Devin Bartlett

NPR, EMS-I

Lead Paramedic Instructor/Paramedic
Yale New Haven Hospital Center for EMS/Branford Fire Department
New Haven, CT

Devin Bartlett is a Nationally Registered Paramedic, EMS Instructor, and educator with the Yale New Haven Hospital Center for EMS in New Haven, Connecticut. After earning her Bachelor of Science in Paramedicine from the University of New Haven in 2018, she began her career as a paramedic serving both urban and suburban EMS systems throughout Connecticut. Driven by a passion for education, Bartlett earned her Connecticut EMS Instructor certification in 2021 and joined the Yale New Haven Hospital Center for EMS faculty. She currently teaches Anatomy & Physiology and Cardiology in the paramedic program, helping prepare the next generation of EMS professionals. In addition to her educational role, Bartlett serves as a paramedic with the Branford Fire Department and as a Research Assistant at Yale University, where she contributes to emergency medicine research and scholarly publications. Her combined experience in clinical practice, education, and research reflects her commitment to advancing prehospital care through evidence-based practice and professional development.

Not a STEMI, Still a Problem: High-Risk ECGs Beyond ST Elevation (Thursday, October 22, 2026 - 4:00-5:15pm)

ST elevation gets all the attention, but other dangerous ECG findings often never trigger a STEMI alert. This class will challenge paramedics to use the 12-lead ECG as more than just a cath lab activation tool.

Participants will explore high-risk, non-STEMI ECG patterns, including occlusion myocardial infarction (OMI), pulmonary embolism, hyperkalemia, genetic conditions, and various toxicities. The session will focus on the underlying pathophysiology, practical ECG interpretation, and field-relevant decision-making to help providers recognize critical findings that may otherwise be missed.

Attendees will gain a broader understanding of how advanced 12-lead interpretation can improve patient assessment, guide treatment decisions, and identify time-sensitive conditions beyond traditional STEMI recognition.