Artificial Intelligence in Emergency Medicine: Viewpoint of Current Applications and Foreseeable Opportunities and Challenges

Abstract

Emergency medicine and its services have reached a breaking point during the COVID-19 pandemic. This pandemic has highlighted the failures of a system that needs to be reconsidered, and novel approaches need to be considered. Artificial intelligence (AI) has matured to the point where it is poised to fundamentally transform health care, and applications within the emergency field are particularly promising. In this viewpoint, we first attempt to depict the landscape of AI-based applications currently in use in the daily emergency field. We review the existing AI systems; their algorithms; and their derivation, validation, and impact studies. We also propose future directions and perspectives. Second, we examine the ethics and risk specificities of the use of AI in the emergency field.

Considering Burnout and Well-Being: Emergency Medicine Resident Shift Scheduling Platform and Satisfaction Insights from a Quality Improvement Project

“…Although scheduler and scheduler-perceived resident satisfaction appear to be average overall, other programs—including those incorporating scheduling software—described issues with learning curves and meeting complex program-specific needs even after meeting with software representatives for scheduling optimization. This echoes our program’s experience and suggests that baseline scheduling software offerings can be improved and may be an underappreciated target for emerging artificial intelligence technology applications in emergency medicine [ 12 ]. Such technology may help to mitigate the administrative burden on chief resident schedulers while also mitigating the drop in resident schedule satisfaction that happens yearly in our program and possibly in other programs across the nation.…”

Infrared Thermal Imaging Analysis in Screening for Toddler’s Fracture: A Proof-of-Concept Study

“…In follow-on studies, this would be considered. Artificial intelligence methods relevant to ED practice [31][32][33] will also be explored in more detail.…”

Specialty grand challenge: emergency health services

“…These advances have the potential to not only increase efficiency and reduce staff burden (like documentation) but also increase the risk of errors, bias, and overreliance on technology to deliver care (34). These risks are all the greater in the time-intensive emergency health services setting (35)(36)(37).…”