How artificial intelligence could transform emergency care

Authors

Marika M. Kachman, US Acute Care Solutions, Canton, OH, United States of America; Department of Emergency Medicine, Virginia Hospital Center, Arlington, VA, United States of America.
Irina Brennan, US Acute Care Solutions, Canton, OH, United States of America; Department of Emergency Medicine, Inova Alexandria Hospital, Alexandria, VA, United States of America.
Jonathan J. Oskvarek, US Acute Care Solutions, Canton, OH, United States of America; Department of Emergency Medicine, Summa Health, Akron, OH, United States of America.
Tayab Waseem, Department of Emergency Medicine, George Washington University, Washington, DC, United States of America.
Jesse M. Pines, US Acute Care Solutions, Canton, OH, United States of America; Department of Emergency Medicine, George Washington University, Washington, DC, United States of America. Electronic address: pinesj@usacs.com.

Document Type

Journal Article

Publication Date

4-16-2024

Journal

The American journal of emergency medicine

Volume

81

DOI

10.1016/j.ajem.2024.04.024

Keywords

Artificial intelligence; Emergency department; Emergency medicine; Machine learning; Technology; Transformation

Abstract

Artificial intelligence (AI) in healthcare is the ability of a computer to perform tasks typically associated with clinical care (e.g. medical decision-making and documentation). AI will soon be integrated into an increasing number of healthcare applications, including elements of emergency department (ED) care. Here, we describe the basics of AI, various categories of its functions (including machine learning and natural language processing) and review emerging and potential future use-cases for emergency care. For example, AI-assisted symptom checkers could help direct patients to the appropriate setting, models could assist in assigning triage levels, and ambient AI systems could document clinical encounters. AI could also help provide focused summaries of charts, summarize encounters for hand-offs, and create discharge instructions with an appropriate language and reading level. Additional use cases include medical decision making for decision rules, real-time models that predict clinical deterioration or sepsis, and efficient extraction of unstructured data for coding, billing, research, and quality initiatives. We discuss the potential transformative benefits of AI, as well as the concerns regarding its use (e.g. privacy, data accuracy, and the potential for changing the doctor-patient relationship).

APA Citation

Kachman, Marika M.; Brennan, Irina; Oskvarek, Jonathan J.; Waseem, Tayab; and Pines, Jesse M., "How artificial intelligence could transform emergency care" (2024). GW Authored Works. Paper 4717.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/4717

Department

School of Medicine and Health Sciences Resident Works