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Pro Tip: Understand the History of EHR Adoption Before Trying to Sell Your Application to a Health System
With an influx of digital health funding, more and more professionals from other verticals are flocking to healthcare in search of new challenges. Due to this, I find myself being asked how to sell healthcare technology to health systems, and ultimately having the same conversations week after week. Many of the people I speak with have only recently jumped into this industry and are excited to be part of the action. Typically, they have an amazing product they’re psyched to sell, and they want to get it into the hands of patients and providers as quickly as possible. And that’s great! Their enthusiasm is a huge part of why this industry is growing at such an astonishing rate. But, awesome as it is, their drive also lacks a healthy dose of reality—though it isn’t ideal for anyone, the truth is that the healthcare industry moves at a rather sluggish pace. This is due to the incredibly long sales cycles at health systems, and also their history of being rather conservative when it comes to adopting new technology (the phrase “a matter of life and death” is not hyperbolic when it comes to relying on new medical technology to perform as promised). So, no matter how innovative your product is and how badly you want to sell it, you have to realize that it’s just not going to hit the shelves quickly. Selling your digital health application is something you have to be in for the long haul. Two Things to Know about Health IT Instead of diving head-first into how to sell to health systems, I’ve decided to lay down a (somewhat) brief background on the two things you need to know about healthcare tech in order to do so: How did we get to where we are today (a world of innovation and desire for applications like yours)? AKA — understanding how history shapes the current status quo. How do existing healthcare IT systems function (operationally and from a tech stack standpoint). AKA — Using this knowledge, what can I do to prime my product for success? *Bonus*: Because brevity is not my strong suit, I also jotted down three tools/takeaways to use when working with health systems. How Did We Get Here? When I started in healthcare tech at a large EHR vendor in early 2009, I was simply grateful to have a job (quick reminder of the economy circa 2009). I never planned on getting into healthcare—I had an anthropology degree and was actually preparing to pursue my PhD before, in a moment of clarity, I realized I wasn’t ready to sign up for seven more years of school. I applied for one job and happily took it during a time when others around me couldn’t find steady work. I started Epic with a group of 37 peers. Less than a year later, new hires would start with groups 10x that size. What happened? How EHRs Reached Market Penetration HITECH, Meaningful Use—government regulations and incentives around electronic health records (EHRs) spurred a lot of change quickly. Meaningful Use was well-intentioned. After all, It was supposed to be about improving outcomes. While I truly believe most EHR vendors had good intentions, they ended up focusing more on checkboxes (an inevitable byproduct of government mandates), than actual outcomes. I’m not going to say they were wrong, or the ONC was wrong, but let’s just say that a variety of factors contributed to the actual execution of the program. The question became “can our system functionally complete ‘x’?” instead of “will our patient population’s health improve because we are going to need to report on readmissions and therefore we’ll need to focus more on keeping patients well and out of the hospital.” Health systems and provider groups alike asked themselves, “if our current system won’t support the cash incentives we could get from attesting to Meaningful Use, should we switch? We’ll have to upgrade... should we look for a different/better/faster/slicker/more light-weight system? Should we find something our docs love?” As the deadline for adopting Meaningful Use grew near, I watched install timelines get progressively shorter. At the risk of being penalized, health systems asked for accelerated installs of large, complex, and fully-integrated software that they had never used before. Though well-intentioned, they were setting themselves up for a huge mess. IT teams who had previously been fairly siloed had to come together to understand how to implement and support an integrated system, one that put pharmacists, nurses, doctors, and registrars all in one bucket—and where one change in a workflow could bring down the system for hours. With everyone pushing to meet deadlines, we did more with less—fewer analysts, fewer resources, fewer dollars in the budget. Installs should get faster and easier each time, right? Because we learn, right? To some extent, yes, but undoing or supporting decades of customized code and personalized menus and one-off workflows is difficult from both a technical and change-management perspective. This created an environment where every decision needed to be carefully evaluated, where no “quick fixes” were available and a climate of change control and bureaucracy was necessary. To make things even more difficult, IT teams were faced with an exodus of analysts fleeing for newly available (and high-paying) consulting jobs thanks to their newfound Meaningful Use experience. When it was all over, IT centralized, but purchasing power didn’t. Product and feature enhancement lists grew and grew. To top it off, EHR vendors, because of the complexity of their own systems, needed to undertake significant testing for each release (as they should), but it meant that true function requests were delivered every 18 months, and that was only IF the health system decided to upgrade (which is based on stability, resources, time and money). This unfortunate series of events caused the accelerated digitization of our medical records using systems with unique and limiting configurations. This has given rise to the exploding digital health climate we see today.
