Picture this:
A local health department (LHD) in a mid-sized county is juggling a new community health assessment, grant reporting deadlines, and an uptick in flu cases. Traditionally, summarizing dozens of focus group transcripts would take weeks, but with Artificial Intelligence (AI), they generate key themes in under an hour. That time saved means the team can shift focus to launching vaccination campaigns before the flu season peaks. This is just one example of how AI is transforming public health operations and freeing teams to focus on what matters most, community impact.
AI is reshaping local health departments and how they serve communities. From planning to surveillance, AI is helping public health teams work smarter, not harder, allowing teams to focus on strategy and community impact while AI handles routine tasks.
Public health professionals bring something no algorithm can replicate: the ability to interpret community needs, build trust, and design interventions that change lives. AI simply supports that process, helping organize data, summarize feedback, predict trends, and improve decision-making.
AI is helping public health teams work smarter, not harder.
Here are 3 powerful ways AI is making an impact:
1. Streamlining Community Health Assessments (CHAs) and Community Health Improvement Plans (CHIPs)
AI can automate time-consuming tasks like:
- Summarizing focus group transcripts
- Performing analysis on community feedback
- Generating data visualization and drafting narratives
Examples in practice:
- A LHD can use AI to analyze thousands of open-ended survey responses from residents about local health priorities. AI can cluster responses into themes like mental health access and food insecurity, then generate a draft narrative for the CHA report.
- AI-generated dashboards can help visualize community health priorities, making it easier to identify gaps and prioritize interventions.
2. Analyzing Grant Reports and Unstructured Data
AI can process thousands of pages of grant reports and program documentation, extracting insights quickly and accurately. This means better evaluations and smarter resource allocation.
Examples in practice:
- A county health department can use AI to review 500 pages of grant documentation and identify underfunded maternal health programs.
- AI can flag recurring issues in program reports, helping teams address systemic challenges faster and improve program quality.
3. Disease Surveillance and Risk Modeling
AI powered analytics can predict outbreaks and model risk factors, strengthen early warning systems, and guide proactive responses. This is predictive public health in action.
Examples in practice:
- AI models can predict a spike in flu cases two weeks before traditional reporting, allowing the department to launch vaccination campaigns early.
- AI risk modeling can help identify neighborhoods most vulnerable to heat-related illnesses, guiding targeted outreach during a heatwave, reducing heat-related hospitalizations.
AI isn’t replacing public health professionals, it’s empowering them to focus on strategy and community impact, using data-driven decisions.
How PHF Can Help
PHF’s AI and Problem Solving Technical Assistance and Training helps public health organizations navigate the opportunities and challenges of AI by supporting its safe, effective, and strategic use in improving public health practice. Our team helps organizations integrate AI tools into workflows, enhance decision-making, and build capacity for data-driven strategies.
Interested in learning more about PHF’s AI and Problem Solving Services? Contact us at info@phf.org.
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