EM Patient Care Innovation & News

  • The Human Touch in the Age of AI

    Christian Rose, MD, director of the Missingness in Action conference on missing data discusses the possibilities and pitfalls in AI automation and eavesdropping.

  • Complex Care Plans for Frequent ED Visitors

    A pilot program targeting frequent ED visitors has reduced ED recidivism and inpatient admissions and saved $710,000 in the first six months while enhancing care pathways.

  • Stanford’s Pediatric ED Expansion: A Strategic Response to Escalating Needs

    Stanford’s Pediatric Emergency Department (ED) has recently completed the final phase of development, growing capacity from 18 to 25 beds. The increase not only positions the department as a regional leader in pediatric emergency care but also reflects a strategic response to the increasing demand for specialized pediatric services.

  • Strategically Planning for the Future

    Dr. Matthew Strehlow, Executive Vice Chair, explores how the Stanford Emergency Medicine integrated strategic plan unites the expertise of the School of Medicine (the university side) and the Emergency Medicine Service Line from Stanford Health Care (the clinical side) in a collaborative and concerted effort to transform healthcare for all.

  • Critical Care Above the Clouds

    Alfredo Urdaneta, MD, guides the medical care for Stanford Life Flight transport, where in-flight, in-air conditions present unique challenges.

  • 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.

  • The Future of Emergency Medicine

    Stanford Department of Emergency Medicine Chair Dr. Andra Blomkalns shares insight on the future of the specialty and the opportunities to lead innovation throughout medicine.

  • 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.

  • 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.