University of Lynchburg DMSc Doctoral Project Assignment Repository
Specialty
Emergency Medicine
Abstract
This article evaluates the use of artificial intelligence (AI) in emergency departments (EDs) to improve workflow and patient outcomes. EDs face persistent overcrowding, prolonged wait times, and increasing clinician workload that negatively affect care delivery. Emerging evidence suggests AI can enhance operational efficiency and clinical decision-making. AI tools demonstrate clinician-level accuracy in triage, diagnosis, and treatment planning, while predictive modeling improves patient prioritization, throughput, and wait times. Additionally, AI reduces administrative burden through support in documentation, billing, coding, and discharge processes, allowing clinicians to focus more on direct patient care. However, barriers to widespread implementation include concerns about diagnostic reliability, legal liability, ethical considerations, and high financial costs. Although AI cannot replace the human elements of emergency medicine, current literature indicates it can meaningfully improve efficiency and clinical performance. Further research is needed to optimize safety, address regulatory and ethical challenges, and develop cost-effective strategies for integration.
Recommended Citation
Geier D. Artificial Intelligence in Emergency Departments: Enhancing Workflow and Patient Outcomes. University of Lynchburg DMSc Doctoral Project Assignment Repository. 2026; 8(1).
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