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Review
. 2024 Jan 27;12(1):e22.
doi: 10.22037/aaem.v12i1.2110. eCollection 2024.

Artificial Intelligence in Optimizing the Functioning of Emergency Departments; a Systematic Review of Current Solutions

Szymczyk Aleksandra  1 , Krion Robert  1 , Krzyzaniak Klaudia  1 , Lubian Dawid  1 , Sieminski Mariusz  1
Affiliations
Review

Artificial Intelligence in Optimizing the Functioning of Emergency Departments; a Systematic Review of Current Solutions

Szymczyk Aleksandra et al. Arch Acad Emerg Med. .

Abstract

Introduction: The burgeoning burden on emergency departments is a global challenge that we have been confronting for many years. Emerging artificial intelligence (AI)-based solutions may constitute a critical component in the optimization of these units. This systematic review was conducted to thoroughly examine and summarize the currently available AI solutions, assess potential benefits from their implementation, and identify anticipated directions of further development in this fascinating and rapidly evolving field.

Methods: This systematic review utilized data compiled from three key scientific databases: PubMed (2045 publications), Scopus (877 publications), and Web of Science (2495 publications). After meticulous removal of duplicates, we conducted a detailed analysis of 2052 articles, including 147 full-text papers. From these, we selected 51 of the most pertinent and representative publications for the review.

Results: Overall the present research indicates that due to high accuracy and sensitivity of machine learning (ML) models it's reasonable to use AI in support of doctors as it can show them the potential diagnosis, which could save time and resources. However, AI-generated diagnoses should be verified by a doctor as AI is not infallible.

Conclusions: Currently available AI algorithms are capable of analysing complex medical data with unprecedented precision and speed. Despite AI's vast potential, it is still a nascent technology that is often perceived as complicated and challenging to implement. We propose that a pivotal point in effectively harnessing this technology is the close collaboration between medical professionals and AI experts. Future research should focus on further refining AI algorithms, performing comprehensive validation, and introducing suitable legal regulations and standard procedures, thereby fully leveraging the potential of AI to enhance the quality and efficiency of healthcare delivery.

Keywords: Artificial intelligence; Emergency medicine; Emergency service; Machine learning; hospital.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Method of article selection
Figure 2
Figure 2
PICO framework of the study
Figure 3
Figure 3
Forest plot for sensitivity of included studies
See this image and copyright information in PMC

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References

    1. Mueller B, Street WN, Carnahan RM, Lee S. Evaluating the performance of machine learning methods for risk estimation of delirium in patients hospitalized from the emergency department. Acta Psychiatr Scand. 2023;147(5):493–505. - PMC - PubMed
    1. Badal K, Lee CM, Esserman LJ. Guiding principles for the responsible development of artificial intelligence tools for healthcare. Commun Med (Lond). 2023;3(1):47. - PMC - PubMed
    1. Chang H, Cha WC. Artificial intelligence decision points in an emergency department. Clin Exp Emerg Med. 2022;9(3):165–8. - PMC - PubMed
    1. Hunter OF, Perry F, Salehi M, Bandurski H, Hubbard A, Ball CG, Morad Hameed S. Science fiction or clinical reality: a review of the applications of artificial intelligence along the continuum of trauma care. World J Emerg Surg. 2023;18(1):16. - PMC - PubMed
    1. Grant K, McParland A, Mehta S, Ackery AD. Artificial Intelligence in Emergency Medicine: Surmountable Barriers With Revolutionary Potential. Ann Emerg Med. 2020;75(6):721–6. - PubMed

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