The “Smart EMR” Differentiator

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.

About the author

John Lynn

John Lynn

John Lynn is the Founder of, a network of leading Healthcare IT resources. The flagship blog, Healthcare IT Today, contains over 13,000 articles with over half of the articles written by John. These EMR and Healthcare IT related articles have been viewed over 20 million times.

John manages Healthcare IT Central, the leading career Health IT job board. He also organizes the first of its kind conference and community focused on healthcare marketing, Healthcare and IT Marketing Conference, and a healthcare IT conference,, focused on practical healthcare IT innovation. John is an advisor to multiple healthcare IT companies. John is highly involved in social media, and in addition to his blogs can be found on Twitter: @techguy.


  • Good post, John. Coincidentally, as part of my Master’s in Medical Informatics, we designed systems as you described above. The EMR was integrated with a federated data repository (which includes all medical care, vaccinations, meds etc.), patient info such as that reported by blood glucose meters etc. In addition, we featured a closed loop. The patient would (in an ideal world) go to a stand alone facility but be referred to the local ER. That Er would be notified and have all past patient informtion prior to them coming through the door.

    This sounds like a dream world, but it is something to work towards, right?

  • Hi Joan,
    I guess that’s the funny part. The technology is already available for almost all of this stuff. It’s just getting it implemented in a thoughtful way so that doctors actually can use it.

    I’d say it’s not just something to work towards, but will likely be a basic requirement of EMR in the future.

  • John

    I love the idea of these integrations. The challenge has been the volume of these integrations. There are thousands of data repositories, devices, and apps that store data outside the doctors office/hospital.

    Developing interfaces to pull in date from each one would be a never ending process.

    In order for something like this to happen in a meaningful, large scale way, there need to be standards. Currently, the only widespread standard I’m aware of for discrete data beyond hl7 (hl7 is really not specific enough for these types of discrete measurements) is DICOM for medical imaging.

    If only th government would step in To help create these standards so that software companies and EHRs can integrate them in a meaningful way

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