Using instant messaging applications for consultations in the emergency department: A cross-sectional survey.

Abstract

This study investigates how consultants and consultees use Instant Messaging Applications (IMAs) during Emergency Department (ED) consultations, examining their attitudes toward these tools and assessing perceptions of existing consultation methods and the perceived need for system improvements. A cross-sectional study was conducted among clinicians involved in Emergency Department consultations at the American University of Beirut Medical Center, Lebanon. Participants completed an online questionnaire assessing their demographics, consultation patterns, IMAs usage, and opinions on consultation modalities. The recruitment period was from 13/11/2023-08/11/2024. A total of 120 participants were included (65 consultants, 55 consultees). Consultants were significantly older than consultees (28.7 ± 3.4 vs. 26.6 ± 1.91 years, p < 0.001). While all consultees were residents, 64.6% of consultants were residents and 35.4% were fellows (p < 0.001). All participants reported using smartphones when on call (100%). IMAs were the most preferred consultation method overall (48.3%), followed by smartphone calls (32.5%). Consultants favored smartphone calls significantly more than consultees (49.2% vs. 12.7%, p < 0.001), whereas consultees preferred workstation phone calls (30.9% vs. 0%, p < 0.001). WhatsApp was the dominant IMA used (98.9%). During night shifts, consultants demonstrated a significantly greater reliance on smartphone calls than consultees (84.6% vs. 63.6%, p = 0.008). IMAs were among the most frequently used methods during both day and night calls (80% vs. 65.2%), and two-thirds of participants (63.7%) reported concerns regarding legal implications and the need for improved consultation tools. The findings highlight the need for structured and secure digital solutions to optimize communication between healthcare teams. With IMAs increasingly embedded in ED consultations, future work should focus on developing dedicated and potentially AI-supported platforms that enhance efficiency, documentation, and data security in clinical communication.