Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework

F.R. Halfwerk; Wytze Duinmeijer; Jutta Arens

doi:10.1177/03913988241279540

Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework

F.R. Halfwerk^*, Wytze Duinmeijer, Jutta Arens

^*Corresponding author for this work

Research output: Contribution to journal › Meeting Abstract › Academic

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Abstract

Extracorporeal membrane oxygenation (ECMO) support is a life-saving treatment for severe cardiac and/or pulmonary failure. Because of its high com-plexity and low patient numbers, complications such as mortality, bleeding, and infections are high. Simulation-based training with ECMO simulators (ECMO sims) is used to train skills such as ECMO cannulation, circuit monitoring, and complex problem solving. Realism (fidelity) is often assessed subjectively, and it is unclear to what extent low-, mid-, and high fidelity ECMO sims are available.
The aim of this study is to develop an objective framework for ECMO fidelity classification and apply this to available ECMO sims.

Original language	English
Pages (from-to)	421-565
Number of pages	145
Journal	The International journal of artificial organs
Volume	47
Issue number	7
DOIs	https://doi.org/10.1177/03913988241279540
Publication status	Published - Jul 2024
Event	50th ESAO Congress 2024: Organ · Cross · Talk - Honoring the Past, Empowering the Future - Eurogress, Aachen, Germany Duration: 8 Sept 2024 → 11 Sept 2024 Conference number: 50 https://www.esao2024.com/

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1177/03913988241279540

HALFWERK_ESAO2024_abstractAccepted author version, 298 KBLicence: CC BY-NC-SA

Cite this

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title = "Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework",

abstract = "Extracorporeal membrane oxygenation (ECMO) support is a life-saving treatment for severe cardiac and/or pulmonary failure. Because of its high com-plexity and low patient numbers, complications such as mortality, bleeding, and infections are high. Simulation-based training with ECMO simulators (ECMO sims) is used to train skills such as ECMO cannulation, circuit monitoring, and complex problem solving. Realism (fidelity) is often assessed subjectively, and it is unclear to what extent low-, mid-, and high fidelity ECMO sims are available.The aim of this study is to develop an objective framework for ECMO fidelity classification and apply this to available ECMO sims.",

author = "F.R. Halfwerk and Wytze Duinmeijer and Jutta Arens",

year = "2024",

month = jul,

doi = "10.1177/03913988241279540",

language = "English",

volume = "47",

pages = "421--565",

journal = "The International journal of artificial organs",

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publisher = "Sage",

number = "7",

note = "50th ESAO Congress 2024 : Organ · Cross · Talk - Honoring the Past, Empowering the Future, ESAO 2024 ; Conference date: 08-09-2024 Through 11-09-2024",

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T1 - Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework

AU - Halfwerk, F.R.

AU - Duinmeijer, Wytze

AU - Arens, Jutta

N1 - Conference code: 50

PY - 2024/7

Y1 - 2024/7

N2 - Extracorporeal membrane oxygenation (ECMO) support is a life-saving treatment for severe cardiac and/or pulmonary failure. Because of its high com-plexity and low patient numbers, complications such as mortality, bleeding, and infections are high. Simulation-based training with ECMO simulators (ECMO sims) is used to train skills such as ECMO cannulation, circuit monitoring, and complex problem solving. Realism (fidelity) is often assessed subjectively, and it is unclear to what extent low-, mid-, and high fidelity ECMO sims are available.The aim of this study is to develop an objective framework for ECMO fidelity classification and apply this to available ECMO sims.

AB - Extracorporeal membrane oxygenation (ECMO) support is a life-saving treatment for severe cardiac and/or pulmonary failure. Because of its high com-plexity and low patient numbers, complications such as mortality, bleeding, and infections are high. Simulation-based training with ECMO simulators (ECMO sims) is used to train skills such as ECMO cannulation, circuit monitoring, and complex problem solving. Realism (fidelity) is often assessed subjectively, and it is unclear to what extent low-, mid-, and high fidelity ECMO sims are available.The aim of this study is to develop an objective framework for ECMO fidelity classification and apply this to available ECMO sims.

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U2 - 10.1177/03913988241279540

DO - 10.1177/03913988241279540

M3 - Meeting Abstract

SN - 0391-3988

VL - 47

SP - 421

EP - 565

JO - The International journal of artificial organs

JF - The International journal of artificial organs

IS - 7

T2 - 50th ESAO Congress 2024

Y2 - 8 September 2024 through 11 September 2024

ER -

Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework

Abstract

UN SDGs

Access to Document

Other files and links

Fingerprint

Patient-centered educational ECMO simulator (EduECMO)

Simulation-Based Training With Extracorporeal Membrane Oxygenator Simulators – A Training Needs Analysis

Classifying fidelity for ECMO simulators and simulations: An overview of existing physical and computational ECMO simulators

Cite this

Assessing Realism Of Extracorporeal Membrane Oxygenator Simulators – Development And Application Of An Objective Fidelity Classification Framework

Abstract

UN SDGs

Access to Document

Other files and links

Fingerprint

Activities

Patient-centered educational ECMO simulator (EduECMO)

Research output

Simulation-Based Training With Extracorporeal Membrane Oxygenator Simulators – A Training Needs Analysis

Classifying fidelity for ECMO simulators and simulations: An overview of existing physical and computational ECMO simulators

Cite this