AI in Public Health: What We Learned from 2025's NACCHO360 Plenary
Featuring insights from Jonathan Giuffrida, Co-Founder & CTO of Metopio
As the cost of generative AI surpasses our country’s total investment in public health, it raises a critical question: How do we make AI work for us intentionally, responsibly, and meaningfully?
At NACCHO360, Metopio co-founder and CTO Jonathan Giuffrida took the plenary stage to explore this question head-on. The session focused on how local health departments (LHDs) can harness AI to accelerate Community Health Assessments (CHAs) and Community Health Improvement Plans (CHIPs) without fully handing over the reins to technology that still doesn’t know the difference between a dog and a muffin.
Here’s what he shared.
AI Is Everywhere, But It Can’t Replace You
Jonathan opened with a reality check: AI is being deployed across every app and industry, but it still lacks context and judgment — two things essential for public health work.
Generative AI works by filling in the blank. But the real challenge isn’t completing a sentence, it’s knowing which blanks actually matter. That’s where humans lead and AI supports.
A Smarter Way to Work: Think of AI as Your Junior Collaborator
In recent years, Metopio has worked with more than 100 LHDs and hospitals to automate and accelerate the CHA and CHIP processes. Jonathan shared how integrating AI into small, specific tasks across the workflow — like reading transcripts, drafting reports, or summarizing datasets — can reduce CHA timelines by more than 80%.
““Think of AI not as a decision-maker, but as a junior collaborator, one that does 80% of the tedious work and lets you focus on the decisions that matter.” ”
Real Use Cases: How LHDs Are Using AI Today
Jonathan offered a behind-the-scenes look at Metopio’s platform in action:
Turning Focus Group Transcripts into Thematic Summaries: AI instantly reads and groups surveys responses while allowing users to edit everything before finalizing reports.
Providing Sentiment Analysis: AI is helping Metopio users understand how people feel about issues like food access using tone detection and highlight features.
Automating Data Visualizations: Metopio can generate hundreds of charts and maps in minutes. Then, AI writes accurate captions and highlights key insights, like which zip code has the highest rate of depression.
Drafting Narratives: Metopio’s AI uses your real community data (surveys, aggregate claims, historic CHAs) to draft your CHA narrative, surfacing patterns across datasets while keeping you in control.
““This isn’t a black box. You see what the AI pulls, you edit it, you always make the final call.” ”
Moving from CHA to CHIP: Closing the Loop with AI
AI isn’t just streamlining assessments, it’s helping improve and implement community health strategies. With Metopio, you get access to:
Evidence-Based Program Recommendations: Metopio’s AI pulls from a curated library to suggest programs aligned with your priorities
Logic Model Generation: Translates your ideas into structured plans.
Multi-CHIP Rollups: Aggregates impact across programs or counties for system-wide visibility.
What’s Next: AI That Knows Its Limits
One of the most compelling demonstrations was Metopio’s AI assistant, connected directly to survey data. Users can ask it questions in plain English (“Cross-tab X by Y,” “Summarize this topic”, etc.) and it uses secure, HIPAA-compliant access to run real SQL queries and build charts on demand.
““This is the future! Not AI pretending to know your data, but AI that uses your real data securely, and shows its work.” ”
Final Takeaway: Carpe Diem, Not ChatGPT
Jonathan closed with an important reminder — don’t look for machines to make decisions that belong to humans.
““Seize the day with the tools at hand. You might find you have a lot more time in your schedule.” ”
Want to See It in Action?
Metopio’s platform puts these ideas into practice, helping local health departments and hospitals streamline their CHAs and CHIPs while staying grounded in real, local data.
Schedule a demo to learn more about how your team can put AI to work with the right guardrails, frameworks, and focus.