Introduction: Mass-casualty incidents (MCIs) are events in which many people are injured during the same period of time. This has major implications in regards to practical concerns and planning for both personnel and medical equipment. Smart glasses are modern tools that could help Emergency Medical Services (EMS) in the estimation of the number of potential patients in an MCI. However, currently there is no study regarding the advantage of employing the use of smart glasses in MCIs in Thailand.
Study objective: This study aims to compare the overall accuracy and amount of time used with smart glasses and comparing it to manual counting to assess the number of casualties from the scene.
Methods: This study was a randomized controlled trial, field exercise experimental study in the EMS unit of Srinagarind Hospital, Thailand. The participants were divided into two groups (those with smart glasses and those doing manual counting). On the days of the simulation (February 25 and 26, 2022), the participants in the smart glasses group received a 30-minute training session on the use of the smart glasses. After that, both groups of participants counted the number of casualties on the simulation field independently.
Results: Sixty-eight participants were examined, and in the smart glasses group, a total of 58.8% (N = 20) of the participants were male. The mean age in this group was 39.4 years old. The most experienced in the EMS smart glasses group had worked in this position for four-to-six years (44.1%). The participants in the smart glasses group had the highest scores in accurately assessing the number of casualties being between 21-30 (98.0%) compared with the manual counting group (89.2%). Additionally, the time used for assessing the number of casualties in the smart glasses group was shorter than the manual counting group in tallying the number of casualties between 11-20 (6.3 versus 11.2 seconds; P = .04) and between 21-30 (22.1 versus 44.5 seconds; P = .02).
Conclusion: The use of smart glasses to assess the number of casualties in MCIs when the number of patients is between 11 and 30 is useful in terms of greater accuracy and less time being spent than with manual counting.
Keywords: Emergency Medical Services; artificial intelligence; mass-casualty incidents; prehospital emergency care; smart glasses.