From 911 to Hospital: Challenges and Opportunities for AI Integration in Emergency Medical Services

2026-06-15

AI Summary

Emergency Medical Services (EMS) operate under high-stress conditions and rely on distributed teamwork, rendering existing AI systems poorly suited to their complex workflows. This study addresses this gap by conducting semi-structured interviews with 25 EMS clinicians in the United States, integrating distributed cognition and human-computer interaction theories to systematically identify five key risk dimensions through which AI interventions may disrupt team coordination. Building on these insights, the work proposes five design principles centered on enhancing situational awareness. The research clarifies core EMS requirements for AI systems—particularly regarding reliability, privacy preservation, and contextual sensitivity—and offers an actionable design framework for effective human-AI collaboration in high-stakes clinical environments.

Abstract

Artificial Intelligence (AI) is increasingly introduced into healthcare settings, yet its integration into fast-paced, high-pressure domains such as Emergency Medical Services (EMS) remains limited. EMS work unfolds across distinct stages, each characterized by different information needs, constraints, and forms of collaboration. Designing effective AI support requires understanding how AI interventions align with, or disrupt, EMS work across its different stages. We conducted semi-structured interviews with 25 EMS clinicians across the United States to examine how existing technologies currently support emergency services workflows and how they envision opportunities for, and concerns about, future AI-based support across different stages of emergency response. Our analysis reveals the cognitive, social, and procedural factors that enable EMS team coordination, which is grounded in situational awareness across distributed roles. EMS clinicians expressed significant concerns about how AI integration threatens this coordination mechanism across multiple dimensions: legal and privacy issues, technical reliability, contextual sensitivity, professional autonomy, and workflow friction. We propose five design principles for AI systems that augment distributed cognition and situational awareness, enabling EMS teams to deliver effective care under extreme constraints.

Problem

• Emergency Medical Services
• Artificial Intelligence
• Team Coordination
• Situational Awareness
• AI Integration

Innovation

• Emergency Medical Services
• Artificial Intelligence
• Distributed Cognition
• Situational Awareness
• AI Design Principles