The “Smart EMR” Differentiator

Posted on October 25, 2011 I Written By

John Lynn is the Founder of the HealthcareScene.com blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of InfluentialNetworks.com and Physia.com. John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

As I’ve been able to talk to more and more EMR companies I’ve been trying to figure out a way to differentiate the various EHR software. In fact, when I meet with EHR software companies I suggest that instead of them showing me a full demo of their EHR software, I ask them to show me the feature(s) that set their EHR apart from the other 300+ EHR companies out there. I must admit that it’s always interesting to see what they show me. Sometimes because what they show me isn’t that interesting or different. Many of my EMR company specific posts come from these experiences.

Today at MGMA as I went from one EHR company to another I started to get an idea for what might be the future differentiation between EHR companies. I’m calling it: “Smart EMR.”

You can be sure that I’ll be writing about my thoughts on Smart EMR software many more times in the future. However, the basic idea is that far too many EHR software are just basic translations from paper to electronic. Sure, some of them do a pretty good job of capturing the data in granular data elements (something not possible on paper), but that’s far from my idea of what a future Smart EMR software will need to accomplish.

I’m sure that many of those that are reading this post immediately started to think about the idea of clinical decision support. Certainly clinical decision support will be one important element of a Smart EMR, but I think that’s barely even the beginning of how a Smart EMR will need to work in the future. However, clinical decision support as it’s been described to date focuses far too much on how a clinician’s discretely entered data elements can support the care they provide. That’s far too narrow of a view of how an EMR will improve the patient-doctor interaction.

Without going into all the detail, EHR software is going to have to learn to accept and process a number of interesting and external data sources. One example could be all the data that a patient has in the PHR. Another could be patient data that was collected using personal various medical devices like a blood pressure cuff, an EKG, and blood glucose meters. Not to mention more consumer centric data devices and apps such as RunKeeper, Fitbit, sleep tracking, mood tracking, etc etc etc.

Another example of an external source could be access to some community health data repository. Why shouldn’t community trends in healthcare be part of the patient care process? None of this is far reaching since we’re collecting this data today and it will become more and more mainstream over time. Something we can’t do today, but likely will in the future is things like genomics. Imagine how personalized healthcare will change when an EHR will need to know and be able to process your genome in order to provide proper care.

I don’t claim to know all the sources, but I think that gives you a flavor of what a Smart EMR will have to process in the future. I’ll be interested to see which EHR software companies see this change and are able to execute on it. Many of the current innovations in EHR have been pretty academic. The Smart EMR I describe above will be much more complicated and require some specific skills and resources to do it right.