Family Medicine Residency Learning Networks

A family medicine residency learning network comprises multiple family medicine residency programs working together to accomplish mutually agreed upon objectives and obtain or create new knowledge. This page includes resources to help learning network leaders create or improve their networks.

A family medicine residency learning network comprises multiple family medicine residency programs working together to accomplish mutually agreed upon objectives and obtain or create new knowledge. Some networks are time-limited—they are formed implement a specific project— and others are enduring.STFM’s Residency Learning Network initiative was supported by a grant from the ABFM Foundation.

Resources Available From STFM

Aggregated Resources

Miscellaneous Resources
Papers on Residency Learning Networks
Papers Specific to the I3 Collaborative

Miscellaneous Resources

Graduates of STFM Residency Learning Network Leadership Training

2024 Graduates

The following successfully completed the 2024 Leadership Training for Residency Learning Networks:

  • Angela Cherry, MD, MBA, West Virginia University Rural Family Medicine Residency
  • Barbara Miller, MD, KCU-GMEC/Freeman Program
  • Chelsea Kolodziej, DO, Marion General Health Family Medicine Residency
  • Emilio Russo, MD, LSU Rural Family Medicine Bogalusa
  • James Chris Rule, LCSW, Baptist Health - UAMS Family Medicine Residency
  • Jason Lanham, MD, MA, Medical College of GA at Augusta Univ
  • Jennifer Svarverud, DO, University of Wisconsin Madison
  • Kathleen Young, PhD, Novant Health New Hanover Family Medicine Residency
  • Kathy Pabst, MBA, Missouri Academy of Family Physicians
  • Kelvin Wynn, MD, UICOMP Family Medicine Residency at Carle Health Methodist
  • Lauren Anderson, PhD, Rush-Esperanza Family Medicine Residency
  • Lauren Gibson-Oliver, MD, University of Arkansas for Medical Sciences Little Rock
  • Meggan Robinson, DO, Ascension Genesys Family Medicine Residency
  • Melissa Stephens MD, MS, East Central Mississippi Health Network Inc.
  • Michelle Keating, DO, Wake Forest University School of Medicine Family Medicine Residency- Atrium Health Wake Forest Baptist
  • Roger Garvin, MD, Oregon Health and Science University.
  • Soumya Sridhar, MBBS, MSc, University of Rochester-Highland Family Medicine Residency Program
  • Tana Chongsuwat, MD, McGaw Northwestern University
  • Victor Pulido, DO, Marian Regional Medical Center
  • William Bowen, MD, Medicos de El Centro
  • Zaiba Jetpuri, DO, UT Southwestern Family & Community Medicine

2023 Graduates

The following successfully completed the 2023 Leadership Training for Residency Learning Networks:

  • Tanya Anim, MD, Mercy Health Janesville
  • Jamila Benn, MD, Hawaii Island Family Medicine Residency Program
  • Karl Clebak, MD, MHA, Penn State Health- Milton S. Hershey Medical Center- Hershey
  • Nikola Conrad MD, Indiana University School of Medicine Family Medicine Residency at Memorial Hospital in Jasper
  • Y Monique Davis-Smith, MD, Atrium Health Navicent
  • Andrew Gaillardetz, MD, SLU Southwest Illinois Family Medicine Residency Program
  • Richard Guthmann, MD, Advocate Illinois Masonic Family Medicine Residency
  • Drew Keister, MD, Lehigh Valley Health Network
  • Robert Langan, MD, St. Luke's Family Medicine Residency/Sacred Heart Campus
  • Donna Kaminski, DO, MPH, Rutgers Robert Wood Johnson Somerset Family Practice Family Medicine Residency Program
  • Alex Kipp, MD, UC Irvine Family Medicine
  • Zach Merten, MD, UMN Methodist Hospital Family Medicine Residency Program
  • Michael Partin, MD, Penn State Health Milton S. Hershey Medical Center Family and Community Medicine Residency
  • Patty Pinanong, MD, Keck USC Family Medicine
  • Molly Polverento, MSEd, CPH, Michigan State University Department of Family Medicine Residency Network
  • David Lee Rebedew, MD, Mercy Health Janesville
  • Morgan Rhodes, PharmD, Prisma Health/USC Family Medicine Residency (Columbia)
  • Doug Rose, MD, MBA, Hawaii Island Family Medicine Residency
  • Tiffani Thomas, MD, Aiken Regional Medical Center
  • Kelly Ussery-Kronhaus, MD, Hackensack Meridian Ocean University Medical Center
  • Ryan Wallace, MD, MPH, Alaska Family Medicine Residency

STFM Family Medicine Learning Networks Team

  • Corey Lyon, DO, Program Director, University of Colorado Family Medicine Residency Program
  • Mary Theobald, MBA, Chief of Strategy and Innovation, Society of Teachers of Family Medicine

Questions?

If you have questions about Family Medicine Residency Learning Networks or the resources in this section, contact Mary Theobald at the email link below.

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Tips for Using STFM's AI Assistant

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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Identify the Subject Clearly: Clearly state the subject or area you need information about.

Example:

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.

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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.

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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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While the AI Chat Assistant is a helpful tool, it can still produce inaccurate or incomplete responses. Always verify critical information with reliable sources or colleagues before taking action.

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STFM AI Assistant
Disclaimer: The STFM Assistant can make mistakes. Check important information.