EM Technology and AI Innovation & News

  • 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.

  • 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.

  • 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.

  • 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.

  • 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.

  • 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).

  • 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.

  • 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.

  • What Digital Health Tells Us About Disease

    Christine Ngaruiya, MD, uses Natural Language Processing to uncover gender disparities in noncommunicable diseases, while also leading initiatives at the intersection of health and climate change, fostering targeted interventions and policy changes worldwide.

  • 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.

  • 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.

  • 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.

  • How digital tools are heading off alcohol-related health problems

    Brian Suffoletto, MD, associate professor of emergency medicine, views interactions with patients in the Emergency Department as valuable opportunities to identify specific risks and then facilitate positive behavior changes post-ED discharge using digital devices.

  • Harnessing Data to Improve Emergency Care

    The Emergency Department Data Analytics Committee (EDAC) is employing informatics to improve care delivery through research, quality monitoring, and machine learning. Comprised of emergency medicine physicians with informatics expertise, a clinical data architect, and a data analyst, the team guides emergency medicine clinical operations and researchers in utilizing patient data in innovative ways.

  • Innovative Methods for Prevention and Early Treatment of ARDS

    Jennifer Wilson, MD, a clinical assistant professor with Stanford Department of Emergency Medicine, is exploring innovative methods for prevention and early treatment of acute respiratory distress syndrome (ARDS) and sepsis…

  • Profile in Innovation: Pediatric EM Physician Dan Imler, MD

    Daniel Imler, MD of Stanford’s Department of Emergency Medicine was awarded the American Academy of Pediatrics EBSCO Health/DynaMed Plus Award for Technological Innovations in Pediatric Emergency Medicine Award for his work in creating Curbside, an online physicians-first decision optimization tool.

  • Rising to the Challenges of Covid-19 Through Telehealth

    One of Stanford’s first steps toward virtual emergency care was to establish a drive-through alternative care site for COVID-19 testing in 2020, supported by a remote emergency medicine physician.

  • Using Digital Devices to Expand Care Beyond the Emergency Department

    As an associate professor of emergency medicine, Brian Suffoletto, MD sees emergency department (ED) patient encounters as opportunities to identify individuals with specific risks and connect them to effective interventions that help them adopt behavioral changes after they leave the ED.

  • Using Phenotypes to Improve TBI Treatment

    Angela Lumba-Brown, MD, associate professor in Emergency Medicine is defining new best practices for diagnosing and treating traumatic brain injury (TBI), including concussion, using phenotyping.

  • Training Health Care Providers Around the Globe

    Matthew Strehlow, MD helped to develop a free, online, 15-module COVID-19 training now used by more than 120,000 learners in low- to middle-income countries.