Every software vendor in home health claims to have an AI story right now. Listen to enough of them and they start to sound the same: a workflow takes too long, so just add AI and release a new feature. Every demo looks impressive. Every product feels the same.
But there is a foundational problem. Home health agencies currently run five, six, even seven tools to manage a single patient episode. An EHR for documentation and billing, a separate tool for intake, a spreadsheet for scheduling, a documentation assistant and a coding team.
Zach Newman, CEO of Enzo Health, spent months asking operators what they actually wanted in their agencies. The answer was consistent: they want a better system altogether.
“Adding AI features can help,” he says. “But it ignores the bigger problem: the fact that five different platforms shouldn’t be necessary at all.”
The companies that built those platforms weren’t wrong. They solved real problems with the tools they had. But they built piece by piece, department by department, responding to requests rather than looking at the whole picture. The result, accumulated over decades of incremental updates, is a patchwork. And patchwork has a cost.
Everyone working inside legacy software knows the feeling: it wasn’t built for how the work actually happens.
“If you bolt an AI documentation tool onto that architecture, you get faster notes. That’s real value,” Newman says. “But the outdated EHR is still at the center. It’s still the bottleneck. Now you’ve just plugged faster outputs into the same broken foundation.”
Some agencies have gone further, building AI agents within their traditional legacy systems. The work moves faster, but so do the mistakes. Instead of catching problems early, teams spend their time reacting to errors that already cleared several steps. The issues don’t go away — they just travel faster than anyone can track them, now with less visibility into what’s happening.
Newman stopped asking how to improve what existed. “At some point the answer isn’t another point solution,” he says. “It’s a new system entirely.”
“What used to take 10 days is now four to five at the very most.”
On June 1, Enzo Health released what it’s calling the first AI-native home health EHR. Newman and his team didn’t add AI to an existing system: they built an EHR with AI as the foundation. Not feature by feature. From the ground up.
The result is a system that doesn’t simply record what happened and wait for a human to act. It moves every step of the patient episode forward automatically, pausing only when something requires human judgment. And it gets better over time.
Trisha Perrenoud (RN, BSN, MSN), administrator at Alliance Healthcare of Idaho, brought Enzo into an operation that had run on a patchwork of systems for years. “What used to take 10 days is now four to five at the very most,” she says. “I took a risk at first because I didn’t know what it was going to look like. Now the results are proven.”
This is what Enzo EHR was built to do across the episode. Referral-to-admit decisions happen in minutes. Sixty days of scheduling are generated instantly. The OASIS builds itself in real time during visits. Charts are automatically reviewed before reaching a biller. All without any handoffs, data re-entry or separate tools bridging the gaps, because the gaps don’t exist.
“That’s not a roadmap,” Newman says. “That’s what Enzo EHR does today.”
A new stage in home-based care AI
Home health agencies that want AI point solutions will have no trouble finding them. The harder problem is the architecture underneath. It’s the same software it’s always been, only now it moves faster. The patchwork didn’t go away. It just got automated.
Two types of agencies will come out of this moment. One added AI features to the systems they already had. The other replaced those systems with something built for AI from the start. Those two agencies look similar today. They won’t for much longer.
This Views is sponsored by Enzo Health. To learn more, visit them at enzo.health.