Today I had an interesting conversation with MEDENT. It’s an EHR company that’s in only 8 states. I could actually write a whole post on just their approach to EMR software and the EMR market in general. They take a pretty unique approach to the market. They’ve exercised some restraint in their approach that I haven’t seen from many other EHR vendors. I’ll be interested to see how that plays out for them.

Their market approach aside, I was really intrigued by their approach to dealing with ICD-10. They actually described their approach to ICD-10 similar to how Google handled search. There’s all this information out there (or you could say all these new codes) and so they wanted to build a simple interface that would be able to easily and naturally filter the information (or codes in this case). A unique way of looking at the challenge of so many new ICD-10 codes.

However, that was just the base use case, but didn’t include what I consider applying AI (Artificial Intelligence) to really improve a user interface. The simple example they gave had to do with collecting data from their users about which things they typed and which codes they actually selected. This real time feedback is then added to the algorithm to improve how quickly you can get to the code you’re actually trying to find.

One interesting thing about incorporating this feedback from actual user experiences is that you could even create a customized personal experience in the EMR. In fact, that’s basically what Google has done with search with their search personalization (ie. when you’re logged in it knows your search history and details so it can personalize the search results for you). Although, when you start personalizing, you still have to make sure that the out of box experience is good. Plus, in healthcare you could do some great personalization around specialties as well that could be really beneficial.

I’d heard something similar from NextGen at the user group meeting applied to coding. The idea of tracking user behavior and incorporating those behaviors into the intelligence of the EMR is a fascinating subject to me. I just wonder how many other places in an EMR these same principles can apply.

I see these types of movements as part of the larger move to “Smart EMR Software.”