EMS Research with Professor Bram
Join Bram Duffee, a paramedic and researcher with over 20 years of experience in critical care and 911, as he explores the latest research in emergency medicine and paramedicine. Each episode of "EMS Research with Professor Bram" features an in-depth discussion, as well as an analysis of new studies and their implications for paramedics. As a PhD researcher and paramedic, Bram brings a unique perspective to the podcast. His expertise and experience allow him to break down complex concepts and make them accessible to listeners. Whether you're an experienced paramedic looking to stay up-to-date on the latest research or someone interested in learning more about emergency medicine, "EMS Research with Professor Bram" is the perfect podcast for you.
Host biography: Bram Duffee has authored 2 books on communication. With over two decades of experience as a paramedic (since 1998), his roles have included 911 and critical care, along with operations management for both 911 and private companies. He has taught over 60 university-level courses in Interpersonal Communication, Leadership, Organizational Behavior, and more. He currently serves as a full-time paramedic in Houston and is an Advisory Board Member for the National Association of Medical Emergency Technicians of Portugal. He also holds a research appointment as an Institute for Social Innovation Fellow with Fielding Graduate University.
Refer to links:
http://www.ProfessorBram.com
http://www.youtube.com/@4EMSresearch
https://www.facebook.com/profile.php?id=100087933902422&mibextid=ZbWKwL
https://www.linkedin.com/in/bramduffee
EMS Research with Professor Bram
Can AI Help Paramedics Make Better Decisions?
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Can artificial intelligence tools like ChatGPT help paramedics with differential diagnosis and transport decisions? A groundbreaking new study explores AI's accuracy in prehospital care, offering a glimpse into a future where technology acts as a clinical safety net. Host Bram Duffee, PhD, EMT-P, sits down with lead author Eric D. Miller to discuss his team's fascinating findings. This first-of-its-kind study analyzed 104 real prehospital care records. ChatGPT was tasked with generating the most likely diagnosis, which was then compared to the diagnosis made by the treating paramedic. When the two differed, two emergency physicians reviewed the case to determine the more accurate conclusion.
Key Findings:
• High Accuracy: ChatGPT correctly predicted the diagnosis in approximately 75% of cases.
• Conservative Bias: In 46% of disagreements, the AI identified more critical conditions, suggesting it may help reduce under-triage.
• Strong Safety Profile: In only one case out of 104 did the AI suggest a potentially inappropriate transport decision.
Watch the full interview with Eric D. Miller to understand the nuances of this research. Subscribe for more expert discussions on the future of EMS.
Disclaimer: This content is for educational and informational purposes only and does not constitute medical advice. Always follow your local protocols and medical direction.
Book announcement: Bram Duffee is a co-author of the latest book about how hypnosis has the potential to revolutionize medical care for those struggling with emergency / acute distress. Hypnotic Communication in Emergency Medical Settings: For Life-Saving and Therapeutic Outcomes demonstrates how hypnotic communication has the potential to improve patient outcomes in emergency care, integrating insights on the connection between mind and body for paramedics and other first responders. https://routledge.pub/Hypnotic-Communication-in-Emergency-Medical-Settings
Stay up to date: Review the most recent research in EMS through the monthly article reviews put out by the International PreHospital Medicine Institute https://iphmi.com/ems-articles-of-the-month
Connections: If you want to connect with the EMS Research Podcast staff check out our website at www.ProfessorBram.com If you enjoyed this episode please consider subscribing to EMS Research on YouTube: / @4emsresearch
Reference: Miller, E. D., Franc, J. M., Hertelendy, A. J., Issa, F., Hart, A., Woodward, C. A., Newbury, B., Newbury, K., Mathew, D., Whitten-Chung, K., Bauer, E., Voskanyan, A., & Ciottone, G. R. (2025). Accuracy of commercial large language model (ChatGPT) to predict the diagnosis for prehospital patients suitable for ambulance transport decisions: Diagnostic accuracy study. Prehospital Emergency Care, 29(3), 238–242.