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      Lessons learned in preparing for and responding to the early stages of the COVID-19 pandemic: one simulation’s program experience adapting to the new normal

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          Abstract

          Use of simulation to ensure an organization is ready for significant events, like COVID-19 pandemic, has shifted from a “backburner” training tool to a “first choice” strategy for ensuring individual, team, and system readiness. In this report, we summarize our simulation program’s response during the COVID-19 pandemic, including the associated challenges and lessons learned. We also reflect on anticipated changes within our program as we adapt to a “new normal” following this pandemic. We intend for this report to function as a guide for other simulation programs to consult as this COVID-19 crisis continues to unfold, and during future challenges within global healthcare systems. We argue that this pandemic has cemented simulation programs as fundamental for any healthcare organization interested in ensuring its workforce can adapt in times of crisis. With the right team and set of partners, we believe that sustained investments in a simulation program will amplify into immeasurable impacts across a healthcare system.

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          Reconsidering fidelity in simulation-based training.

          In simulation-based health professions education, the concept of simulator fidelity is usually understood as the degree to which a simulator looks, feels, and acts like a human patient. Although this can be a useful guide in designing simulators, this definition emphasizes technological advances and physical resemblance over principles of educational effectiveness. In fact, several empirical studies have shown that the degree of fidelity appears to be independent of educational effectiveness. The authors confronted these issues while conducting a recent systematic review of simulation-based health professions education, and in this Perspective they use their experience in conducting that review to examine key concepts and assumptions surrounding the topic of fidelity in simulation.Several concepts typically associated with fidelity are more useful in explaining educational effectiveness, such as transfer of learning, learner engagement, and suspension of disbelief. Given that these concepts more directly influence properties of the learning experience, the authors make the following recommendations: (1) abandon the term fidelity in simulation-based health professions education and replace it with terms reflecting the underlying primary concepts of physical resemblance and functional task alignment; (2) make a shift away from the current emphasis on physical resemblance to a focus on functional correspondence between the simulator and the applied context; and (3) focus on methods to enhance educational effectiveness using principles of transfer of learning, learner engagement, and suspension of disbelief. These recommendations clarify underlying concepts for researchers in simulation-based health professions education and will help advance this burgeoning field.
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            Simulation-based medical education: an ethical imperative.

            Medical training must at some point use live patients to hone the skills of health professionals. But there is also an obligation to provide optimal treatment and to ensure patients' safety and well-being. Balancing these 2 needs represents a fundamental ethical tension in medical education. Simulation-based learning can help mitigate this tension by developing health professionals' knowledge, skills, and attitudes while protecting patients from unnecessary risk. Simulation-based training has been institutionalized in other high-hazard professions, such as aviation, nuclear power, and the military, to maximize training safety and minimize risk. Health care has lagged behind in simulation applications for a number of reasons, including cost, lack of rigorous proof of effect, and resistance to change. Recently, the international patient safety movement and the U.S. federal policy agenda have created a receptive atmosphere for expanding the use of simulators in medical training, stressing the ethical imperative to "first do no harm" in the face of validated, large epidemiological studies describing unacceptable preventable injuries to patients as a result of medical management. Four themes provide a framework for an ethical analysis of simulation-based medical education: best standards of care and training, error management and patient safety, patient autonomy, and social justice and resource allocation. These themes are examined from the perspectives of patients, learners, educators, and society. The use of simulation wherever feasible conveys a critical educational and ethical message to all: patients are to be protected whenever possible and they are not commodities to be used as conveniences of training.
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              Reducing door-to-needle times in stroke thrombolysis to 13 min through protocol revision and simulation training: a quality improvement project in a Norwegian stroke centre

              In eligible patients with acute ischaemic stroke, rapid revascularisation is crucial for good outcome. At our treatment centre, we had achieved and sustained a median door-to-needle time of under 30 min. We hypothesised that further improvement could be achieved through implementing a revised treatment protocol and in situ simulation-based team training sessions. This report describes a quality improvement project aiming to reduce door-to-needle times in stroke thrombolysis. All members of the acute stroke treatment team were surveyed to tailor the interventions to local conditions. Through a review of responses and available literature, the improvement team suggested changes to streamline the protocol and designed in situ simulation-based team training sessions. Implementation of interventions started in February 2017. We completed 14 simulation sessions from February to June 2017 and an additional 12 sessions from November 2017 to March 2018. Applying Kirkpatrick’s four-level training evaluation model, participant reactions, clinical behaviour and patient outcomes were measured. Statistical process control charts were used to demonstrate changes in treatment times and patient outcomes. A total of 650 consecutive patients, including a 3-year baseline, treated with intravenous thrombolysis were assessed. Median door to needle times were significantly reduced from 27 to 13 min and remained consistent after 13 months. Risk-adjusted cumulative sum charts indicate a reduced proportion of patients deceased or bedridden after 90 days. There was no significant change in balancing measures (stroke mimics, fatal intracranial haemorrhage and prehospital times). Implementing a revised treatment protocol in combination with in situ simulation-based team training sessions for stroke thrombolysis was followed by a considerable reduction in door-to-needle times and improved patient outcomes. Additional work is needed to assess sustainability and generalisability of the interventions.
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                Author and article information

                Contributors
                petro82@gmail.com
                Journal
                Adv Simul (Lond)
                Adv Simul (Lond)
                Advances in Simulation
                BioMed Central (London )
                2059-0628
                3 June 2020
                3 June 2020
                2020
                : 5
                : 8
                Affiliations
                [1 ]GRID grid.415502.7, Unity Health Toronto – Simulation Program, St. Michael’s Hospital, , Unity Health Toronto, ; Toronto, Canada
                [2 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Medicine, , University of Toronto, ; Toronto, Canada
                [3 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Paediatrics, , University of Toronto, ; Toronto, Canada
                [4 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Physical Therapy, , University of Toronto, ; Toronto, Canada
                [5 ]GRID grid.415502.7, Department of Medicine, Division of Critical Care Medicine, St. Michael’s Hospital, , Unity Health Toronto, ; Toronto, Canada
                [6 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Medicine and Interdepartmental Division of Critical Care Medicine, , University of Toronto, ; Toronto, Canada
                [7 ]GRID grid.415502.7, Department of Anesthesia, St. Michael’s Hospital, , Unity Health Toronto, ; Toronto, Canada
                [8 ]GRID grid.17063.33, ISNI 0000 0001 2157 2938, Department of Anesthesiology and Pain Medicine, , University of Toronto, ; Toronto, Canada
                [9 ]GRID grid.415502.7, Department of Emergency Medicine, , St. Michael’s Hospital, ; Toronto, Canada
                Article
                128
                10.1186/s41077-020-00128-y
                7267752
                24d7dd9a-6c5a-4754-a889-4b2778efc28d
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 24 April 2020
                : 19 May 2020
                Categories
                Innovation
                Custom metadata
                © The Author(s) 2020

                healthcare simulation,quality improvement and patient safety,pandemic planning and response

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