Same Patient, Same Space, Divergent Needs: Revealing Gaps and Design Opportunities in Surgeon–Anesthesiologist Collaboration

要旨

Effective communication and teamwork are vital in high-stakes environments such as the operating room, where timely and accurate information exchange directly affects patient safety and surgical outcomes. Among intraoperative interactions, the collaboration between the surgeon and anesthesiologist is especially critical for maintaining smooth workflows and preventing adverse events. Despite its importance, little HCI research has explicitly examined the unique needs of this dyad or how AI-driven supportive systems might be designed to address them. In this work, we present a qualitative study of surgeon–anesthesiologist collaboration, drawing on focus groups with both specialties and in-situ observations of 45 surgeries spanning open, laparoscopic, and robotic procedures. Our findings uncover key challenges, unmet needs, and coordination breakdowns that shape this relationship. Based on these insights, we conceptualize a systems design to better support intraoperative collaboration.

著者
Hamraz Javaheri
Embedded Intelligence, Kaiserslautern, Germany
Omid Ghamarnejad
Allgemein-, Viszeral und Thoraxchirurgie, Chirurgische Onkologie, Klinikum Saarbrücken, Saarbrücken , Germany
PD Dr. Konrad Schwarzkopf
Klinikum Saarbrücken, Saarbrücken, Germany
Jakob Karolus
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany
Gregor A. Stavrou
Klinikum Saarbrücken gGmbH, Saarbrücken, Germany
Paul Lukowicz
German Research Center for Artificial Intelligence (DFKI), Kaiserslautern, Germany

会議: CHI 2026

ACM CHI Conference on Human Factors in Computing Systems

セッション: Health Tools and Technologies

P1 - Room 129
7 件の発表
2026-04-16 18:00:00
2026-04-16 19:30:00