2024 AAOE Virtual AI Summit – Revving up revenue cycle with AI-driven automation for a lean workforce
AI can help reduce waste & improve efficiency in the revenue cycle by analyzing human touches & making recommendations for waste reduction.
By looking at the actions taken, resolution rates, and variation among individuals, AI can identify areas where mistakes are occurring and help determine how to address them. AI can also automate processes and create smarter work queues based on outcomes. However, the lack of human-generated data is a risk for organizations investing in AI, as it is necessary to understand what is happening in the revenue cycle. Technology, including AI, is essential in improving revenue cycle management, but it is important to consider the data points driving AI and the need for human-generated data.
I’ve spent 25 years focused on revenue cycle IT consulting and software development, so I’ve seen a lot change when it comes to margin pressure. I love all of the clinical innovations in healthcare. However, what it comes down to is: are you actually getting paid what you’re supposed to be paid on time? Also, how many people and how many touches does this actually take on the administrative side to get paid? Billions of dollars a year are wasted on touches that generate no outcome whatsoever by the revenue cycle staff.
Click image for larger view
Your margin is being impacted. What you charge doesn’t matter. What you get reimbursed is a reflection of the quality of the service and the administrative staff doing their job correctly. So, what does it cost? We know what the supplies, the clinical labor, the OR, and the facility costs are that are impacting margins. What about the administrative costs? What do we control? We control the ability to look at human touches. This is where AI comes in. Start looking at where humans get involved in the revenue cycle and make recommendation sets on where you can reduce waste.
Click image for larger view
Here are some of the things that you should look at in a revenue cycle from the time an appointment is scheduled to the time a claim is a zero balance. Where do people make mistakes? Note that even AI, RPAs, and bots make mistakes when not configured correctly. The next question is how quickly can we determine where those mistakes are recurring and what do we do about it?
Click image for larger view
Healthcare providers can’t answer the questions above. They don’t know what the true cost per touch on the administrative side is. They don’t know how many bad touches are occurring and how it’s impacting profit margin. They are collecting less than 98.5% (NCR), and it’s costing more to collect less. A lot of the money is coming from the consumer now who may or may not be able to pay their medical bills in a timely manner. 20 years ago, 5% of provider income came from the consumer. High deductible plans have made a huge impact. Therefore, many providers just stop seeing patients with certain types of undesirable insurance plans. It’s not good for the community and society at large.
Click image for larger view
Human generated data is not available in practice management systems. They were never designed to capture structured data that records actions that employees are performing across the revenue cycle – factors like how you get your work, what the status is, what the action taken is based on the status. Take a look at the resolution rates above. These are real numbers from one of our orthopedic clients. Take a look at the actions taken in the bottom left of the slide above – 30% of touches from the AR representatives were on paid claims that needed an adjustment at a 95% resolution rate. What can be done differently to reduce that 30% and eliminate the need to make manual adjustments to paid claims? Allow more time for processing, right? AI can move things to the right person at the right time to not only reduce touches and waste, but also automate processes.
Click image for larger view
It’s not about how many claims the AR representative worked, it’s about what actually happened to the claim when they touched it. When we look at context and variation among individuals, this is when you can start to see change. Why is it taking one rep 1.6 touches to resolve a claim and somebody else 1.3 touches? Why is one rep’s resolved balance 70% and another is at 33%. This is where you make decisions about incentivizing your top performers and retaining them. PM systems can’t get you this data. Ask a small physician practice what they would do if they freed up 25% of touches by reducing the waste resulting another $5,000 a month in capacity? These are real numbers at the bottom right. But in order to determine where the waste is occurring, one has to understand where the touches are occurring and AI won’t solve that piece.
Click image for larger view
When thinking of the future of generative AI, there is system generated data – what every AI company out there is going to tap into. It’s basic data from your PM, clearinghouse, scheduling, and claims. What it’s missing is the human-generated data. When you combine it together and run it through a generative AI model, that’s when you start to find more unique ways around machine learning including robotic process automations (RPA) and prescriptive analytics for process improvement. It helps you build smarter work queues based on outcomes. I have a higher probability of success when this employee does it this way. Therefore, create and assign this work queue to them for maximum success. The biggest gap in every medical group is that we don’t have enough human generated data to profile what’s actually happening in the revenue cycle.
Click image for larger view
Atlas Healthcare Partners, one of MedEvolve’s clients, is a storyboard of success, because they have adopted the principles of accountability from the time that surgery is scheduled till the time the claim is zero balance. So, they have deployed MedEvolve’s workflow automation system on top of their PM/EMR that allows them to measure every single touch by every single person. As a result, they are able to see not only increases in productivity, but the effectiveness of work. 25% of their employees chose not to be on the team, because they didn’t want to be held accountable. Since then, she’s further increased the capacity of her teams even in areas that we weren’t even focused on. The numbers above reflect that.
Click image for larger view
Atlas has been able to tremendously improve labor capacity: billing department at 52% improvement to capacity. They’re buying and building lots of ASCs, and they don’t have to hire people. The coding team experienced a 36% improvement to capacity. They are actually installing our AI coding solution now, because she wants to further improve capacity, reduce denials, stop paying so much for coders, and let the machine do the work. Patient access saw a 22% increase in capacity. They are also installing our prior authorization automation solution right now. Unfortunately, AI is going to remove jobs, but there will always be a need for humans in the revenue cycle. As long as you have misalignment between the insurance company, the consumer, and the provider services, we’re always going to have people involved in revenue cycle. What we’re trying to do with our software is increase capacity in the teams by bringing awareness to where the waste is occurring. Then, you can diagnose the why. Is it a technology, process, or people issue?
Click image for larger view
Their front end financial clearance process has been amazing. They’ve put our workflow automation system in place. Every scheduled case goes through 12 different checks prior to service. Patients are cleared 9 days before surgery, which is amazing. And even with same day patients, they’re able to clear them within 24 hours. Pre-service collections are 97.5%, and bad debt is very minimal for that organization. When the patient knows we’ve done all the checks, they’re more likely to show up for their case, and that keeps the cancellation rate low. With our auto-coding solution, they’re going to have less demand on people and they’ll even have further quality on coding, billing lags, getting claims out the door, and getting paid quicker. Our Effective Intelligence solution measures something called a zero touch rate, when no human actually had to get involved in the revenue cycle after the service was rendered. Atlas is operating into the 70th percentile. A lot of the orthopedic groups I work with start somewhere around 45%. Our best client is at about 81%. It’s a metric that we have, because we do measure every touch. We know where people are getting involved and it shows on the back end. When you get the front end right, the back end metrics will reflect those processes.
Click image for larger view
AI is here to stay. I challenge the industry to think about the data points that are going to be driving the AI and the data science. I believe that the lack of human generated data is the biggest risk point for organizations making heavy investments in AI, because you’re going to be told things that you already know. How do we reduce touches? Diagnose the why, and that’s the position MedEvolve has taken.
Matt Seefeld, Executive Vice President & Chief Commercial Officer at MedEvolve, brings over 24 years of management consulting experience in the healthcare industry. He has extensive expertise in the assessment, design and implementation of process improvement programs and technology development across the entire revenue cycle. Matt began his career with Stockamp & Associates, Inc. and worked for both PricewaterhouseCoopers LLP and Deloitte Consulting LLP in their healthcare and life sciences practice lines. In 2007, he developed a business intelligence solution and founded Interpoint Partners, LLC, where he served as Chairman and Chief Executive Officer. In 2011, he sold his business to Streamline Health Solutions where he then served as Chief Strategist of Revenue Cycle followed by Senior Vice President of Solutions Strategy until 2014. Matt ran global sales for NantHealth and provided consulting services for healthcare technology and service businesses nationwide, prior to joining MedEvolve full-time.
Review and assess your practice’s financial status in 5 min or less and know exact where you are losing money and why. Measure the work effort of every revenue cycle employee, incentivize and retain your top performers, and help employees that need improvement.
You can prevent most common denials, rejections and write-offs during the scheduling and pre-registration process in advance of the appointment. Configure checkpoints and use central task management to quickly clear patients and keep your front office staffing needs at a minimum.
Aligning the power of the MedEvolve Coding solutions with your internal resources personalizes and trains the autonomous coding model, increasing the speed that auto-codes are generated. The portal workflow also drives operational efficiency, resulting in repeatable and scalable performance.
As team members log in to the web-based application and record each “touch” of a claim, outcome, and next task, key data points are recorded like who completed the task and when, outcome, task notes, internal / external messages sent, collection success and other data points that feed into our real-time analytics.
Reduce RCM labor dependence with financial clearance, coding, insurance A/R, & patient A/R automation modules with real-time analytics.
Increase productivity and simplify front & back office processes while keeping your staff focused with our flagship PM system.
AI can help reduce waste & improve efficiency in the revenue cycle by analyzing human touches & making recommendations for waste reduction.
MedEvolve Rated Top Revenue Cycle Management Workflow Optimization and Automation Solution, 2024 Black Book RCM Client Survey
Healthcare organizations should focus on zero-touch rate—the percentage of insurance claims that require no human intervention for payment.
Monday – Friday
7:00 am – 7:00pm
1115 West 3rd Street
Little Rock, AR 72201
Privacy Policy | 2024 All Rights Reserved