Not many companies have benefited from the rising interest in artificial intelligence-enabled clinical documentation more than Abridge.
On Monday, the company announced a $250 million Series D fundraise one year after it nabbed $150 million in a Series C round.
Related: Inside the competitive ambient AI vendor space
As more health systems adopt ambient AI documentation tools, which turn a recording of a doctor-patient conversation into usable clinical notes, Abridge has become a major player. The company has won business from Oakland, California-based Kaiser Permanente, Baltimore-based Johns Hopkins, Durham, North Carolina-based Duke Health and many other systems.
Along with the funding, the company also announced on Monday the creation of a new AI tool that will produce billable notes at the point of care. In January, Abridge revealed it was rolling out an AI documentation tool specifically for emergency medicine doctors after testing it with Atlanta-based Emory Healthcare, Johns Hopkins and a few other health systems.
“Emergency medicine clinicians face the highest rates of burnout of any specialty,” said CEO Dr. Shiv Rao, who started the company in 2018. “When you think about how chaotic and frenetic emergency medicine can be, that’s really what drew us in. Part of our ethos as a company is to run into challenges.”
But that’s not the only area Abridge is targeting within clinical documentation. In an interview, Rao said they’re also going after nursing burnout. The interview, conducted before the announcement of Abridge's Series D fundraise, has been edited for length and clarity.
Now that you’ve rolled out ambient AI documentation for emergency medicine, what other areas of medicine are a focal point for Abridge?
A big focus for us this year is nursing. That's one key area of continuous development. We previously announced that we were starting work with the Mayo Clinic and [electronic health record company] Epic on a nursing solution. This is the year where we're going to be deploying that work and getting feedback, iterating upon it, and hopefully scaling it across the country.
How do those nursing workflows differ from physician documentation workflows?
My God, it’s 10 times more complicated than [physician] workflows. A nurse goes into a room, they're talking to a patient, a family member, they're recording vital signs, they're noticing the quality or the color of the urine. … All of that information needs to get turned into structured data. It's not a story the way my notes might seem. It's structured data that goes into very discrete fields inside the medical record that are called flow sheets. They're basically spreadsheets. And there's a challenge that once you've seen one of these flow sheets, you probably have seen only one of those flow sheets. So how do you take information from very unstructured and seemingly disparate data sources and convert that into structured data and discrete data?
With so many ambient AI documentation vendors out there, how do you stand out?
The proof is in the pudding. We typically get the question, “How are you different from your competitors?” And there's one company that we tend to compete with in the segment of the market we focus on and that's Microsoft/Nuance. On the other end of that spectrum, healthcare is not homogenous. With small provider groups and independent doctors, there could be any number of startups in that space. But we’re in the enterprise space and it's obviously a very different story. The boxes that they're looking to check off are related to: Can you be a true enterprise grade partner for the decades to come? Are you capitalized for it? Can you check off all the compliance and security boxes? What kinds of certifications do you have? How can you demonstrate that you can really do what you say you can do, and create these notes for all the different specialties? Can you handle how diverse our population is? Can you do telemedicine conversations as well, in addition to in-person? In that world, we tend to mostly just compete with one company and so far, so good. We’ve been able to demonstrate a significant differentiation.
What does the pricing of these tools look like for health systems?
The big evolution over this past year has been enterprise pricing. More often than not, we figure out what enterprise pricing can look like for a health system, and that feels a little bit more like all you can eat. Part of the dynamic is, once we go live, sometimes it can turn into a story of the haves and have nots. "Why did those 50 doctors get it and we didn't?” Health systems are trying to get ahead of those potential challenges … and land on something that they can affordably scale across their system.
