care costs

Much of the benefit of AI, when applied to RCM, is that it eliminates the cost of manual labor in repetitive tasks and processes — especially those that can be transformed. to run in parallel, shortening the revenue cycle. And as it continues to ingest and learn, it shortens the time it takes to learn the next task, as it can often run in the background without interrupting the work in progress. Any new project or process can produce results faster than ever, because testing can be done in cycles — and the fact that testing becomes the stakes on the table is one of the big ways. to make healthcare delivery more efficient and effective as profits increase.

“We can really make tough choices and changes, as opposed to throwing darts at the wall,” explains Eller. “Because AI workflows are based on historical data and so many cycles of learning, it can also ensure that you have that best practice model in place. It continuously learns and refines as you go — as you grow and as your patient population or revenue cycle demands.”

For example, a clinic can rotate much more easily to handle something like this year Act of no surpriseand incorporate compliance into the workflow quickly.

Best practices for AI implementationchemistry

AI is simplifying workflow, but it’s a complex technology to adopt, especially for healthcare organizations. The most essential part of the equation, says Roy, is strong partnerships, because of the synergy of data scientists and engineers with employees with the necessary business and field knowledge. is very important.

“One thing we have learned in our three years working with Kaushik and his team is that domain expertise combined with technical and AI expertise is critical,” said Eller. explain. “We are building models based on nuances that can really throw the model away. Having all the domains as a partner, testing, traversing the scenarios, identifying the differences and making sure the results were in the right percentages we needed, delivered give us the confidence we need.”

This relates to the question of building or buying eternity, which can be difficult when an organization has in-house expertise. But knowing where your team excels and where support can make a difference is the turning point. If you don’t already have a mature AI store, outside expertise can be tapped into while you build your talent roster internally. But starting a new network can be expensive, and unless you want to invest years without returns, it can be a challenge.

“Building AI requires a lot of infrastructure, especially data infrastructure and regulatory frameworks,” Roy pointed out. “You need permission to use data access etc. That may not be possible for many mid-sized and certainly smaller clinics. That’s where you have to leverage other vendors or expertise.”

A staggered implementation plan, patience as the algorithm learns, and setting end-user expectations for how AI models will perform are also important. It requires time and commitment from all parties in the AI ​​implementation project to shape the models where they can be successfully implemented. It’s also important to choose your use cases wisely, narrow the focus down to a very specific problem, and apply that patience and commitment, says Roy.

“Pick a small problem, whatever it is, but an important one with clearly defined value, and then establish and grow that success,” he said.

For an insight into how AI is changing each step of the revenue cycle, consider implementation challenges and opportunities — including regulatory and industry concerns, plus a glimpse About the emerging AI technologies that will continue to transform the healthcare industry, don’t miss this VB On-Demand event!

Watch on demand now!


  • How AI can support financial performance and operational efficiency
  • Case studies demonstrate how AI technology improves clinical workflow
  • Ways AI can increase net patient revenue (NPR) for providers
  • Exploring NLP-based medical entity extraction


  • Tina EllerVice President of RCM Tech-Enabled Transformation, Change Healthcare
  • Kaushik RoyVice President of AI Product Management, Change Healthcare
  • Cole’s ArtModerator, VentureBeat


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