Literature DB >> 35521080

COVID-SIM: building testing capacity through public engagement with healthcare simulation.

Natasha Christodoulides1, William P Duggan1, Kirsten R Dalrymple1.   

Abstract

Entities:  

Keywords:  in situ simulation; medical education; simulation based learning; simulation-based education

Year:  2020        PMID: 35521080      PMCID: PMC8936933          DOI: 10.1136/bmjstel-2020-000637

Source DB:  PubMed          Journal:  BMJ Simul Technol Enhanc Learn        ISSN: 2056-6697


× No keyword cloud information.

Introduction

An outbreak of respiratory disease caused by COVID-19 has caught the world off guard. As death tolls rise and governments implement stringent measures to control its spread, members of the public show desire to help. Testing as a means to manage and contain the disease has been recognised worldwide. This has spurred numerous initiatives including set-up of drive-through COVID-19 testing clinics. Currently, drive-through testing is performed by healthcare workers. Using these drive-through clinics as inspiration, we propose integrating simulation to train volunteers from the public to perform safe testing of symptomatic patients for COVID-19 in the community.

Making simulation accessible

The initial uptake of simulation in contemporary healthcare education was first employed to prepare for crisis events. As we combat the COVID-19 pandemic, healthcare educators have a duty to expand the use of simulation beyond its dominant use in training and assessment to its full potential, including making it readily accessible and relevant to the public. We suggest Kneebone et al’s model of ‘distributed simulation’ as an easily accessible, widely available method to deliver a low-cost, ‘immersive’ simulated experience.1 This can be achieved by taking simulation away from the physical confines of a simulation facility and into the community. We envisage that this could be successful as learners and educators will be working towards a common goal with personal meaning. Volunteers from the public, ideally with a basic understanding of infection control, for example, from the food handling industry, biomedical laboratories. Simulated ‘test centres’ to train volunteers on safely donning and doffing personal protective equipment (PPE) and swabbing symptomatic patients for COVID-19. Alleviate pressures posed on the healthcare system, allowing greater numbers of nurses and paramedics to return to the front line. Safely teach new skills to volunteers. Create a representation of ‘safe swabbing’ for the purposes of practice. Extend the benefits of simulation to the community. Provide a safe space for learners for feedback and debriefing.

COVID-SIM: a low-cost, mobile simulator

Our purpose

In the preparation phase, comprehensive and achievable intended learning objectives should be set around the use of PPE, appropriate sample collection and communicating with patients. We propose that educators use a low-technology manikin head, PPE and testing kits to deliver situated training in the community, based on a standardised protocol. Following an introduction and demonstration of the simulators, volunteers will learn through practice and experimentation. The educator’s role will be to provide ‘Vygotskian’-style ‘scaffolding’, encouraging novice learners to experiment and providing support and feedback when required to advance learning.2 A formal debrief will conclude each session (figure 1).
Figure 1

Description of the phases involved in the design and application of the simulated activity for COVID-SIM (adapted from Swanwick et al 2). ILO, intended learning objective.

Description of the phases involved in the design and application of the simulated activity for COVID-SIM (adapted from Swanwick et al 2). ILO, intended learning objective.

Simulation-based instructional design

The simulation design progressively layers and integrates skills as follows: Safe donning and doffing of PPE (demonstration, practice with PPE, feedback). Swabbing of patients (demonstration, practice with swabs and manikin heads, feedback). Communication for gaining consent, explanation of the procedure and process of obtaining test results (demonstration, role-play, feedback). Task performance using the manikin in a ‘car’, with the voice of an educator/volunteer (briefing, experimentation, simulation practice, debriefing).

Stage 2: scenario-based simulations

Multiple debriefing tools exist to structure the discussion that follows the simulation. The primary aim is to foster a supportive environment where the learners feel safe and psychologically challenged to engage in reflective practice.3

Rethinking fidelity: shifting focus to engagement and meaningfulness for learners

The rise in popularity of technology in simulation accompanies the assumption that greater simulation fidelity (ie, a high resemblance to real patients, events and/or environments) will lead to enhanced learning.4 This has shifted focus away from the intended educational outcomes of the simulated experience. Hamstra et al argue that higher fidelity does not necessarily correspond to improved educational effectiveness. They go so far as to maintain that the concept of fidelity is unhelpful and that ‘functional task alignment’ and ‘learner engagement’ are more important features of learning using simulation.4 Going beyond the above definition of fidelity, Stokes-Parish and colleagues describe two complementary modes of reality: (1) conceptual or ‘semantical’ realism, that is, the cue that invites the learner to progress in the scenario, and (2) ‘phenomenal’ realism or the emotional buy-in of the learner.5 The potential for COVID-SIM’s success lies in the phenomenal realism that learners bring to the simulation. Our intended learners have willingly signed up so we anticipate they enter the programme with greater emotional investment, greater sense of purpose and, hence, a greater average level of engagement. As effective simulation lies largely in engagement and meaningfulness for the learner, COVID-SIM is poised to create learning gains using flexible and low-cost simulation approaches.1 2 4

How can we use the lessons learnt here to integrate simulation in the future?

COVID-19 has created a global healthcare crisis. Here we propose a role for simulation that goes beyond the confines of the simulation facility and beyond the healthcare community. As a new initiative addressing an expanded ‘audience’ we believe COVID-SIM offers space and potential for exploration. In an attempt to reflect the emergent nature of the COVID-19 crisis, we have not added details on how we would train educators nor what suitable equipment could be used where potential shortages of PPE or testing kits exist. Like this virus, simulation sees no boundaries. Moving forward, this initiative could provide a starting point to illustrate an expanded scope for simulation, one that potentially forges greater connections and collaboration between healthcare and the public. The COVID-19 crisis provides an unprecedented opportunity for healthcare educators internationally, to employ low-cost, easily accessible and portable simulated training to relieve pressures on healthcare systems. Taking simulation beyond the confines of training and assessment of clinical ‘insiders’ shows the potential for simulation to train non-clinical volunteers to perform essential tasks. Practice, experimentation, feedback and effective debrief are key in encouraging reflective practice in learners. Crisis situations are known to create a stronger sense of ‘community’—the emotional engagement of learners and educators can be harnessed to promote relevant learning.
  4 in total

Review 1.  Debriefing with good judgment: combining rigorous feedback with genuine inquiry.

Authors:  Jenny W Rudolph; Robert Simon; Peter Rivard; Ronald L Dufresne; Daniel B Raemer
Journal:  Anesthesiol Clin       Date:  2007-06

2.  Distributed simulation--accessible immersive training.

Authors:  Roger Kneebone; Sonal Arora; Dominic King; Fernando Bello; Nick Sevdalis; Eva Kassab; Raj Aggarwal; Ara Darzi; Debra Nestel
Journal:  Med Teach       Date:  2010-01       Impact factor: 3.650

3.  Reconsidering fidelity in simulation-based training.

Authors:  Stanley J Hamstra; Ryan Brydges; Rose Hatala; Benjamin Zendejas; David A Cook
Journal:  Acad Med       Date:  2014-03       Impact factor: 6.893

4.  Expert opinions on the authenticity of moulage in simulation: a Delphi study.

Authors:  Jessica Stokes-Parish; Robbert Duvivier; Brian Jolly
Journal:  Adv Simul (Lond)       Date:  2019-07-08
  4 in total
  1 in total

1.  Simulation translation differences between craft groups.

Authors:  Jye Gard; Chi Duong; Kirsty Murtagh; Jessica Gill; Katherine Lambe; Ian Summers
Journal:  Adv Simul (Lond)       Date:  2022-07-27
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.