Accepted for/Published in: JMIR XR and Spatial Computing (JMXR)
Date Submitted: Sep 7, 2024
Open Peer Review Period: Sep 9, 2024 - Oct 2, 2024
Date Accepted: Nov 27, 2024
(closed for review but you can still tweet)
Applications of Augmented Reality for Pre-hospital Emergency Care: A Systematic Review of Randomized Controlled Trials
ABSTRACT
Background:
Delivering high-quality prehospital emergency care remains challenging, especially in resource-limited settings where real-time clinical decision support (CDS) is limited. Augmented reality (AR) has emerged as a promising healthcare technology, offering potential solutions to enhance decision-making, care processes, and EMS training.
Objective:
This systematic review assesses the effectiveness of AR in improving clinical decision-making, care delivery, and educational outcomes for EMS providers.
Methods:
We searched databases including PubMed, Cochrane CENTRAL, Web of Science, IEEE, Embase, PsycInfo, and ACM. Studies were selected based on their focus on AR in prehospital care. Fourteen randomized controlled trials (RCTs) were selected from an initial screening of 2081 manuscripts. Included studies focused on AR use by EMS personnel, examining clinical and educational impacts. Data such as study demographics, intervention type, outcomes, and methodologies were extracted using a standardized form. Primary outcomes assessed included clinical task accuracy, response times, and training efficacy. A narrative synthesis was conducted, with bias evaluated using Cochrane's Risk of Bias Tool. Improvements in AR-assisted interventions and their limitations were analyzed.
Results:
AR significantly improved clinical decision-making accuracy and EMS training outcomes, reducing response times in simulations and real-world applications. However, small sample sizes and challenges in integrating AR into workflows limit the generalizability of the findings.
Conclusions:
AR holds promise for transforming prehospital care by enhancing real-time decision-making and EMS training. Future research should address technological integration and scalability to fully realize AR’s potential in EMS. This review was supported by the Stepping Strong Center for Trauma Innovation, Harvard Medical School.
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Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.