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STFM Accepting Comments on Draft Framework for Family Medicine Artificial Intelligence Centers of Excellence

September 3, 2025—The Society of Teachers of Family Medicine’s Artificial Intelligence (AI) in Medical Education Task Force, in collaboration with the Association of Departments of Family Medicine and Stanford Medicine's Healthcare AI Applied Research Team, is developing a Family Medicine AI Centers of Excellence recognition program, integrating clinical care, education, and research to advance innovation, equity, and impact. This project is being funded by the American Board of Family Medicine Foundation.

STFM is now accepting feedback on a draft framework for AI Centers of Excellence. Now is the opportunity to share your thoughts and provide insights to shape future iterations and ensure it reflects the diverse needs of family medicine.


Submit Your Comments Here

Creation of the Artificial Intelligence Centers of Excellence (CoE) Draft Framework

After a collaborative and iterative process shaped by landscape scans, feedback cycles, and work sessions, the STFM AI Task Force developed the draft CoE framework with the following five foundations:

  1. 5 C’s of primary care: First contact, comprehensiveness, continuity, coordination, and community
  2. Quintuple Aim: Patient experience, population health, cost of care, care team well-being, and health equity
  3. 3 pillars of academic family medicine: Clinical care, education, and research;
  4. Leading models from existing health care and industry CoEs
  5. Insights from family medicine leaders working at the intersection of AI, innovation, and care delivery

The draft framework is organized into four domains:

  1. Purpose: A unifying mission to advance the Quintuple Aim through responsible use of AI
  2. Core Functions: Clinical transformation, education and workforce development, research, and evaluation
  3. Enabling Conditions: Infrastructure, process, people, and culture
  4. Illustrative Activities: Governance, funding, talent development, IT optimization, data access, community and provider engagement, and partnerships

More About the Family Medicine Artificial Intelligence Centers of Excellence Initiative

Happening concurrently with the open comment period on the draft framework is a nationwide environmental scan, engaging 20–30 family medicine departments to gather insights on their AI infrastructure and integration. Departments were selected for this scan based on their diversity in geography and populations served. STFM welcomes additional departments and programs to be interviewed for the environmental scan.

In 2027, a national Family Medicine AI CoE Summit will introduce the first cohort of COEs and launch a Family Medicine AI Collaborative. This collaborative will support shared learning, mentorship, and sustained engagement in service to all of family medicine.

The project timeline is below:

  1. July 2025–January 2026: Draft Framework Publication and Environmental Scan
  2. February 2026–May 2027: Framework Refinement and Dissemination
  3. May 2027–June 2027: National Centers of Excellence Summit
  4. June 2027: Centers of Excellence Network Launch
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STFM's AI Assistant is designed to help you find information and answers about Family Medicine education. While it's a powerful tool, getting the best results depends on how you phrase your questions. Here's how to make the most of your interactions:

1. Avoid Ambiguous Language

Be Clear and Specific: Use precise terms and avoid vague words like "it" or "that" without clear references.

Example:

Instead of: "Can you help me with that?"
Try: "Can you help me update our Family Medicine clerkship curriculum?"
Why this is important: Ambiguous language can confuse the AI, leading to irrelevant or unclear responses. Clear references help the chatbot understand exactly what you're asking.

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Instead of: "What resources does STFM provide?"
Try: "I'm a new program coordinator for a Family Medicine clerkship. What STFM resources are available to help me design or update clerkship curricula?"
Why this is better: Providing details about your role ("program coordinator") and your goal ("design or update clerkship curricula") gives the chatbot enough context to offer more targeted information.

3. Don't Assume the AI Knows Everything

Provide Necessary Details:The STFM AI Assistant has been trained on STFM's business and resources. The AI can only use the information you provide or that it has been trained on.

Example:

Instead of: "How can I improve my program?"
Try: "As a program coordinator for a Family Medicine clerkship, what resources does STFM provide to help me improve student engagement and learning outcomes?"
Why this is important: Including relevant details helps the AI understand your specific situation, leading to more accurate and useful responses.

4. Reset if You Change Topics

Clear Chat History When Switching Topics:

If you move to a completely new topic and the chatbot doesn't recognize the change, click the Clear Chat History button and restate your question.
Note: Clearing your chat history removes all previous context from the chatbot's memory.
Why this is important: Resetting ensures the AI does not carry over irrelevant information, which could lead to confusion or inaccurate answers.

5. Provide Enough Context

Include Background Information: The more context you provide, the better the chatbot can understand and respond to your question.

Example:

Instead of: "What are the best practices?"
Try: "In the context of Family Medicine education, what are the best practices for integrating clinical simulations into the curriculum?"
Why this is important: Specific goals, constraints, or preferences allow the AI to tailor its responses to your unique needs.

6. Ask One Question at a Time

Break Down Complex Queries: If you have multiple questions, ask them separately.

Example:

Instead of: "What are the requirements for faculty development, how do I register for conferences, and what grants are available?"
Try: Start with "What are the faculty development requirements for Family Medicine educators?" Then follow up with your other questions after receiving the response.
Why this is important: This approach ensures each question gets full attention and a complete answer.

Examples of Good vs. Bad Prompts

Bad Prompt

"What type of membership is best for me?"

Why it's bad: The AI Chat Assistant has no information about your background or needs.

Good Prompt

"I'm the chair of the Department of Family Medicine at a major university, and I plan to retire next year. I'd like to stay involved with Family Medicine education. What type of membership is best for me?"

Why it's good: The AI Chat Assistant knows your role, your future plans, and your interest in staying involved, enabling it to provide more relevant advice.

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