Andrew Napier
Masters Student in Clinical Informatics Management, admitted Summer 2025
Bio
Andrew Napier, MD, FAAEM, is a board-certified emergency physician, Army veteran, and founder working at the boundary of bedside care, medical devices, and clinical AI. He built and FDA-cleared a single-use video laryngoscope with on-blade lens clearing, co-founded an ambient documentation platform used across more than 100 care sites, and now works on real-time procedural guidance for intubation and bronchoscopy.
At Stanford MCiM, his interests include human-in-the-loop guidance for high-risk procedures, ambient clinical assistants that reduce cognitive load, and pragmatic trials that measure speed, accuracy, first-pass success, and downstream outcomes. His focus is whether clinical AI changes care at the bedside when the patient is sick and the clinician has seconds to act.
Previously, he served as Vice Chair and Assistant Medical Director of a 70,000-visit emergency department. He holds issued and pending patents, published on lens-clearing laryngoscopy in AJEM, and served as a combat medic in Afghanistan before practicing emergency medicine at high-acuity trauma centers.
Honors & Awards
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Tillman Military Scholar, Pat Tillman Foundation (2012)
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U.S. Army Awards — Purple Heart; Combat Medical Badge; Combat Action Badge; Valorous Unit Award, United States Army (2008-2009)
Professional Affiliations and Activities
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Fellow, American Academy of Emergency Medicine (FAAEM) (2024 - Present)
Education & Certifications
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Doctor of Medicine, University of South Florida, Doctor of Medicine (MD) (2017)
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Board Certification, American Board of Emergency Medicine
Patents
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Andrew Napier. "United States Patent US 11,103,130; 11,627,873 Disposable Video Laryngoscope with Fluid Spray System"
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Andrew Napier. "United States Patent US 17/547,726 (pending) Laryngoscope and Methods of Use"
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Andrew Napier. "United States Patent US 63/548,015 (provisional) Individualized Physician Clinical Documentation Tools"
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Andrew Napier. "United States Patent US 63/619,785 (provisional) AI-Enhanced Depth Perception and Anatomical Highlighting"
https://orcid.org/0000-0001-9128-4755