High-performance, scalable, and fully managed. Explore the Mega Data Warehouse
AI in skilled nursing is no longer a future-state conversation. It's happening now — and the operators who understand why their data infrastructure matters are the ones who will move fastest.
In Episode 5 of Care, Code, and Capital, Dan Brody sits down with Shalom Reinman, CEO of Megadata Health Systems, to talk about what 18 years on the inside of long-term care data actually taught him, why the user interface of healthcare technology is about to change completely, and what it looks like when AI connects to a decade's worth of clean, integrated clinical and operational data.
Shalom Reinman didn't set out to build a healthcare technology company.
In 2008, at 23 years old, he took a billing job at a nursing home for $23,000 a year. His brother had talked him out of his entrepreneurial instincts. Get in the door. Learn the business. Be around people you can learn from.
So that's what he did.
What followed was 18 years of working from the inside out. Accounts payable to financial analysis. Excel workbooks to IBM business intelligence systems. One nursing home company to the next, always chasing the same question: how do you actually run this business on data, in real time, before a small problem becomes a crisis?
By the time he was building analytics platforms at Marquee, now a 100-plus facility organization, Shalom had his answer. The problem was, he'd built it for one company. He wanted to build it for the industry.
That's why he left to start Megadata.
Before the Series A. Before 80-plus integrations. Before the data warehouse. There was Covid.
When the pandemic hit, nursing homes were ground zero — roughly 40% of U.S. deaths in the early months. Business analytics didn't matter anymore. What mattered was whether Megadata could actually help.
Shalom's team started digging into the clinical data they already had. Temperature readings weren't early enough. But oxygen saturation data was different. A single resident dropping from 95% to 90% didn't register as alarming on its own. But when 20 residents in the same building showed the same slight drop on the same day, that was a signal. And it was appearing days before anyone in the facility knew they had an outbreak.
Ten out of eleven operators who signed up for a trial became real customers. The story made ABC Nightline.
"We realized the only thing that really matters right now is how can we help people with this. We'll figure out business ones later."
That moment clarified what Megadata was actually building: not a reporting tool, but an early warning system. Not dashboards for their own sake, but data infrastructure that could save lives.
Today, Megadata serves multi-facility LTC operators with an analytics platform built on 80-plus integrations, a native mobile app, and a Mega Data Warehouse that connects every part of the business — census, labor, clinical, finance, and reimbursement — into one place.
But Shalom is honest about where the real work happens. Eighty-five to ninety percent of what Megadata has built isn't what customers see on the surface. It's the data infrastructure underneath. The integrations. The data models. The years of business logic that make the data clean, accurate, and HIPAA-compliant.
That foundation is what makes AI in skilled nursing actually work — not as a demo, but as a daily operational tool.
In the last six months, Megadata's data warehouse customer count grew from two to twelve without a single marketing campaign. Operators who had connected AI tools to their own data were reaching out, asking if they could tap into Megadata's. The answer was yes.
"The user interface of the future is not navigate to a dashboard, drill down into some predetermined drill-down path. With tools like Claude and other AI tools, you could ask a bunch of questions. It generates the charts. You could ask more advanced questions. It answers the questions."
That shift — from navigating to asking — changes who can use the data, how fast they can use it, and what they can build with it. Financial analysts who have never written a line of code are becoming, in Shalom's words, software developers. Internal tools that used to cost $100,000 to build are getting built in a day.
For nursing home operators sitting on years of integrated clinical, financial, and operational data, the opportunity is unlike anything the industry has seen.
One line that stayed with us:
"The humans who use AI most effectively are going to be the most valuable people. The ones who avoid it — they get left in the dust."
Worth your time, whether you're running facilities, building technology, or trying to understand what's actually coming in long-term care.
