How 40 AI Agents Make Prior Auth 90% Faster

So um you know the the industry has a very common process called utilization management or prior authorization today right. So what happens today is to the extent that you know the available information is there when when a when a member goes to a provider or a doctor and it can be approved it can get approved but many times what happens is that the there's a lot of back and forth between the insurer or the risk bearing entity and the health system or provider or the doctor's office and for getting an approval before the service could be performed. Right? So what happens is they send either fax or sometimes electronic but many times fax is still that's reviewed by a clinician or an medical director and uh they they have to match eligibility requirements. They have to understand if the benefit is covered. Then they have

to look at medical necessity to apply guidelines the evidence-based guidelines to see if this is actually necessary care because a lot of times the care that's being administered is unnecessary and it creates more complication more spend and so so they have to go through the decisioning on that and then when you go through that there may be information from the medical record that's missing right that is required to then they reach out to the provers's office and many times there's not like sometimes maybe there's connectivity with EHR that you and message them electronically otherwise somebody has to call the doctor's office and the doctor's office goes they not they're in the middle of looking at somebody else so they're not able to answer them so they have to return the call then you get the missing information you have to go through the process to

redo the workflow so it takes time it adds administrative burden and meanwhile the patient or the member is waiting for all this look at now what AI can do right it's not just these kind of like very straightrough scenarios all these complex scenario scenarios with peer reviews and data going back and forth and reviews that need to happen at when you look at this end to end process. What we are able to show is that bringing in 40 agents, not one or two, 40 agents working on behalf of one clinician, they can streamline all of this, right? And when they do this when the when the AI is working in tandem with the human with a lot of responsible AI layers built in the human is still getting so they're reading the document surfacing the first summary they're saying whether it's eligible or not they're

saying whether it's benefits covered or not they're already applying the clinical criteria guideline to suggest what might be the they're saying here's the missing information they're actually fetching the missing information from the EHR and doing the redetermination on the fly they're notifying the pro it's end to end right so all these edge scenarios when 40 agents can work on behalf of a clinician, it gives an enormous lift to the clinicians. Right? So, it's the question is not about um how do you really um replace the clinicians, the question is about how do you give relief to the clinicians, right? and with all this administrative work that's happening so they can actually apply it to either counseling or looking at care guidelines and accepting and and practice at the highest of their license. Right? So that is that is dimmetry that workflow I just described is

80 to 90% more efficient and the turnaround times improve by like multiffold and the patient gets what they need right away. >> That's the I think that's really important to call out. Um, that percentage won. Crazy. Very good.