We’ve all heard it—AI is going to revolutionize healthcare. It’ll predict diagnoses, optimize billing, streamline prior auths, and even tell your doc when it’s time to refill your prescriptions.
Sounds great, right?
But here’s the kicker most folks don’t talk about: AI, for all its hype, still has a major blind spot—it can’t access the data it needs from EHRs without a little help.
Let’s unpack that.
The EHR Problem Nobody Wants to Talk About
Electronic Health Records (EHRs) are a goldmine of clinical information. But they weren’t built for open access or easy integration. Most are heavily siloed, filled with proprietary logic, and sitting behind interfaces that are… well, let’s just say less than friendly.
APIs? Limited and expensive. HL7/FHIR? Great in theory, but a mess in practice—especially when you’re dealing with older or customized systems.
So, what’s an AI supposed to do when it needs to pull in a patient’s chart, analyze treatment history, and spit out a recommended care pathway?
It can’t—not without something (or someone) doing the heavy lifting to get that data first.
Enter RPA: The AI Whisperer
This is where Robotic Process Automation (RPA) steps in. We like to think of RPA as the hands and eyes for AI in the healthcare space.
Let me give you a real-world example: one of our clients wanted to use a machine learning model to predict prior auth denials. Smart idea—but the model needed access to real patient data to train itself. The problem? That data lived inside 4 different EHRs, all with different UIs, login protocols, and workflows.
Did the AI figure it out on its own?
Of course not. We deployed attended and unattended bots that could log into each system, extract structured and unstructured data (think demographics, CPT codes, previous denial reasons), and send it to a central repository for the AI to work its magic.
Without RPA, that AI would still be twiddling its thumbs, waiting for someone to hand it the data on a silver platter.
AI + RPA = Healthcare Harmony
Here’s the deal: AI is only as good as the data it’s fed. And in healthcare, that data is often locked away behind 8 different clicks, a Citrix session, and a 3-minute load time.
RPA doesn’t care. It’ll wait. It’ll click. It’ll extract and validate.
Better yet, it’ll do it 24/7, error-free, and at scale.
Now we’re seeing powerful AI solutions emerge—not because they magically integrate with EHRs, but because RPA made the introduction.
Looking Ahead
Healthcare orgs are rushing to adopt AI, and rightly so. But the ones seeing the best results? They’re the ones who realize that RPA isn’t just a stopgap—it’s a strategic partner.
AI might be the brain. But RPA? It’s the body that gets the job done.
So next time someone tells you AI is the future of healthcare, smile and nod. Then tell them it’s RPA that’s quietly doing the work behind the scenes.
Want to see how AI and RPA can work together in your healthcare organization? Drop us a line—we’ve done it before, and we’re ready to help you do it too.
Written by: Mihai Cerbu, CTO
