The future of healthcare interoperability lies in our ability to achieve a similar level of data liquidity that drives innovation in other industries. Where access to health data has nothing to do with accessing a source system or knowing anything else about the network in which it sits. But where are we now with interoperability? And why is the transition so slow? 

We'll start with an analogy about how the movie-rental industry was forever changed by questioning the very distribution method for movie rentals.  Netflix replaced Blockbuster by eliminating the drive to a brick-and-mortar store and all of the little annoyances we all took for granted. Late fees, poor interactions with staff, waiting in line, and the uncertainty of whether you’ll find something. For individual consumers, renting a movie you’d like was made easier with a simple web interface and a flat monthly fee. The Netflix story doesn’t end with DVD-by-mail though, right? 

There is a greater lesson to be learned for those of us in healthcare that lived through the migration from paper patient records to electronic health records and the first interoperability standards. Netflix eventually drove the wedge between digital and physical delivery by way of data and they disrupted themselves over a period of years and moved almost entirely to a streaming-only service. Not only was the change better for Netflix, but it was better for their customers as well. They leveraged gender, age, and rental history data to make eerily accurate title recommendations. Sure, Chad at Blockbuster could spend a few minutes talking to you while strolling through the comedy section and make a recommendation that might be right for you. But who has a better chance of being right? Chad, or the data that knows every movie you watched, rewatched, and rated?

The same could be true for healthcare. A doctor can recommend treatments because they have the education to do so paired with what you shared during your appointment. However, if you have data in another doctor's office or lab system that was never communicated to your provider, all of that data is missing from their treatment recommendation. These gaps lead to situations where providers will unknowingly order duplicate tests, find it harder to establish an accurate diagnosis or miss opportunities for early interventions within their high-risk patient populations.  

By moving from a reliance on static charts inside of an EHR to accessing centralized repositories of patient health data that doesn’t care which platform a provider uses, we would see the same scale of change and increased value in healthcare that we saw with Blockbuster to Netflix transition. Health information exchanges built on the modern principles of data liquidity wouldn’t entertain us, it would save lives and greatly reduce the cost of healthcare. 

With the promise of these benefits, why are we stuck in the middle stage of interoperability? 

The current state of interoperability feels like the equivalent of Netflix’s original postal delivery service; there are benefits to the advancements that have been made but we’re just not quite there yet. The high-level answer is that healthcare is vastly different from any other industry when it comes to market drivers and incentives. For data to interoperate between external systems to become the norm, not just internal systems in one organization, there needs to be a market driver.  

Over the past 10 years, the expectation of an electronic health record system was that interoperability could be achieved by taking the data in physical charts, that you could not previously interoperate, and put them in a single system. Then the government got involved, for all the right reasons, because we had critical, massive data that could be used for great outcomes.

The current incentive is not just from a reimbursement perspective, but also to not get fined. The government became the catalyst for some of this change and movement forward. Yet still, the industry incentives are just to be compliant and be certified, which is fundamentally different from every other industry. We are finally at a nexus where the development community is on the bleeding edge of artificial intelligence, machine learning, and doing amazing things in other industries that we as people are starting to expect, and should expect, in healthcare as well. The idea of using big data to move industries forward is becoming more accepted, where it used to be scary.


However, data acquisition is still the problem. 

Interoperability has gotten a bad rap because it's been around for so long with very few results. Healthcare is at the point where we have to change the narrative from interoperability and exchanging data from one system to another to data liquidity. This is how real change was realized in other industries.

This is how Blockbuster was replaced by Netflix, by using big data to do what another human potentially could not do. Machines can be used to assist in diagnosing an illness and the best treatment of said illness but these tools are hindered because interoperability was expected to be a promise of access to data, which is not what happened. Instead, interoperability is the access to data within specific systems and the red tape is holding the industry back.

Where does Healthjump come into this equation? 

For data to become liquid, the outgoing information needs to be structured. Healthjump converts the raw EHR data into a usable format. The Healthjump Platform manages the collection, storage, and movement of financial and clinical data between EHRs, applications, and healthcare organizations. We leverage developer resources and automation to access and deliver data via API, webhooks, flat-file, HL7, FHIR, and more.

Essentially, our role in the movement to data liquidity is just as disruptive as Netflix was to Blockbuster. Eliminating the extra steps in the middle that consumers of health data must take today, serving up normalized flat-files of EHR data right to a company’s digital S3 doorstep, or streaming it directly into their application via modern development tools such as API, Webhooks, or even FHIR.

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