Classifying simulators and simulations for extracorporeal membrane oxygenation (ECMO) - A review with a new framework on classifying fidelity

Introduction: Background, Context and Aims
Outcomes of extracorporeal membrane oxygenation (ECMO) for cardiac or respiratory failure improve when performed with a suitable annual exposure to ECMO cases. High-volume ECMO centres are scarce, whereas simulation-based training (SBT) offers an addition to these low-volume centres for training and maintenance of skills, and to improve interdisciplinary team interactions. However, ECMO simulators and/or simulations (ECMO sims) techniques vary in purpose, and therefore their level of realism (fidelity). The necessary level of fidelity must be based on the intended
training outcome. Therefore, level of fidelity is not the same as quality of an ECMO sim.
The aim is to develop a fidelity classification framework and objectively classify available ECMO sims by an
interdisciplinary panel of users and developers as low-, mid-, or high-fidelity.

Methods
Fidelity classification is based on a new framework consisting of overall ECMO sim fidelity, established by taking the median of the definition-based fidelity, component fidelity, and customization fidelity as determined by expert opinion. PRISMA (preferred reporting items for systematic reviews and meta-analyses) scoping guidelines were followed. Consensus was achieved on definitions, and ultimate classification.

Results & Discussion
Until October 2022, 30 ECMO sims were found, with 26 suitable for classification. According to this framework, all assessed ECMO sims only classified as low- or mid-fidelity. Most ECMO sims (54%) lacked patient customization, i.e. ECMO sims with different physical features as skin colour, sex, or amount of subcutaneous fat. This comparison method may be used in the future for the description of new developments in ECMO sims, making it possible for ECMO sim designers, users, and researchers to compare accordingly, and ultimately improve ECMO patient outcomes.