The 2019 WACEM expert document on hybrid simulation for transforming health-care simulation through “mixing and matching”

Lateef, Fatimah; Too, Xin Yi

doi:10.4103/jets.jets_112_19

Cited by 6 publications

(2 citation statements)

References 27 publications

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“…Even with this, each resident's training and supervision are customized to their individual capability, capacity, accumulated acquisition of competencies, level of ease, and familiarity with procedures, cases, and techniques, as well as other summative and formative factors. [5][6][7] With all these in mind, it must always be set against the background of the emergency department, whereby the environment is extremely dynamic, fast-paced and functions on a 24/7 basis.…”

Section: Emergency Medicine Residency Trainingmentioning

confidence: 99%

Advocacy inquiry and circular questioning to maintain psychological safety in training, feedback, and conversations with residents

Lateef

2024

Emerg Crit Care Med

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Training of emergency physicians through an emergency medicine residency program takes 5 years, that is, 3 years in junior residency and 2 years in senior residency. Throughout this period, residents will be exposed to a variety of educational methodologies and meet a spectrum of faculty, supervisors, and teachers, who will have different personalities, styles, and approaches to teaching and nurturing them. It is important to ensure the maintenance of psychological safety for these residents throughout their training journey and into the future years of practice s an emergency physician. Communications, interactions (which involve questioning), and presentations will be an important part of this training program. This article looks at two modes of questioning: advocacy inquiry and circular questioning, which can be applied as appropriate. These two methods are examples in which faculty may consider adopting in their many interactions, follow-up, feedback, tutorials, facilitation, partnerships, and counseling sessions with residents. These two techniques offer options to maintain psychological safety, which can facilitate learners sharing and opening up. It can be included in the faculty’s armamentarium of questioning techniques and applied where applicable.

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Section: Emergency Medicine Residency Trainingmentioning

confidence: 99%

Advocacy inquiry and circular questioning to maintain psychological safety in training, feedback, and conversations with residents

Lateef

2024

Emerg Crit Care Med

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“…It is worth highlighting that a hybrid ML-simulation methodology, which is the focus of the present study, should not be confused with a hybrid simulation, which, instead, is based on the use of two or more different simulation modalities (e.g. combining time-based and event-based simulation) with proper alignment, coordination, and interfacing of the model components [38][39][40][41][42]. There are some studies that can be considered precursors of the topics tackled in this review.…”

Section: Introductionmentioning

confidence: 99%

Combining simulation models and machine learning in healthcare management: strategies and applications

Ponsiglione,

Zaffino,

Ricciardi

et al. 2024

Prog. Biomed. Eng.

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Simulation models and artificial intelligence are largely used to address healthcare and biomedical engineering problems. Both approaches showed promising results in the analysis and optimization of healthcare processes. Therefore, the combination of simulation models and artificial intelligence could provide a strategy to further boost the quality of health services. In this work, a systematic review of studies applying a hybrid simulation models and artificial intelligence approach to address healthcare management challenges was carried out. Scopus, Web of Science, and PubMed databases were screened by independent reviewers. The main strategies to combine simulation and artificial intelligence as well as the major healthcare application scenarios were identified and discussed. Moreover, tools and algorithms to implement the proposed approaches were described. Results showed that machine learning appears to be the most employed artificial intelligence strategy in combination with simulation models, which mainly rely on agent-based and discrete-event systems. The scarcity and heterogeneity of the included studies suggested that a standardized framework to implement hybrid machine learning-simulation approaches in healthcare management is yet to be defined. Future efforts should aim to use these approaches to design novel intelligent in-silico models of healthcare processes and to provide effective translation to the clinics.

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Multi-Modal Simulation to Prepare Final Year Nursing Students for Transition to Clinical Practice: A Mixed Methods Study

Liaw,

Rusli,

Schmidt

et al. 2024

Clinical Simulation in Nursing

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The 2019 WACEM expert document on hybrid simulation for transforming health-care simulation through “mixing and matching”

Cited by 6 publications

References 27 publications

Advocacy inquiry and circular questioning to maintain psychological safety in training, feedback, and conversations with residents

Advocacy inquiry and circular questioning to maintain psychological safety in training, feedback, and conversations with residents

Combining simulation models and machine learning in healthcare management: strategies and applications

Multi-Modal Simulation to Prepare Final Year Nursing Students for Transition to Clinical Practice: A Mixed Methods Study

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