Gen AI Isn't Magic - New Session at PHCA 2025

Artificial intelligence is one of the most talked-about topics in healthcare today. But for long-term care operators, the real question is:

‍How can AI actually improve daily operations, staffing, reimbursement visibility, and resident care outcomes?

At this year’s PHCA Annual Convention & Trade Show, the Megadata team—CEO Shalom Reinman, VP of Technology Aryeh Hoffman, and VP of GTM Dan Brody—led a breakout session to address that exact challenge. The session, “Gen AI Isn’t Magic: A Realistic Look at AI in Long-Term Care,” offered a practical look at how leaders in skilled nursing and senior care can use AI tools alongside real-time data analytics to solve real problems.

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Setting the Stage

Dan opened with a quick poll:

“By a show of hands, how many people here work in a long-term care facility every day?”

Hands shot up across the room. It underscored that the audience wasn’t just curious about the buzz—they were the administrators, clinical leaders, and executives who live the challenges of staffing, compliance, and collections every day.

Dan then set the tone for the conversation:

“Gen AI isn’t magic, but results can be magical.”

That idea carried through the entire discussion: AI isn’t a replacement for strong leadership or long-term care dashboards—but it can enhance them in ways that feel transformative.

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What AI Really Is—and Isn’t

Many operators wonder: What is AI in long-term care, really? Aryeh broke it down clearly:

“At its core, a large language model is just predicting the next word in a sentence. The better the context and the prompt, the better the results.”

This framing helped demystify AI, making it easier to see how tools like AI for PBJ reporting, AI in progress notes summarization, or even AI-driven reimbursement insights can be powerful—but only with the right inputs.

Shalom emphasized the correct mindset:

“We’re not turning to AI for all the answers. Use it as an assistant, not an oracle.”

And Aryeh reminded attendees that AI works best when paired with human expertise:

“To the novice user, it can feel like AI is right every time. But experienced operators will see where it falls short. The good news is—you can guide it to be better.”

For long-term care executives, the message was clear: AI won’t replace your team, but it can augment labor management tools, collections analytics, and clinical dashboards with faster insights.

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Practical Applications in Skilled Nursing and Long-Term Care

The session spotlighted real-world applications that operators can act on today:

PBJ Analytics with AI:

“We were struggling to understand the core logic CMS was using in a 100-page document. ChatGPT processed it and helped output usable code—cutting development time dramatically.” – Aryeh

Custom GPTs for Policies & Procedures:

“Instead of flipping through a 400-page manual, imagine asking a Custom GPT, ‘What’s our PTO policy?’ and getting the exact answer in seconds.” – Aryeh

Clinical Risk Prediction in Nursing Homes:

“By analyzing vitals, meds, falls, and diagnoses, AI can flag which residents are at highest risk and explain why. It’s about getting staff to focus on the right residents, faster.” – Shalom

AI Agents in Healthcare:

“Agents are where things get exciting. They don’t just tell you something—they can take action: read your calendar, propose meeting times, compare data across sites, even draft the email for you.” – Aryeh

Each of these examples ties AI back to core operational goals: reducing rehospitalizations, improving collections, streamlining staffing compliance, and enhancing the resident experience.

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Seeing Through the Hype

The panel was clear: while AI has potential, operators need to see through the hype.

Shalom compared today’s AI craze to the dot-com era:

“AI today is what software was 20 years ago. Everyone will figure out their role in the new AI world, but a lot of companies won’t make the cut.”

Aryeh added:

“All you hear today is AI, AI, AI—just like everyone was talking about ‘www’ during the dot-com bubble. The key is focusing on lasting value.”

For LTC operators, this means looking past vendor promises and focusing on solutions that integrate seamlessly with real-time analytics platforms and solve real problems—whether it’s staffing dashboards, collections performance, or clinical risk management.

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Key Takeaways for Long-Term Care Leaders

1. AI is powerful, but not perfect.
   “It needs guidance, context, and prompting to deliver the right results.” – Aryeh
2. Start with problems, not technology.
   “The best use cases come from solving customer problems, not chasing tech trends.” – Shalom
3. Data is the foundation.
   Without structured, reliable data, AI for skilled nursing facilities won’t produce actionable insights.
4. Use AI as a supplement, not a replacement.
   “It’s a tool to make care more efficient—not to replace your teams.” – Shalom

Final Thoughts

The energy in the room was proof that long-term care leaders are ready to move beyond theory and put AI to work.

The most engaged questions came from administrators and executives eager to test AI in staffing management, billing and collections dashboards, and clinical quality reporting.

And while AI isn’t magic, one message stuck with everyone who attended:

“AI may not be magic, but when you use it to solve real problems, the results can feel magical.”

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Ready to see how Megadata is already helping operators with their labor management tools, collections analytics, and clinical dashboards? Get in touch with our team.

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