Browsing by Author "Barnes, Sue"

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    Commissioning simulations to test new healthcare facilities: a proactive and innovative approach to healthcare system safety
    (2019-07-16) Kaba, Alyshah; Barnes, Sue
    Abstract Development and reconstruction of new healthcare facilities and spaces has the potential for latent safety threats to emerge, specifically unintentional harm that could affect actual patients once the facility opens, such as missing equipment, inefficient setup, or insufficient space for procedures. Process-orientated simulation and testing is a novel innovation in healthcare. The aim of process-orientated simulations and debriefing is to examine the process of care, rather than the outcome of care. These simulations, which take place in actual patient care settings and environments prior to occupancy, are an emerging strategy that can be used to test new environments and new healthcare facilities to ensure that the spaces created match the needs of the staff and administration, while proactively identifying latent safety threats prior to delivering patient care. In turn, these simulations can be also be used as part of the new site orientation and training plan. The aim of this paper is to examine a case study describing the use of the novel innovation of process-orientated simulations to test the opening of a new 300-bed healthcare facility.
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    Correction to: COVID-19 pandemic preparation: using simulation for systems-based learning to prepare the largest healthcare workforce and system in Canada
    (2021-04-20) Dubé, Mirette; Kaba, Alyshah; Cronin, Theresa; Barnes, Sue; Fuselli, Tara; Grant, Vincent
    An amendment to this paper has been published and can be accessed via the original article.
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    COVID-19 pandemic preparation: using simulation for systems-based learning to prepare the largest healthcare workforce and system in Canada
    (2020-08-18) Dubé, Mirette; Kaba, Alyshah; Cronin, Theresa; Barnes, Sue; Fuselli, Tara; Grant, Vincent
    Abstract Healthcare resources have been strained to previously unforeseeable limits as a result of the COVID-19 pandemic of 2020. This has prompted the emergence of critical just-in-time COVID-19 education, including rapid simulation preparedness, evaluation and training across all healthcare sectors. Simulation has been proven to be pivotal for both healthcare provider learning and systems integration in the context of testing and integrating new processes, workflows, and rapid changes to practice (e.g., new cognitive aids, checklists, protocols) and changes to the delivery of clinical care. The individual, team, and systems learnings generated from proactive simulation training is occurring at unprecedented volume and speed in our healthcare system. Establishing a clear process to collect and report simulation outcomes has never been more important for staff and patient safety to reduce preventable harm. Our provincial simulation program in the province of Alberta, Canada (population = 4.37 million; geographic area = 661,848 km2), has rapidly responded to this need by leading the intake, design, development, planning, and co-facilitation of over 400 acute care simulations across our province in both urban and rural Emergency Departments, Intensive Care Units, Operating Rooms, Labor and Delivery Units, Urgent Care Centers, Diagnostic Imaging and In-patient Units over a 5-week period to an estimated 30,000 learners of real frontline team members. Unfortunately, the speed at which the COVID-19 pandemic has emerged in Canada may prevent healthcare sectors in both urban and rural settings to have an opportunity for healthcare teams to participate in just-in-time in situ simulation-based learning prior to a potential surge of COVID-19 patients. Our coordinated approach and infrastructure have enabled organizational learnings and the ability to theme and categorize a mass volume of simulation outcome data, primarily from acute care settings to help all sectors further anticipate and plan. The goal of this paper is to share the unique features and advantages of using a centralized provincial simulation response team, preparedness using learning and systems integration methods, and to share the highest risk and highest frequency outcomes from analyzing a mass volume of COVID-19 simulation data across the largest health authority in Canada.