Amid the many AI tools available for ASCs, Nikhil Shetty, MD, said he’s found the most return on investment from applications that assist with revenue cycle, predict denials and act as a “force multiplier” for the workforce.
Dr. Shetty, COO of Midwest Interventional Spine Specialists in Munster, Ind., shared the areas where AI is proving the most effective.
Note: This conversation was lightly edited for clarity.
Question: Where are you seeing AI delivering the most measurable ROI in the ASC?
Dr. Nikhil Shetty: The biggest high impact use cases of AI within the surgery center has an ASC component and a clinical component. Using AI to take advantage of revenue cycle optimization does help. AI platforms can automate prior authorizations, check eligibility, validate coding and make sure that we’re not under-billing or over-billing for our clinic visits. It can also charge capture all relevant services that we’re able to provide for our patients. Along those same lines on the administrative portion, AI currently has the greatest impact on the ability to predict denials before submission by analyzing our notes, making sure coding and billing is accurate and capturing all of the relevant information. And then once that bill is submitted AI closes the loop on revenue cycle management to make sure that patients are eligible for what they’re getting. If there’s prior authorization required, those documentations are submitted separately and closing back the loop to make sure that we capture denials or predict them before they happen.
One thing our ASC has yet to take advantage of is predictive scheduling. When AI is able to predict that based on physician tendencies, preferences, case selection and patient information, that OR time and inefficiencies. It will create scheduling blocks that maximize the care we’re able to deliver for the patients and minimize downtime in between.
Q: I want to home in on what you’re seeing with AI in terms of revenue cycle management and prior authorizations. Can you pinpoint any particular examples where AI was helpful from an actionable standpoint?
NS: One example is when it comes to denial prediction. There are many different AI platforms where we can use the template and the models that they have for certain disease states requiring certain kinds of procedures, and those models predict which procedures are going to be denied for which patient based on the indication, documentation and histories. We’re able to see what a patient is most likely going to be a candidate for prior to us submitting for the procedure and waiting for insurance feedback. We’re just starting to tap into this predictive denial prediction strategy where we can circumvent the whole peer-to-peer process and the denial process.
But the insurance companies are well ahead, particularly with the use of AI, and so their models are already in place to kind of circumvent that process and kind of stop us in our tracks. Utilizing AI is the standard now. It’s not like we can get ahead of insurers with AI. You need AI just to keep up.
Q: What’s working well with clinical applications for AI?
NS: One of the practitioners in our office uses the Open Evidence AI platform. It’s very educational, and we can stay up to date on literature, particularly for an interventional pain, and it does have ambient listening as a service. It’s able to take an encounter where the physician or the practitioner is able to speak directly to the patient face-to-face without typing on a computer. As long as you’re dictating out loud, these devices are able to synthesize notes based upon your own dictation including all of the relevant information and patient histories.
Q: What are the biggest barriers you’re seeing for AI adoption? How can ASCs get around those?
NS: I’ll use our practice as an example. When we first started to adopt and encourage the use of AI, particularly for these services, the biggest concern was what would happen to some people’s roles. The natural fear with any type of AI adoption is replacement, but we’ve used this and transformed into a force multiplier.
That was an initial hesitation preventing us from diving into it full force, but now we’ve empowered each of our members to use AI to dynamically improve their current roles. They’re able to use these other tools, saving them time in their own tasks and being significantly more productive and efficient in their own role.
Q: Any final thoughts on AI and ASCs?
NS: An ambulatory surgery center that’s fully integrated with AI is something that’s five to six years down the road. In the future ASCs will combine full operational intelligence and procedural intelligence. On the one side you have AI, optimizing every aspect of the business, which we mentioned, like revenue cycle management, clinical documentation and predicting denials. On the other side, you’ll have AI enhancing what happens in the procedure room itself. We have more developments down the pipeline making enhanced procedurals much more efficient, much more safe and much more minimally invasive.
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