Advances in simulation (London, England)最新文献

Background: Healthcare simulation education often aims to promote transfer of learning: the application of knowledge, skills, and attitudes acquired during simulations to new situations in the workplace. Although achieving transfer is challenging, existing theories and models can provide guidance.

Recommendations: This paper provides five general recommendations to design simulations that foster transfer: (1) emphasize whole-task practice, (2) consider a cognitive task analysis, (3) embed simulations within more comprehensive programs, (4) strategically combine and align simulation formats, and (5) optimize cognitive load. We illustrate the application of these five recommendations with a blueprint for an educational program focusing on simulation activities.

Conclusions: More evidence-informed approaches to healthcare simulation might require a paradigm shift. We must accept that a limited number of simulations is not enough to develop complex skills. It requires comprehensive programs that combine simulation sessions with workplace learning.

Background: Training prehospital personnel in identifying patients with acute stroke is key to providing rapid treatment. This study aimed to investigate whether game-based digital simulation training is a feasible alternative to standard in-person simulation training.

Methods: Second-year paramedic bachelor students at Oslo Metropolitan University in Norway were invited to participate in a study to compare game-based digital simulation (intervention) to standard in-person training (control). For 2 months, students were encouraged to practice the NIHSS, and both groups logged their simulations. Then, they performed a clinical proficiency test, and their results were assessed using a Bland-Altman plot with corresponding 95% limits of agreement (LoA).

Results: Fifty students participated in the study. Individuals in the game group (n = 23) spent an average (SD) of 42:36 min (36) on gaming and performed 14.4 (13) simulations on average, whereas the control group (n = 27) spent 9:28 min (8) simulating and performed 2.5 (1) simulations. Comparing time variables collected during the intervention period, the mean time for each simulated assessment was significantly shorter in the game group (2:57 min vs. 3:50 min, p = 0.004). In the final clinical proficiency test, the mean difference from the true NIHSS score was 0.64 (LoA: - 1.38 to 2.67) in the game group and 0.69 (LoA: - 1.65 to 3.02) in the control group.

Conclusion: Game-based digital simulation training is a feasible alternative to standard in-person simulation training to acquire competence in NIHSS assessment. Gamification seemed to give an incentive to simulate considerably more and to perform the assessment faster, with equal accuracy.

Trial registration: The study was approved by the Norwegian Centre for Research Data (reference no. 543238).

In situ simulation (ISS) programs deliver patient safety benefits to healthcare systems, however, face many challenges in both implementation and sustainability. Prebriefing is conducted immediately prior to a simulation activity to enhance engagement with the learning activity, but is not sufficient to embed and sustain an ISS program. Longer-term and broader change leadership is required to engage colleagues, secure time and resources, and sustain an in situ simulation program. No framework currently exists to describe this process for ISS programs. This manuscript presents a framework derived from the analysis of three successful ISS program implementations across different hospital systems. We describe eight change leadership steps adapted from Kotter's change management theory, used to sustainably implement the ISS programs analyzed. These steps include the following: (1) identifying goals of key stakeholders, (2) engaging a multi-professional team, (3) creating a shared vision, (4) communicating the vision effectively, (5) energizing participants and enabling program participation, (6) identifying and celebrating early success, (7) closing the loop on early program successes, and (8) embedding simulation in organizational culture and operations. We describe this process as a "longitudinal prebrief," a framework which provides a step-by-step guide to engage colleagues and sustain successful implementation of ISS.

Background: Healthcare curricula need summative assessments relevant to and representative of clinical situations to best select and train learners. Simulation provides multiple benefits with a growing literature base proving its utility for training in a formative context. Advancing to the next step, "the use of simulation for summative assessment" requires rigorous and evidence-based development because any summative assessment is high stakes for participants, trainers, and programs. The first step of this process is to identify the baseline from which we can start.

Methods: First, using a modified nominal group technique, a task force of 34 panelists defined topics to clarify the why, how, what, when, and who for using simulation-based summative assessment (SBSA). Second, each topic was explored by a group of panelists based on state-of-the-art literature reviews technique with a snowball method to identify further references. Our goal was to identify current knowledge and potential recommendations for future directions. Results were cross-checked among groups and reviewed by an independent expert committee.

Results: Seven topics were selected by the task force: "What can be assessed in simulation?", "Assessment tools for SBSA", "Consequences of undergoing the SBSA process", "Scenarios for SBSA", "Debriefing, video, and research for SBSA", "Trainers for SBSA", and "Implementation of SBSA in healthcare". Together, these seven explorations provide an overview of what is known and can be done with relative certainty, and what is unknown and probably needs further investigation. Based on this work, we highlighted the trustworthiness of different summative assessment-related conclusions, the remaining important problems and questions, and their consequences for participants and institutions of how SBSA is conducted.

Conclusion: Our results identified among the seven topics one area with robust evidence in the literature ("What can be assessed in simulation?"), three areas with evidence that require guidance by expert opinion ("Assessment tools for SBSA", "Scenarios for SBSA", "Implementation of SBSA in healthcare"), and three areas with weak or emerging evidence ("Consequences of undergoing the SBSA process", "Debriefing for SBSA", "Trainers for SBSA"). Using SBSA holds much promise, with increasing demand for this application. Due to the important stakes involved, it must be rigorously conducted and supervised. Guidelines for good practice should be formalized to help with conduct and implementation. We believe this baseline can direct future investigation and the development of guidelines.

Introduction: Rapid-cycle deliberate practice (RCDP) is a simulation-based educational strategy that consists of repeating a simulation scenario a number of times to acquire a planned competency. When the objective of a cycle is achieved, a new cycle initiates with increased skill complexity. There have been no previous randomized studies comparing after-event debriefing clinical manikin-based simulation to RCDP in adult cardiopulmonary resuscitation (CPR).

Methods: We invited physicians from the post-graduate program on Emergency Medicine of the Hospital Israelita Albert Einstein. Groups were randomized 1:1 to RCDP or after-event debriefing simulation prior to the first station of CPR training. During the first 5 min of the pre-intervention scenario, both groups participated in a simulated case of an out-of-hospital cardiac arrest without facilitator interference; after the first 5 min, each scenario was then facilitated according to group allocation (RCDP or after-event debriefing). In a second scenario of CPR later in the day with the same participants, there was no facilitator intervention, and the planned outcomes were evaluated. The primary outcome was the chest compression fraction during CPR in the post-intervention scenario. Secondary outcomes comprised time for recognition of the cardiac arrest, time for first verbalization of the cardiac arrest initial rhythm, time for first defibrillation, and mean pre-defibrillation pause.

Results: We analyzed data of three courses conducted between June 2018 and July 2019, with 76 participants divided into 9 teams. Each team had a median of 8 participants. In the post-intervention scenario, the RCDP teams had a significantly higher chest compression fraction than the after-event debriefing group (80.0% vs 63.6%; p = 0.036). The RCDP group also demonstrated a significantly lower time between recognition of the rhythm and defibrillation (6 vs 25 s; p value = 0.036).

Conclusion: RCDP simulation strategy is associated with significantly higher manikin chest compression fraction during CPR when compared to an after-event debriefing simulation.

Background: During hospital relocations, it is important to support healthcare professionals becoming familiar with new settings. Simulation-based training seems promising and in situ simulation has been suggested as a beneficial educational tool to prepare healthcare professionals for relocation. This study aimed to investigate the impact of a simulation-based training intervention on health professionals´ readiness to work in their new environment, as well as investigate sick leave before and after relocation.

Methods: The study was a controlled intervention study implemented at a university hospital in Denmark. Simulation was used to prepare employees for workflows prior to relocation. Before relocation, 1199 healthcare professionals participated in the in situ simulation-based training program. Questionnaires on readiness to perform were distributed to participants at pre-, post-, and follow-up (6 months) measurement. In addition, data on participants' sick leave was gathered from a business intelligence portal. To compare dependent and independent groups, paired and unpaired t tests were performed on mean score of readiness to perform and sick leave.

Results: Compared to the control group, healthcare professionals participating in the intervention felt significantly more ready to work in a new hospital environment. As a measure of psychological wellbeing, register data indicated no difference in sick leave, when comparing intervention and control groups before and after participating in the in situ simulation-based training program.

Conclusions: Healthcare professionals felt significantly more ready to work in a new environment, after participating in the in situ simulation-based training program, indicating that the intervention supported healthcare professionals during relocations. This may mitigate feelings of uncertainty; however, further research is needed to explore such effects.

Trial registration: The study was approved by The Regional Ethics Committee (no. 1-16-02-222-22).

Background: The Promoting Excellence and Reflective Learning in Simulation (PEARLS) Healthcare Debriefing Tool is a cognitive aid designed to deploy debriefing in a structured way. The tool has the potential to increase the facilitator's ability to acquire debriefing skills, by breaking down the complexity of debriefing and thereby improving the quality of a novice facilitator's debrief. In this pilot study, we aimed to evaluate the impact of the tool on facilitators' cognitive load, workload, and debriefing quality.

Methods: Fourteen fellows from the New York City Health + Hospitals Simulation Fellowship, novice to the PEARLS Healthcare Debriefing Tool, were randomized to two groups of 7. The intervention group was equipped with the cognitive aid while the control group did not use the tool. Both groups had undergone an 8-h debriefing course. The two groups performed debriefings of 3 videoed simulated events and rated the cognitive load and workload of their experience using the Paas-Merriënboer scale and the raw National Aeronautics and Space Administration task load index (NASA-TLX), respectively. The debriefing performances were then rated using the Debriefing Assessment for Simulation in Healthcare (DASH) for debriefing quality. Measures of cognitive load were measured as Paas-Merriënboer scale and compared using Wilcoxon rank-sum tests. Measures of workload and debriefing quality were analyzed using mixed-effect linear regression models.

Results: Those who used the tool had significantly lower median scores in cognitive load in 2 out of the 3 debriefings (median score with tool vs no tool: scenario A 6 vs 6, p=0.1331; scenario B: 5 vs 6, p=0.043; and scenario C: 5 vs 7, p=0.031). No difference was detected in the tool effectiveness in decreasing composite score of workload demands (mean difference in average NASA-TLX -4.5, 95%CI -16.5 to 7.0, p=0.456) or improving composite scores of debriefing qualities (mean difference in DASH 2.4, 95%CI -3.4 to 8.1, p=0.436).

Conclusions: The PEARLS Healthcare Debriefing Tool may serve as an educational adjunct for debriefing skill acquisition. The use of a debriefing cognitive aid may decrease the cognitive load of debriefing but did not suggest an impact on the workload or quality of debriefing in novice debriefers. Further research is recommended to study the efficacy of the cognitive aid beyond this pilot; however, the design of this research may serve as a model for future exploration of the quality of debriefing.