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A Pilot Randomized Controlled Trial of Augmented Reality Just-in-Time Guidance for the Performance of Rugged Field Procedures

Published online by Cambridge University Press:  07 May 2024

Laurel O’Connor Open the ORCID record for Laurel O’Connor [Opens in a new window] ,
Sepahrad Zamani ,
Xinyi Ding ,
Nicolette McGeorge ,
Susan Latiff ,
Cindy Liu ,
Jorge Acevedo Herman ,
Matthew LoConte ,
Andrew Milsten Open the ORCID record for Andrew Milsten [Opens in a new window]  and
Michael Weiner
...Show all authors
Laurel O’Connor*
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Sepahrad Zamani
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Xinyi Ding
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Nicolette McGeorge
Affiliation:
Charles River Analytics Inc, Cambridge, Massachusetts USA
Susan Latiff
Affiliation:
Charles River Analytics Inc, Cambridge, Massachusetts USA
Cindy Liu
Affiliation:
Charles River Analytics Inc, Cambridge, Massachusetts USA
Jorge Acevedo Herman
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Matthew LoConte
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Andrew Milsten
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Michael Weiner
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Timothy Boardman
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Martin Reznek
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
Michael Hall
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
John P. Broach
Affiliation:
Department of Emergency Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts USA
*
Correspondence: Laurel O’Connor, MD Department of Emergency Medicine University of Massachusetts Chan Medical School, 55 Lake Avenue North Worcester, Massachusetts USA E-mail: laurel.oconnor@umassmed.edu
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Abstract

Introduction:

Medical resuscitations in rugged prehospital settings require emergency personnel to perform high-risk procedures in low-resource conditions. Just-in-Time Guidance (JITG) utilizing augmented reality (AR) guidance may be a solution. There is little literature on the utility of AR-mediated JITG tools for facilitating the performance of emergent field care.

Study Objective:

The objective of this study was to investigate the feasibility and efficacy of a novel AR-mediated JITG tool for emergency field procedures.

Methods:

Emergency medical technician-basic (EMT-B) and paramedic cohorts were randomized to either video training (control) or JITG-AR guidance (intervention) groups for performing bag-valve-mask (BVM) ventilation, intraosseous (IO) line placement, and needle-decompression (Needle-d) in a medium-fidelity simulation environment. For the interventional condition, subjects used an AR technology platform to perform the tasks. The primary outcome was participant task performance; the secondary outcomes were participant-reported acceptability. Participant task score, task time, and acceptability ratings were reported descriptively and compared between the control and intervention groups using chi-square analysis for binary variables and unpaired t-testing for continuous variables.

Results:

Sixty participants were enrolled (mean age 34.8 years; 72% male). In the EMT-B cohort, there was no difference in average task performance score between the control and JITG groups for the BVM and IO tasks; however, the control group had higher performance scores for the Needle-d task (mean score difference 22%; P = .01). In the paramedic cohort, there was no difference in performance scores between the control and JITG group for the BVM and Needle-d tasks, but the control group had higher task scores for the IO task (mean score difference 23%; P = .01). For all task and participant types, the control group performed tasks more quickly than in the JITG group. There was no difference in participant usability or usefulness ratings between the JITG or control conditions for any of the tasks, although paramedics reported they were less likely to use the JITG equipment again (mean difference 1.96 rating points; P = .02).

Conclusions:

This study demonstrated preliminary evidence that AR-mediated guidance for emergency medical procedures is feasible and acceptable. These observations, coupled with AR’s promise for real-time interaction and on-going technological advancements, suggest the potential for this modality in training and practice that justifies future investigation.

Keywords

augmented realityaustere medicineJust-in-Time Guidanceprehospital care
Type
Original Research
Information
Prehospital and Disaster Medicine , First View , pp. 1 - 9
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of World Association for Disaster and Emergency Medicine

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