Development and Implementation of Augmented Reality Enhanced High-Fidelity Simulation for Recognition of Patient Decompensation

被引:16
作者
Zackoff, Matthew W. [1 ,2 ]
Cruse, Bradley [3 ]
Sahay, Rashmi D. [1 ,4 ,5 ]
Fei, Lin [1 ,4 ]
Saupe, Jennifer [5 ]
Schwartz, Jerome [5 ]
Klein, Melissa [1 ,6 ]
Geis, Gary L. [1 ,7 ]
Tegtmeyer, Ken [1 ,2 ]
机构
[1] Univ Cincinnati, Coll Med, Dept Pediat, Cincinnati, OH 45221 USA
[2] Cincinnati Childrens Hosp Med Ctr, Div Crit Care Med, Cincinnati, OH 45229 USA
[3] Cincinnati Childrens Hosp Med Ctr, Ctr Simulat & Res, Cincinnati, OH 45229 USA
[4] Cincinnati Childrens Hosp Med Ctr, Div Biostat & Epidemiol, Cincinnati, OH 45229 USA
[5] Cincinnati Childrens Hosp Med Ctr, Ctr Profess Excellence, Cincinnati, OH 45229 USA
[6] Cincinnati Childrens Hosp Med Ctr, Div Gen & Community Pediat, Cincinnati, OH 45229 USA
[7] Cincinnati Childrens Hosp Med Ctr, Div Emergency Med, Cincinnati, OH 45229 USA
来源
SIMULATION IN HEALTHCARE-JOURNAL OF THE SOCIETY FOR SIMULATION IN HEALTHCARE | 2021年 / 16卷 / 03期
关键词
Simulation-based medical education; augmented reality; decompensation; cardiopulmonary arrest; COMPETENCE; EDUCATION; CARE;
D O I
10.1097/SIH.0000000000000486
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Introduction Simulation is a core aspect of training and assessment; however, simulation laboratories are limited in their ability to visually represent mental, respiratory, and perfusion status. Augmented reality (AR) represents a potential adjunct to address this gap. Methods A prospective, observational pilot of interprofessional simulation assessing a decompensating patient was conducted from April to June 2019. Teams completed 2 simulations: (1) traditional training (TT) using a manikin (Laerdal SimJunior) and (2) AR-enhanced training (ART) using a manikin plus an AR patient. The primary outcome was self-assessed effectiveness at the assessment of patient decompensation. Secondary outcomes were attitudes toward and adverse effects during the AR training. Results Twenty-one simulation sessions included 84 participants in headsets. Participants reported improved ability to assess the patient's mental status, respiratory status, and perfusion status (all P < 0.0001) during ART in comparison to TT. Similar findings were noted for recognition of hypoxemia, shock, apnea, and decompensation (all P <= 0.0003) but not for recognition of cardiac arrest (P = 0.06). Most participants agreed or strongly agreed that ART accurately depicted a decompensating patient (89%), reinforced key components of the patient assessment (88%), and will impact how they care for patients (68%). Augmented reality-enhanced training was rated more effective than manikin training and standardized patients and equally as effective as bedside teaching. Conclusions This novel application of AR to enhance the realism of manikin simulation demonstrated improvement in self-assessed recognition of patient decompensation. Augmented reality may represent a viable modality for increasing the clinical impact of training.
引用
收藏
页码:221 / 230
页数:10
相关论文
共 24 条
  • [1] [Anonymous], 2004, REPORT EUROPEAN COMM
  • [2] Feasibility of an augmented reality cardiopulmonary resuscitation training system for health care providers
    Balian, Steve
    McGovern, Shaun K.
    Abella, Benjamin S.
    Blewer, Audrey L.
    Leary, Marion
    [J]. HELIYON, 2019, 5 (08)
  • [3] Technology-Enhanced Simulation and Pediatric Education: A Meta-analysis
    Cheng, Adam
    Lang, Tara R.
    Starr, Stephanie R.
    Pusic, Martin
    Cook, David A.
    [J]. PEDIATRICS, 2014, 133 (05) : E1313 - E1323
  • [4] Challenges of biological realism and validation in simulation-based medical education
    Day, Roger S.
    [J]. ARTIFICIAL INTELLIGENCE IN MEDICINE, 2006, 38 (01) : 47 - 66
  • [5] Effect of High-Fidelity Simulation on Pediatric Advanced Life Support Training in Pediatric House Staff A Randomized Trial
    Donoghue, Aaron J.
    Durbin, Dennis R.
    Nadel, Frances M.
    Stryjewski, Glenn R.
    Kost, Suzanne I.
    Nadkarni, Vinay M.
    [J]. PEDIATRIC EMERGENCY CARE, 2009, 25 (03) : 139 - 144
  • [6] Simulation-based Education to Ensure Provider Competency Within the Health Care System
    Griswold, Sharon
    Fralliccardi, Alise
    Boulet, John
    Moadel, Tiffany
    Franzen, Douglas
    Auerbach, Marc
    Hart, Danielle
    Goswami, Varsha
    Hui, Joshua
    Gordon, James A.
    [J]. ACADEMIC EMERGENCY MEDICINE, 2018, 25 (02) : 168 - 176
  • [7] Han Jenny E, 2014, J Grad Med Educ, V6, P501, DOI 10.4300/JGME-D-13-00420.1
  • [8] Research electronic data capture (REDCap)-A metadata-driven methodology and workflow process for providing translational research informatics support
    Harris, Paul A.
    Taylor, Robert
    Thielke, Robert
    Payne, Jonathon
    Gonzalez, Nathaniel
    Conde, Jose G.
    [J]. JOURNAL OF BIOMEDICAL INFORMATICS, 2009, 42 (02) : 377 - 381
  • [10] Features and uses of high-fidelity medical simulations that lead to effective learning: a BEME systematic review
    Issenberg, SB
    McGaghie, WC
    Petrusa, ER
    Gordon, DL
    Scalese, RJ
    [J]. MEDICAL TEACHER, 2005, 27 (01) : 10 - 28