Key Healthcare Interoperability Insights From the eHealth Exchange Annual Meeting

At the eHealth Exchange Annual Meeting, healthcare leaders explored the progress, challenges, and future of nationwide health data exchange. From network trust and data quality to payer-provider interoperability, healthcare AI agents, and appropriate data access, the discussions highlighted the complex work required to make health information sharing more secure, useful, and reliable.

Here are some of the key announcements, perspectives, and takeaways from the meeting, along with additional commentary from Healthcare IT Today.

As a community, it was exciting to see Douglas Dietzman on stage for his first Annual Meeting with eHealth Exchange. Definitely was a unique venue in the hills of Austin that felt more comfortable than a bland conference room.

I think by this point you know that I’m a stats nerd. It’s great to see eHealth Exchange doing 32 billion data exchanges each year. That’s an impressive number. The growth across a wide variety of categories is particularly interesting.

At the core of all these healthcare interoperability discussions is trust. A network like eHealth Exchange must create trust within the network. This look at what they do to engender trust is great to see.

I imagine that many people in health IT don’t know eHealth Exchange. This is a good overview of some of its history and the trusted exchange work they’re doing.

I was fascinated that Dietzman positioned his first presentation on the eHealth Exchange Annual Meeting stage as assurances moving forward. This is a great example of good leadership of a network. It’s important that a network communicates clearly what’s important to them and the values that they live by.

This list of focus areas for eHealth Exchange was really interesting. In many ways, I’d describe them as being involved in almost every type of exchange. It’s impressive to see the depth of work they’re doing.

Sam Kaardal was one of the best ONC presentations I’ve seen. He did a great job summarizing the work that ONC is doing. These 3 priorities were a great summary of where ONC is focusing.

When it comes to government policy, certification, standards, etc, it can be easy to forget the purpose of all these efforts. Kaardal reminded all of us that each of the ONC efforts is really focused on making healthcare better.

This is the simplest look at how health IT has evolved over the last 2 decades that I’ve been covering the industry. How quickly do you think we’ll get to computable?

I loved this slide from a provider that shared what payer-provider exchange looked like at their organizations. The number of contracts they have to navigate is overwhelming. I’ll definitely be referencing this slide when people think that healthcare data sharing is simple.

This was a good analogy for provider-payer exchange. In fact, Michael Westover said that it’s more like a food fight with people throwing everything at each other. What do you think of this analogy? Do you think it’s a good description of what it’s like?

One of the common themes across the annual meeting was the challenge of knowing whether the exchange of health data is appropriate or not. The fear of misuse is real in this community. Plus, we have a lot of different definitions of what “misuse” really looks like. And yet, the network has a responsibility to evaluate usage and protect the network as much as possible from misuse. This is a real challenge.

This line from Matthew Eisenberg was a powerful example of the importance of governing the use of data on a healthcare network. You have to be a little judgmental to avoid misuse and make sure that the network is trusted.

I love Mariann Yeager’s description of the need to verify as a way to build trust. I think we’d all love for that to happen so we can more easily trust.

The AI Agent Doctor panel was one of the most provocative panels at the conference. This is a quickly evolving as healthcare starts to embrace AI powered doctors. There is not agreement on whether these new AI “doctors” deserve the same access to data as a human doctor. Imagine being a patient treated by an AI doctor which doesn’t have access to your health data. That’s scary. However, the fear of startup companies saying they’re an AI doctor to be able to pull in all your health information exploring for opportunities is real too. We’ve seen this happen already with the treatment use case in TEFCA.

Some really interesting responses to Brendan’s question. What would be your answer to this question?

Quality data is another hot topic in health data exchange now. Doctors don’t want to be overwhelmed with all the data. They want the data that is needed in their current context. Plus, they don’t want duplicate data or data that they can’t trust. Health data sharing has gotten doctors more of the patient’s data, but it also has made that data much more complex and harder to trust.

One of my big takeaways from the quality session was that it’s complex and context really matters. There’s risk in sharing poor quality data. There’s risk in not sharing that data if it could impact care too. There’s no simple answer to this other than doing the hard work of improving the quality of the data over time. Also, provenance can help those who view the data know how much they can trust or not trust the data too.

Thanks to eHealth Exchange for having Healthcare IT Today at their annual meeting. It’s amazing to see the progress that we’re making on healthcare interoperability and how much more work there is to do.