Healthcare pricing has always been a hidden system, built up over decades of complexity. Peeling back those layers is the whole reason the price transparency laws exist in the first place. A whole industry has grown up around making that data accessible. However, there’s still a wide gap between access and usability. Even if you can access the data, and that’s a big “if” given the size and complexity, actually turning it into tangible insights requires specialized expertise and teams of analysts. Not to mention the time: seemingly simple requests can take days or weeks to answer.
The first step was making all of this data accessible, with the most detail possible. Payerset has been on a journey to build the infrastructure that gives anyone self-service access to the full detail and the full history of the transparency data. Now we are excited to launch the next evolution: the Payerset Research Assistant. We’re combining the industry’s most complete healthcare pricing dataset with years of hard-won context from working with customers, so anyone can answer the most complex pricing questions in healthcare.
Why not just another “Ask Data” integration?
It would have been easy to put a chatbot on top of our existing UI, or on a slice of the data. That gets you to a good demo, but nowhere near the depth that healthcare pricing actually requires.
Take a seemingly simple question: “How do I compare across ortho surgeries for my top three competitors in Georgia for Elevance?”
Here’s an idea of what actually has to happen underneath it:
- Explore the full scope of NPIs, both organizational and individual physician, through ownership structures and affiliations to understand where the contracts may be associated.
- Understand how that specific payer publishes. The group might have some rates contracted at the individual provider level and some at the organization level. Or the payer might only publish at the individual level, and that’s where the true source lives.
- Figure out what those groups actually perform and what they’re billing (that’s claims data).
- Query every plan and network under Elevance.
- Then normalize and compare. Some anomalies are valid and some aren’t, so you compare against the right Medicare benchmark, the facility vs. professional component, and settings like ASCs the practice might own. Evaluate networks, plans, and other legitimate drivers of rate variance.
What looked like a simple question is actually multiple threads to chase across multiple data sources, plus the context and industry knowledge that’s impossible for an LLM to know on its own. And that’s before you even get to presenting it, where you need the flexibility to go anywhere from the raw data all the way up to an executive report for the board.
That’s the crux of what we built with the Payerset Research Assistant: making all the depth and knowledge required to answer healthcare pricing questions available to everyone.
The time is now
We’re five years into the transparency laws going into effect, and we’ve reached a tipping point, from continued focus on relevant policy and enforcement to the technological strides that finally make a solution like this possible. The demand is reaching critical mass and coming from every corner of the ecosystem: health systems, self-funded employers, and the patients caught in the middle, all of them clamoring for a market that actually works.
We are entering the next era of price transparency: not just accessing the data, but enabling everyone to actually use it, especially the people and organizations who never had the time or the resources to do it themselves.
Read the full press release on Business Wire.