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Translational simulation for rapid transformation of health services, using the example of the COVID-19 pandemic preparation.

ABSTRACT: Healthcare simulation has significant potential for helping health services to deal with the COVID-19 pandemic. Rapid changes to care pathways and processes needed for protection of staff and patients may be facilitated by a translational simulation approach-diagnosing changes needed, developing and testing new processes and then embedding new systems and teamwork through training. However, there are also practical constraints on running in situ simulations during a pandemic-the need for physical distancing, rigorous infection control for manikins and training equipment and awareness of heightened anxiety among simulation participants. We describe our institution's simulation strategy for COVID-19 preparation and reflect on the lessons learned-for simulation programs and for health services seeking to utilise translational simulation during and beyond the COVID-19 pandemic. We offer practical suggestions for a translational simulation strategy and simulation delivery within pandemic constraints. We also suggest simulation programs develop robust strategies, governance and relationships for managing change within institutions-balancing clinician engagement, systems engineering expertise and the power of translational simulation for diagnosing, testing and embedding changes.

SUBMITTER: Brazil V

PROVIDER: S-EPMC7267758 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:This study presents two simulation modelling tools to support the organisation of networks of dialysis services during the COVID-19 pandemic. These tools were developed to support renal services in the South of England (the Wessex region caring for 650 dialysis patients), but are applicable elsewhere. A discrete-event simulation was used to model a worst case spread of COVID-19, to stress-test plans for dialysis provision throughout the COVID-19 outbreak. We investigated the ability of the system to manage the mix of COVID-19 positive and negative patients, the likely effects on patients, outpatient workloads across all units, and inpatient workload at the centralised COVID-positive inpatient unit. A second Monte-Carlo vehicle routing model estimated the feasibility of patient transport plans. If current outpatient capacity is maintained there is sufficient capacity in the South of England to keep COVID-19 negative/recovered and positive patients in separate sessions, but rapid reallocation of patients may be needed. Outpatient COVID-19 cases will spillover to a secondary site while other sites will experience a reduction in workload. The primary site chosen to manage infected patients will experience a significant increase in outpatients and inpatients. At the peak of infection, it is predicted there will be up to 140 COVID-19 positive patients with 40 to 90 of these as inpatients, likely breaching current inpatient capacity. Patient transport services will also come under considerable pressure. If patient transport operates on a policy of one positive patient at a time, and two-way transport is needed, a likely scenario estimates 80 ambulance drive time hours per day (not including fixed drop-off and ambulance cleaning times). Relaxing policies on individual patient transport to 2-4 patients per trip can save 40-60% of drive time. In mixed urban/rural geographies steps may need to be taken to temporarily accommodate renal COVID-19 positive patients closer to treatment facilities.

Project description: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.

Project description:BackgroundDuring the COVID-19 pandemic in Ontario, Canada, an Emergency Standard of Care for Major Surge was created to establish a uniform process for the "triage" of finite critical care resources. This proposed departure from usual clinical care highlighted the need for an educational tool to prepare physicians for making and communicating difficult triage decisions. We created a just-in-time, virtual, simulation-based curriculum and evaluated its impact for our group of academic Emergency Physicians.MethodsOur curriculum was developed and evaluated following Stufflebeam's Context-Input-Process-Product model. Our virtual simulation sessions, delivered online using Microsoft Teams, addressed a range of clinical scenarios involving decisions about critical care prioritization (i.e., Triage). Simulation participants completed a pre-course multiple-choice knowledge test and rating scales pertaining to their attitudes about using the Emergency Standard of Care protocol before and 2-4 weeks after participating. Qualitative feedback about the curriculum was solicited through surveys.ResultsNine virtual simulation sessions were delivered over 3 weeks, reaching a total of 47 attending emergency physicians (74% of our active department members). Overall, our intervention led to a 36% (95% CI 22.9-48.3%) improvement in participants' self-rated comfort and attitudes in navigating triage decisions and communicating with patients at the end of life. Scores on the knowledge test improved by 13% (95% CI 0.4-25.6%). 95% of participants provided highly favorable ratings of the course content and similarly indicated that the session was likely or very likely to change their practice. The curriculum has since been adopted at multiple sites around the province.ConclusionOur novel virtual simulation curriculum facilitated rapid dissemination of the Emergency Standard of Care for Major Surge to our group of Emergency Physicians despite COVID-19-related constraints on gathering. The active learning afforded by this method improved physician confidence and knowledge with these difficult protocols.

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Translational simulation for rapid transformation of health services, using the example of the COVID-19 pandemic preparation.

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