How artificial intelligence is reshaping the emergency department
Emergency departments (EDs) are under greater pressure than ever. In addition to growing patient volumes, staffing shortages, and rising expectations for the delivery of safe, high-quality care, emergency rooms are a common destination for some of the most vulnerable patients, those transferred from skilled nursing facilities (SNFs) and other post-acute care settings.
Too often, SNF patients bring incomplete or outdated information, leaving clinicians with limited context to make critical decisions. Frontline teams must then find ways to manage higher demands and complexity without compromising results.
As an emergency physician, I see firsthand how a lack of information can slow care, increase costs, and lead to avoidable hospitalizations. But I also see how artificial intelligence (AI) is starting to change that. By filling critical information gaps, AI enables emergency clinicians to act more quickly and with more confidence, thereby improving safety and continuity of care across the care environment.
Bridging the information gap
One of the greatest challenges in acute care involves post-acute transfer. When SNF patients arrive without clear documentation or with lengthy packages that must be manually reviewed, valuable time is wasted. Clinicians are forced to repeat tests or delay treatment to understand why patients are admitted.
Now, AI-enabled tools can quickly extract and summarize the most relevant details from a patient’s recent hospitalization, such as vital signs, new diagnoses, changes in condition, or treatments performed within the past 24 hours. Often within seconds, the emergency room team knows why the patient was transferred, what was done and what needs to be done next. This structured, real-time insight helps determine if hospitalization is necessary or if the patient can be safely stabilized and returned to the hospital.
The AI model is built on some of the largest post-acute data sets in North America, providing a comprehensive view of a patient's history that is also timely, often until the moment the patient is transported. Integrating this intelligence directly into existing ED workflows eliminates the need to log into separate systems or sift through the thick forms, reports and other documents patients typically carry. Teams can immediately act on information displayed in existing electronic health record screens, supporting faster, evidence-based decision-making.
Improve efficiency and value-based care
When used responsibly, AI can help health systems achieve measurable gains in efficiency and quality. It can shorten emergency room stays, reduce unnecessary admissions, and identify patients at highest risk for readmission. Targeted care plans developed in the emergency department can also safely redirect frequently used patients to more appropriate outpatient resources, improving patient flow and preserving the ability to respond to true emergencies.
Just as importantly, AI can enhance staff and patient safety. Real-time alerts on behavioral or clinical risks enable teams to prepare before patient contact. This advance notification helps reduce workplace accidents and improves bedside confidence. By replacing uncertainty with actionable insights, clinicians can experience less stress and greater satisfaction, benefits that spill over to patient care.
The ability to avoid unnecessary admissions and redundant diagnoses also supports the shift to value-based care. That’s because having accurate, contextual information at the point of care allows for faster, more confident decisions, ensuring patients receive the right level of care in the right environment.
This drives financial sustainability and continuity of care, resulting in a safer patient experience and more efficient use of resources for providers and payers.
Create a continuum of interconnectedness
Yet even with these improvements, hospital clinicians remain wary of embedding new AI technologies deeply into clinical workflows. That’s why transparency of data and advice is crucial. After all, these tools should highlight what matters most, not replace human judgment, and clinicians should be able to trace every insight back to its original documentation.
Likewise, a responsible AI framework should emphasize fairness, accountability, and privacy. Models should perform equitably across diverse patient populations, and strict data governance must ensure patient information is protected. When these safeguards are deployed, AI can enhance clinical confidence rather than causing additional concerns.
Ultimately, the promise of AI in the emergency department goes beyond operational efficiency. We are building a more connected system that bridges the acute and post-acute settings by integrating insights across the continuum. These insights empower clinicians to get the information they need, when they need it, enabling faster, safer, more person-centered care.
Emergency departments will continue to face increasing demands and complexity. Yet we are already seeing that the responsible use of AI offers meaningful opportunities for critical care teams. Additionally, AI can help place the emergency department anywhere as a central hub for coordinated, safe and efficient patient transitions across the continuum of care.
Photo: pablohart, Getty Images
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