POCUS Program Participants

See a list of current participants and graduates of the STFM Family Medicine POCUS Educator's Certificate Program. Graduates have 1 year to complete the program requirements and pass the assessment.

POCUS Educator's Certificate Program Graduates by Year

2025–2026 Graduates
2024–2025 Graduates

2025–2026 Graduates

  • Sumaya Abed, MD, University of Alabama Birmingham Cahaba-Highlands FMR Program
  • R. Eugene Bailey, MD, SUNY Upstate FMR Program, Syracuse, NY
  • Jennifer Bamford, MD, University of Vermont FMR, Burlington, VT
  • Jacob Castiglia, MD, University of Rochester Highland Hospital, Rochester, NY
  • Mark Cohee, MD, Forbes Family Medicine, Monroeville, PA
  • Chelsea Cole, MD, University of Texas Southwestern Family and Community Medicine, Dallas, TX
  • Tatiana Cordova, MD, University of Texas Health San Antonio FMR Program
  • Jessica Douglas, MD, University of Mississippi Medical Center Family Medicine, Jackson, MS
  • Chelsea Forrester, DO, Hamilton Medical Center FMR, Dalton, GA
  • Chris Galletti, MD, East Tennessee State University Kingsport FMR Program, Johnson City, TN
  • Mario Garcia, DO, Baptist Memorial Hospital—Memphis FMR, Memphis, TN
  • Stephen Gipson, DO, Onvida Health FMR, Yuma, AZ
  • Michael Gonzales, MD, Kaiser Permanente Washington FMR, Seattle, WA
  • Bradley Green, MD, Gadsden Regional Medical Center FMR Program, Gadsden, AL
  • Elizabeth Harpster, MD, Seneca FMR—Prisma Health, Senera, SC
  • Christopher Heron, MD, Penn State Health Family & Community Medicine Residency at Mount Nittany Medical Center, State College, PA
  • Bianca Lambert, MD, Montefiore Family and Social Medicine Program, Bronx, NY
  • Alegria Lim, DO, Kaiser Permanente San Jose FMR Program, San Jose, CA
  • Stacey Lockard, MD, Franciscan Health Indianapolis FMR, Indianapolis, IN
  • Marina MacNamara, MD, MPH, Mountain Area Health Education Center—Asheville, North Carolina
  • Jeffrey Magnatta, DO, Munson Family Practice, Traverse City, MI
  • Steve Mow, MD, East Carolina University Family Medicine, Greenville, NC
  • Colbert Nelson, DO, MPH, CAQ-SM, Oklahoma University HSC Family and Preventative Medicine Residency Program, Oklahoma City, OK
  • Laura Nietfeld, MD, CHRISTUS Health/Texas A&M College of Medicine FMR San Antonio, TX
  • Ryan Poland, MD, Northern Colorado Medical Center, Greeley, CO
  • Jaydon Polant-Kiernan, Morristown Medical Center FMR, Morristown, NJ
  • Roxanne Radi, MD, The University of Colorado FMR, Aurora, CO
  • Priyanka Rajput, Digital Health—St Joseph Medical Center Stockton, California
  • Arie Rennert, MD, Atlantic Health System—Morristown FMR, Morristown, NJ
  • Wesley Roten, MD, University of North Carolina, Chapel Hill, NC
  • Andrew Shadrach, MD, McLaren Bay Region FMR, Bay City, MI
  • Ryan Stolakis, MD, WellSpan York Hospital FMR, York, PA
  • Allison Strauss, MD, University of Colorado FMR, Aurora, CO
  • Tyler Thorson, MD, FMR of Western Montana, Missoula, MT
  • Meghan Veno, MD, MedStar/Georgetown FMR Program, Washington, D.C.
  • Theresa Yurkonis, DO, Penn State Health St. Joseph's Family and Community Medicine Residency, Reading, PA

2024–2025 Graduates

  • Haider Attarwala, DO, Advocate Lutheran General FMRP
  • Laura Brusky, MD, All Saints Family Medicine Residency Program
  • Erin Cathcart, MD, UMass Worcester Family Medicine Residency
  • Paul Chenowith, DO, Summa Health Family Medicine Residency Program, Akron City Hospital
  • Daniel Frasca, DO, VCU / Riverside Family Medicine Residency
  • Salla Hennessy, MD, Morehouse School of Medicine Dominican Hospital Family Medicine Residency Program in Santa Cruz, California
  • Raymond Hunt, MD, Cahaba + UAB Family Medicine Residency Highlands
  • Adiba Khan, MD, McGaw Northwestern Family Medicine Residency at Lake Forest
  • Michael Lam, MD, Lakeland Regional Health Family Medicine Residency
  • Chase Ledbetter, DO, In His Image Family Medicine Residency Program
  • Elizabeth Lorick, MD, University of Connecticut/ St. Francis Hospital Family Medicine Residency Program
  • Donnie Ours, DO, Washington Health System Family Medicine Residency
  • Cristina Rabaza, MD, University of Colorado Family Medicine Residency Program
  • Kiran Rayalam, MD, CAQGM, Geisinger Lewistown Rural Family Medicine Residency
  • Sarah Tiggelaar, MD, CLC, University of Rochester Family Medicine Residency
  • Alice Tin, MD, MPH, Swedish Cherry Hill Family Medicine Residency
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AI Chatbot Tips

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.

2. Use Specific Terms

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.

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.

Double Check Important Information

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.

Technical Limitations

The Chat Assistant:

  • Cannot access external websites or open links
  • Cannot process or view images
  • Cannot make changes to STFM systems or process transactions
  • Cannot access real-time information (like your STFM Member Profile information)

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