Maryanne Thompson is the controller for MidLantic Urology, a specialty practice with 46 locations and 70-plus physicians in the U.S.
Ms. Thompson told Becker's ASC Review about MidLantic Urology's biggest revenue cycle management problem and how AI helped solve it.
Note: Responses were lightly edited for style and clarity.
Q: What's the biggest RCM hurdle your practice has faced and how did you overcome it?
Maryanne Thompson: We became a large urology group practice by bringing smaller urology groups together. That resulted in a major hurdle for us — decentralization of the RCM process. The doctors at the individual practices liked having ownership of that process. They wanted to have staff in their own offices because they felt that having RCM staff in close proximity meant that they were staying on top of it. We struggled for many years to find a way to show them that bringing RCM staff together actually improves the revenue cycle because employees can better collaborate and solve problems under one roof. We overcame that by working with a third-party RCM solutions provider to gauge performance through analytics and AI-driven metrics and reports. We tested it with one practice and were very successful, so once the doctors from other practices saw the results in the monthly reports, they wanted the same for their practices. It helped get buy-in as we worked to become more efficient.
Q: What was the most impactful lesson you learned when introducing a new RCM management solution at your practice?
MT: We initially overestimated the number of full-time employees we needed to staff our newly centralized business office. Prior to implementing MedEvolve RCM Workflow Automation, we looked at all of the accounts receivable and estimated that we would need to hire eight additional full-time employees. But, after we implemented workflow automation and reviewed our RCM reports, we learned that we would be able to get by with half that number. By streamlining our RCM processes and focusing only on the 10 to 20 percent of claims that need to be worked each day, we were able to work much more efficiently. So, instead of hiring eight employees and building out a whole new department focused on A/R, we streamlined our staffing, and now use half as many staff to deal with our day-to-day A/R needs.
Q: What advice do you have for other practices looking to adopt a new RCM management solution?
MT: RCM in a group practice office is still somewhat traditional — a lot of practices have some reluctance to adopt technology. But had our practice not deferred to the actual data upfront, we would have overstaffed our RCM team. You need to be receptive to using data in day-to-day decision-making.
Practices should also be forthcoming with their concerns when working with an RCM vendor partner. Be clear from the beginning, and the vendor will often work with you to address those concerns. It's also important to identify a vendor that wants to be part of your team and part of your success. It's not just a purchase; it's a relationship. Your vendor should want to review and improve its technology based on your feedback.
As a result of our data and the relationship with our RCM vendor, MedEvolve, we have been able to improve functionality and process from the front desk to the back and everything in between. Having actionable data drives our training — it helps us examine why denials are happening and what processes need to be looked at. Data at all levels is really unearthing challenges that we would never have been able to find on our own because of the volume of information. If you don't have a way to mine information and use it effectively, it's useless.
Q: What are some misconceptions about AI in healthcare that should be cleared up?
MT: The biggest misconception is that AI is here to replace staff. AI is an adjunctive technology, not a replacement technology. Large physician practices generate huge volumes of data on a daily basis, and no one person can handle analyzing all of that. AI technology works with your staff to make them more efficient.
Q: Are there any areas in healthcare outside of RCM that you think could benefit from AI-powered solutions?
MT: As new clinical pathways are designed for good patient care and the extension of life, you can use analytics to mine medical records and identify current patients who may benefit from new treatments. It's an example of the collaborative nature of AI technology. For example, we use technology to look for patients who meet set criteria among the tens of thousands of records in our EHR; it generates a short list of patients who are potential candidates for new life-extending drug therapies. It's an approach that's increasingly used in urology to provide better patient care.
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