Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Mar 11, 2024
Date Accepted: Oct 31, 2024
A Novel Artificial Intelligence-Enhanced Digital Network for Prehospital Emergency Support: A Community Intervention Study
ABSTRACT
Background:
Efficient emergency patient transport systems—are crucial for delivering timely medical care to individuals in critical situations—are faced by certain challenges. Therefore, CONNECT-AI, a novel digital platform connected network for emergency medical systems using artificial intelligence-based comprehensive technical support for the real-time sharing of medical information at the pre-hospital stage, was introduced.
Objective:
This study aimed to evaluate the effectiveness of this system in reducing patient transfer delays.
Methods:
This was a community-based interventional study in two regions of South Korea. The impact of the system was assessed based on the proportion of patients experiencing transfer delays.
Results:
A total of 14,853 patients transported by public ambulance were finally selected for analysis. Overall, the system’s effect on reducing transport time was not statistically significant. However, for patients with fever or respiratory symptoms, there was a statistically significant reduction of more than 75% of outlier cases in the group using the system (P = 0.009). For patients who received real-time acceptance signals from the hospital, the reduction in the percentage of 75% outliers was statistically significant compared to without the system (P = 0.015).
Conclusions:
The present digital emergency medical system platform offers a novel approach to enhancing emergency patient transport by leveraging AI, real-time information sharing, and decision support. While the system demonstrated improvements for certain patient groups facing transfer challenges, further research and modifications are necessary to fully realize its benefits in diverse healthcare contexts. Clinical Trial: NCT04829279
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