Transforming Prior Authorization with AI

Q. Hi Siva. How are you doing today? Welcome to The Big Unlock podcast. Very happy to have you as our guest today. For our audience, as you might be aware, this was started by Paddy Padmanabhan, and I’m building on his legacy. We’ve done many episodes. Let’s do some quick introductions. I’ll start. I’m Rohit Mahajan, Managing Partner and CEO at BigRio and Damo Consulting, and also the host of The Big Unlock podcast. Over to you.

Siva: Wonderful. Appreciate you having me on the podcast, Rohit.
I’m the CEO and co-founder of a company called Cohere Health. We started in late 2019, and we are solving the burdensome issues related to prior authorization.

I’ve been in the healthcare industry for more than 25 years. Prior to Cohere Health, I founded another company called Coda Health Analytics in 2007, built it over 10 years, and sold it in 2018 to EXL. It was a successful analytics company in the healthcare market, funded by VCs including Sequoia Capital. It was a good exit for everyone. We were serving health plans at the time.

Before Coda Health, I started a small company in the provider space and sold it to Perot Systems. I also started my career at Intel, then went to business school at the University of Michigan, got my MBA, and moved to Connecticut. I live in Connecticut now and came here to work for Gartner Group. From there, I wanted to start something on my own, and that’s how I began my healthcare career.

Q. That’s amazing, Siva. Thank you for that introduction. With such successful exits, I’m sure Cohere will also be on a great footing. Could you share how the idea for Cohere came about? You’re so familiar with the healthcare space—I’m sure you saw a big problem to solve. How did it start, and what’s your journey been like?

Siva: As I indicated, in my previous company, I had been working closely with the health plans—health insurance companies. We were doing analytics, and at that time, we were focused a lot more on payments, population health management, care management, etc.

During that process, I came across the prior authorization process, which the health plans were involved with. I’ll get into more detail about prior auth later. So I got involved in that, and it was always in the back of my mind that the process was highly manual and caused a lot of operational issues for both providers and patients.

It was a major pain point for the health plans. After I sold the company, I had to work there for a bit. And then I started thinking: how can we apply AI and other advanced technologies to solve this problem in the healthcare ecosystem? That was my angle.

While I was working with the health plans earlier, some of my clients had indicated they’d be willing to work on this problem—if I could come up with a better solution. That’s how I kind of got into this.

Q. That’s amazing to know that you were able to discover a gap and then build a new business enterprise to fill that gap. So tell us, Siva, a little bit more about prior auth. Most people in healthcare know what prior auth is, but tell us some of the intricacies and more details about it. You’re the expert on it, right?  

Siva: Sure. Prior authorization is, you know—as a patient, for example—when you go to a specialist, they’ll usually examine you. Say you go there for knee pain. Depending on the severity, they might just take an X-ray first to see what the problem is. If it seems more acute, they might order an MRI.

Now, the moment a physician orders something more expensive—like an MRI, which can cost between $1,500 and $2,000—the insurance company wants to know why that test is being ordered. So the physician’s office has to fax or submit information explaining why I need the MRI.

Then, the health plan looks at their policy and decides whether to approve it. So that’s the process. Anytime there’s a costly or potentially unnecessary procedure being considered, this process acts as a check and balance to ensure it’s appropriate.

On the insurance company side, the submission process itself can be confusing. It might happen through a portal, a fax, or a phone call. Then, the health plan assigns it to a nurse, who reviews the information and determines if it aligns with policy. If it does, they approve it.

If the nurse thinks it doesn’t meet the criteria, it goes to an MD for review. The MD might then say, “You don’t need it,” and deny it—or they might approve it. If it’s denied, it’s usually by a specialist on the insurance side who gives a reason—like saying based on the X-ray, the issue doesn’t look serious, so physical therapy might be enough.

My physician might not agree with that, but that’s the process. So then they might send me for conservative therapy, etc. That’s the prior authorization process.

Q. Okay. And Siva, in the first part of what you were explaining, you used the word abrasion, right? I’m very curious—what is this abrasion that’s happening? And second, how long does this process take? Because now the person needs to apply, right? 

Siva: Yes. Right, exactly.

So the process hasn’t always been very clear in terms of what information needs to be submitted. What happens is there can be a lot of back and forth between the physician’s office and the insurance company. For example, the office sends some information, and the insurer says, “No, no, we’re looking for an indication of something else.” Then it gets sent back. The provider looks at the documentation and says, “No, we actually did provide that—here’s where it is,” and they send it again.

So that back and forth adds time and creates more administrative work on both sides.

All this paperwork, documentation, back-and-forth communication, and waiting can take anywhere from five to 14 days. For very complex procedures, it could even take 13 to 14 days. For example, if someone needs surgery, they might have to wait while going through multiple rounds of paperwork and approvals.

Meanwhile, the patient is the one who suffers. The final decision—whether it’s approved or denied—won’t be known until that whole process is complete, and only then can the surgery be scheduled.

That’s what causes the abrasion: the administrative burden, the delays, the unclear requirements, and the possibility of denial at the end of a long process. And that’s still the case in many areas today.

Q. So because of your prior experience with payers, in this particular case insurance companies, you chose to focus on prior auth with them. And there is the healthcare system in the loop, which is the physicians and the providers. How do you distinguish between the two? Because prior auth is important from both perspectives, right?

Siva: For the health plans, it’s a cost. The main reason why there is prior authorization is because, as we all know, healthcare costs have been going through the roof.
There is quite a bit of waste, and a lot of it is due to unnecessary procedures, unnecessary imaging. For example, there’s no need to do imaging if it’s sufficient to have just an X-ray, which costs like 50 bucks instead of a $1,500 or $2,000 scan.
Because of the excessive use of high-cost items, there’s waste in the system. Health plans, being the intermediaries, manage the dollars for employers or the government, like Medicare.
So one of their tasks is to control for this. The health plan’s viewpoint is to prevent unnecessary things.

Obviously, the physician thinks something is very important for the patient, and that’s where the tension is.
The reason we decided to go with the payer side is that payers have the volume, and a lot of things can be controlled from the health plan side using technology.

There’s no point in just speeding up the process on the physician side. There are benefits to it, but you’d have to do it for every physician office.
If you go to the health plan, you can address all of this in one shot.

Q. Awesome. So Shiva, you mentioned that you started in late 2019. So that’s actually before COVID, right? 

Siva: Yeah. That’s like three months before COVID. 

Q. And then COVID hit. It must have impacted your go-to-market and your plans. But you stuck to the mission. You have very good investors who’ve supported you in your journey.
Tell us a little about the bumps on the road, how you overcame them, and where you are today. How many employees, and how are you going about this?

Siva: One of the things is that we actually managed to partner with a large health plan—okay, Humana—it’s on our website. What happened was that I had hired like four people or so. We were actually working in a WeWork office in Boston in February and were in the process of finding an office and recruiting people, etc.

I remember in early March 2020, while working in the office, they called all of us down and said, “Hey, we found somebody with COVID today in the offices. So you guys have to go home. We will call you, and we’ll see when you can come back.”

That was the last time we all saw each other—the four of us. And we came home, and after that, we didn’t see each other for more than a year.

But then we changed our entire plan—worked remotely—and built the product out. They had a deadline of January 1, a client. So January 1st, 2021. We said, “We can’t just sit at home and wait for COVID to go. We need to develop the product and everything else.”

We actually took advantage of the remote situation because initially our office was going to be in Boston, and we were going to recruit engineers in Boston—everybody in Boston. But because of COVID, we said, “You know what? We can hire people anywhere in the country.” And so that actually opened up the pool for us. We went around the country and recruited people from all over.

Q. That’s amazing. And I understand you’re still fully remote, which is very different from many companies shifting to hybrid or back to the office.
So tell us—what’s the secret sauce for keeping people engaged? You’re up to several hundred people now, so how do you keep such a large team engaged remotely?

Siva: It’s not easy. By the beginning of 2023, when things were becoming more normal, we were already up to 400 people across the country.
We didn’t have a choice. A substantial number were in Boston, but that was only about 35%.

So we continued with the remote model but tried to make it more efficient. There are pros and cons. We manage it by making sure management and teams meet regularly.

Our travel budget is high, but since we save on office space, we spend on getting people together. From a management team perspective, we meet once a quarter.

We also have regular team meetings—sales, clinicians, operations, technology, AI, product—each meets in different parts of the country throughout the year. That’s important for building camaraderie.

Q. That’s amazing. And from a time zone perspective, since everyone is in the U.S., that works well. We’ll talk about expansion plans in a bit, but you just mentioned AI. Tell us how you’re applying AI, GenAI, and agents in your product development. Things are moving fast with GenAI.

Siva: In fact, from day one, our goal was—let’s try to provide real-time approvals instead of the usual five to seven days. At the end of those five or six days, if it’s going to be approved anyway, why not do it immediately if the information is there? So we focused on how to approve things faster.

We found that at the end of the prior authorization process, 80 to 85% of requests are usually approved. So we said, let’s focus on that and use AI to approve—not deny—because denial still needs to be reviewed by a nurse or MD. So we focused first on solving that piece.

Today, we approve about 80 to 85% of requests in real time. That’s where AI comes in. We use AI in six or seven different ways on our platform. One of the main ones is this: we get the EMR or medical record from the provider’s office and ask what service is needed. Then, we analyze the unstructured data—diagnosis, patient history, etc.—and determine whether the treatment is clinically appropriate based on certain policies.

For that, our physicians review the algorithms to ensure they’re clinically sound. We have about 50 physicians in the company across multiple specialties. They review the information and help us encode that into the algorithms. It’s a painstaking process, but that’s how we reached 80%, and we’re still improving.

If there’s any doubt about a request, it goes to an MD. We never use AI to deny care—we leave that decision to physicians, who then communicate with other physicians. That’s one big area where we use AI.

We also use GenAI for scheduling patients, retrieving missing information, and automating tasks like converting faxes into structured data. We have intelligent agents that complete entire workflows. Summarization is another area—we use GenAI for documentation and generating letters. We’ve been an AI-native company from day one.

This has helped reduce abrasion because users know that 85–90% of the time, they’ll get an answer immediately. That’s a huge win—they don’t have to wait or reschedule.

We do quarterly user surveys. Our NPS is between 65 and 67—very high. Providers are saying, “Okay, someone is finally solving prior auth,” and that’s one of our biggest outcomes.

For the remaining 15% of requests that still need more review, we’re now working to bring that timeline down to one or two days using AI. We’re able to summarize and present all necessary information so physicians can quickly review and approve it—or reach out to another doctor for a quick consult. So AI is helping us shrink that review time, too.

That’s how we’re deploying AI across the board.

Q. Very interesting. Siva. So that brings me to my next question actually, that when you consider the benchmark of companies or your landscape in which you are doing your competitive positioning, are there any other large players that are in the same space and different and unique and how do you position yourself?  

Siva: The process has been there for more than 30 years. So there are legacy companies that have been doing this for health plans. Yeah. So this is not a new process, right? We didn’t invent this process.

They’ve been doing it, and they are the ones with seven-day, 40-day turnarounds, paperwork, old technology—you’re seeing all of that. So we are completely disintermediating them. We’re creating a completely new category, where we’re actually differentiating ourselves from them.

We’re kind of coming in and changing the way things are being done in this industry.

Q. That is great to know. So, I think we have covered a lot of ground Siva. Any other closing thoughts or any other information or news that you would like to share with the audience? 

Siva: I know that there is a lot of press around prior authorization. To listeners—especially providers and patients—almost everyone goes through this. Just know that companies like Cohere are now using AI to solve the problem. Relief is on the way.

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Disclaimer: This Q&A has been derived from the podcast transcript and has been edited for readability and clarity.