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Reorganizing Neonatal Resuscitation Equipment Improves Performance Speed Under Simulation Conditions

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Advances in Human Factors and Ergonomics in Healthcare and Medical Devices (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 590))

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Abstract

Approximately 10% of infants will need resuscitation at birth. Resuscitations are performed by nurses, physicians, and other health care providers (HCPs) following international guidelines such as the Neonatal Resuscitation Program (NRP). Often, basic neonatal resuscitation equipment (e.g. monitoring and airway supplies) is not organized to facilitate equipment identification and retrieval, hindering HCP performance. In this study, we developed an equipment box with input from NRP-trained providers, reorganizing neonatal resuscitation equipment to improve ordering, grouping, and labeling. In a crossover simulation study, we tested HCP performance with this box against performance using a standard equipment bag. HCPs were faster in completing a simulated resuscitation scenario when using the equipment box (mean completion time 176 ± 21.6 s) compared with the standard equipment bag (192.6 ± 20.2 s) (p < 0.0001). Despite familiarity with the standard equipment bag, all HCPs preferred the equipment box. Reorganizing basic neonatal resuscitation to improve ordering, grouping, and labeling may improve HCP performance.

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Acknowledgments

We would like to thank the Resuscitation-Stabilization-Triage team at the Royal Alexandra Hospital for helping and supporting the study. This research has been facilitated by the Women and Children’s Health Research Institute through the generous support of the Stollery Children’s Hospital Foundation.

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Correspondence to Brenda Law .

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Law, B., Cheung, PY., O’Reilly, M., Fray, C., Schmölzer, G. (2018). Reorganizing Neonatal Resuscitation Equipment Improves Performance Speed Under Simulation Conditions. In: Duffy, V., Lightner, N. (eds) Advances in Human Factors and Ergonomics in Healthcare and Medical Devices. AHFE 2017. Advances in Intelligent Systems and Computing, vol 590. Springer, Cham. https://doi.org/10.1007/978-3-319-60483-1_35

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  • DOI: https://doi.org/10.1007/978-3-319-60483-1_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60482-4

  • Online ISBN: 978-3-319-60483-1

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