![]() In the video interview they share about Ambience Healthcare and how their solution fits between things like Human Scribes, Ambient Clinical Voice, and EHR templates. Rather than describe their approach and solution myself, I hopped on camera with Mike Ng, Co-Founder & CEO, and Nikhil Buduma, Co-Founder & Chief Scientist at Ambience Healthcare to learn more about how they’re approaching this EHR documentation burden problem. With this as background, you can understand why I was intrigued by a new company called Ambience Healthcare which just came out of stealth mode with what they describe as fully automated AI medical scribes. None of these happen if the note isn’t completed in real time during the visit. Second, the real time clinical decision support alerts and the coming value based care alerts often depend on the data that’s being inputted into the note. Not a massive issue since doctors are largely used to charting patients well after the visit, but still not ideal and could lead to mistakes. ![]() First, the doctor still has to go back and finalize the note they get from the ambient clinical voice well after the visit. This causes two major workflow challenges. The second major problem of humans in the loop with ambient clinical voice is that it means there’s a delay in getting the notes completed for the doctor. There are lots of views on this out there, but looking at prices for ambient clinical voice today, this is still to be determined. If they can’t, then pricing becomes an issue for many organizations. Can the backend humans be replaced by technology? If they can, then the cost to provide ambient clinical voice will be driven down. Sure, the AI can make the humans more efficient and effective, but it still means that ambient clinical voice using this approach will be expensive. First, if there are humans doing the work in the backend, that means that you can’t use technology to drive the cost of the service down. Why is this a problem? The problem is two fold in my view. ![]() However, it’s not as automated as the user may think. For the end user, the note is created automagically for them. One of the biggest challenges of ambient clinical voice is that while the technology is listening to the conversation in the exam room, the back end solutions today are using a mix of technology and people (essentially remote scribes) to create the note. In other words, there are a lot of companies working on this problem since the documentation burden on clinicians is real. Plus, there are also a number of scribe companies literally putting people in exam rooms to address the issue. Suki is another AI assistant that’s taking a very different approach to the problem. 3M through MModal is playing in this space as well. The biggest player in this right now is Nuance (now part of Microsoft) and their DAX product (They like to call it ambient clinical intelligence). One of the biggest efforts out there right now is called Ambient Clinical Voice. It’s a burden that’s burning out physicians. As most of you know, I’m a huge fan of all the efforts going on to improve the physician documentation process.
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