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How Grady Health Will Take Rev Cycle AI to the Next Level

Analysis  |  By Jasmyne Ray  
   September 23, 2024

In the latest installment of our interview series for HealthLeaders AI and Finance Mastermind program, we spoke with Jacqueline Samuel, director of revenue cycle quality, strategy, and analytics for the system's billing subsidiary.

Many hospitals and health systems are looking to invest in artificial intelligence to optimize their revenue cycle operations. And while many are partnering with vendors, some are developing their solutions in-house.

Over the last few years, One Grady, the billing subsidiary of Grady Health, and its in-house developers have focused on robotic process automation (RPA) solutions. Now, the system is considering the possibility of expanding into AI.

AI and automation are often used interchangeably despite having different capabilities. Automation focuses on using technology to perform specific, often repetitive tasks, taking the pressure off of staff to do those same tasks. The introduction of AI takes that process further, using technology to generate results or take those tasks to the next level. Eventually, that technology will be used to recommend the next course of action or even predict outcomes.

As health systems and hospitals expand their use of AI, they'll be using the technology to not only improve processes but improve outcomes. In adding AI to their RCM solution lineup, One Grady aims to look beyond the technology's current capabilities and tap into its potential capabilities, says Jacqueline Samuel, director of revenue cycle integrity, stategy, and analytics and a participant in the HealthLeaders Mastermind program on using AI in finance and revenue cycle operations.

“What else can these solutions do as far as thinking for us and giving us the next steps, vs. the kind of programming that has to go into RPA processes?” she stated.

She’s particularly looking forward to using AI to improve denials management and data analytics.

“Our next steps would be exploring how to leverage machine learning to do predictive analysis so we’re taking that manual analysis off of our teams,” she said. “The less time we spend doing that work manually, the more we can focus on complex analyses, automation, and implementing AI solutions.”

One Grady’s staff meet quarterly to discuss prioritization as well as submit suggestions for solutions in development, detailing the process they’re hoping to implement and what the return on investment is. The forms are then reviewed during governance meetings and potentially added to the development pipeline.

Having leadership think through ROI helps ensure that it’s worth the effort for developers to build and implement, and that there isn’t an alternative solution. The success, or efforts, of the solutions are measured by revenue impact.

“Where was that revenue or where were those denials at before we implemented this solution, and where is our revenue impact now?” Samuel explained. “We created a dashboard that shows us on a month-to-month basis what the revenue impact is for each one of our automations.”

Their biggest challenge, Samuel says, is the size of their development team. One Grady’s has seven in-house developers, which could be considered small in comparison to larger, non-safety net organizations.

The developers also support the over health system, which consists of a hospital with significant patient volume, and several neighborhood clinics.

“We only have so many resources and time available. We have an excellent team with and excellent skill set, [but] we need them to be able to focus on certain things,” Samuel explained.

Another challenge is the learning curve that comes with the implementation of a new solution, particularly the number of staff that have to be trained and the time it takes to do so. However, Samuel says that as the solutions get smarter, so do the staff.

With the solutions being developed in house, accountability falls on the One Grady team should anything go wrong; an issue they have, thankfully, not had.

“We identify the issue, make sure we’re communicating with stakeholders and then do what we need to do to fix it,” Samuel said. “Sometimes that can take time, but we just make sure that we’re communicating our status updates with them and letting them know the breadth of the issue.”

The HealthLeaders Mastermind series is an exclusive series of calls and events with healthcare executives. This Virtual Nursing Mastermind series features ideas, solutions, and insights on excelling your virtual nursing program. Please join the community at our LinkedIn page.

To inquire about participating in an upcoming Mastermind series or attending a HealthLeaders Exchange event, email us at exchange@healthleadersmedia.com

Jasmyne Ray is the revenue cycle editor at HealthLeaders. 


KEY TAKEAWAYS

The system has mostly relied on robotic process automation, but are looking into developing an AI solution.

One Grady staff can submit suggestion for solutions in development during quarterly meetings.

Some challenges they face include the size of their in-house development team and the learning curves that accompany the implementation of a new solution.


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