EM Patient Care Innovation & News
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Precision Emergency Medicine: Crafting a New Approach
The 2023 Society for Academic Emergency Medicine Consensus Conference on Precision Emergency Medicine, led by Stanford Department of Emergency Medicine, resulted in two groundbreaking publications that can help create a path for a new paradigm in emergency medicine.
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Breaking the Virtual Care Barrier
Stanford’s Virtual Visit Track (VVT) in the emergency department revolutionizes patient care, enabling remote consultation by board-certified emergency medicine physicians, resulting in shorter stays, satisfied patients, and fewer return visits.
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Turning Case Review Inside Out
Stanford Hospital’s Marc and Laura Andreessen Emergency Department (ED) uses a unique case review process that has led to elevated patient care and improved physician satisfaction and trust.
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Quality, Equity, and AI in Emergency Cardiac Care
Maame Yaa (Maya) Yiadom, MD and a team of emergency medicine physician-researchers tested an AI model against human practice in identifying patients with acute coronary syndrome (ACS). Their findings emphasize the disparities in age-based ACS screening and highlight the delicate interplay between human expertise and AI algorithms in the pursuit of precision emergency care.
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Sepsis Test Results in Hours, Not Days
Samuel Yang, MD, associate professor of emergency medicine, is accelerating the diagnosis of bloodstream infections, including a novel approach to quickly determine the susceptibility of bacterial pathogens to antibiotics.
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Reading People's Faces
Stanford is exploring if a video algorithm can predict hospital admission likelihood by assessing patients’ visual cues, in a project co-led by Ryan Ribeira, MD, site principal investigator.
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Predicting Falls After Discharge from the ED
For America’s aging population, preventing falls is crucial for maintaining independence in their golden years. Brian Suffoletto, MD, and his team are using AI and digital technology to predict and prevent falls in older patients after leaving the emergency department (ED).
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Precision Cardiac Care
Kenton Anderson, MD, and a national collaborative of transesophageal echocardiography (TEE) experts pioneer the use of TEE during cardiac arrest, providing real-time images of the heart’s aortic valve.
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Operation AI
Dev Dash, MD, aims to reshape emergency medicine operations through the use of large language models for admissions assessment, critical care cohorting, and more.
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Transforming Patient Monitoring with Machine Learning
David Kim, MD, PhD and his team are developing software that synthesizes data from electronic health records and physiologic monitors in real-time to provide more specific and accurate information about a patient’s physiology during an emergency department (ED) visit.
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How to Evaluate the Ethics of AI
A study led by Christian Rose, MD, and Jennifer Newberry, MD, JD explores the techno-ethical complexities of applying precision medicine in the volatile emergency care environment.
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Using AI to Save Lives in Rural Alaska
Brian Rice, MD, uses machine learning to analyze medevac utilization in remote areas of Alaska where air transport is the lifeline for emergencies.
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Improving Care for Mothers Around the Globe
In a global effort to increase access to quality emergency care for mothers and newborns, Peter Acker, MD an associate professor of emergency medicine is helping to improve emergency referrals.
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Emergency Care Post-Dobbs
Monica R. Saxena, MD, JD, assistant professor of emergency medicine, developed a protocol to offer medication abortions to patients in the Stanford Hospital emergency department (ED), in collaboration with Carl Preiksaitis, MD, emergency medicine fellow, and Andrea Henkel, MD, MS, assistant professor and complex family planning subspecialist in the Department of Obstetrics & Gynecology.
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Emergency Care for Patients with Dementia
Michelle Lin, MD, MPH, MS, an advocate for comprehensive geriatric care, investigates the accessibility and impact of geriatric emergency departments, aiming to bridge the gap for marginalized populations.
