Browsing by Author "Bajaj, Komal"

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    Building impactful systems-focused simulations: integrating change and project management frameworks into the pre-work phase
    (2021-04-29) Dubé, Mirette; Posner, Glenn; Stone, Kimberly; White, Marjorie; Kaba, Alyshah; Bajaj, Komal; Cheng, Adam; Grant, Vincent; Huang, Simon; Reid, Jennifer
    Abstract Healthcare organizations strive to deliver safe, high-quality, efficient care. These complex systems frequently harbor gaps, which if unmitigated, could result in harm. Systems-focused simulation (SFS) projects, which include systems-focused debriefing (SFD), if well designed and executed, can proactively and comprehensively identify gaps and test and improve systems, enabling institutions to improve safety and quality before patients and staff are placed at risk. The previously published systems-focused debriefing framework, Promoting Excellence and Reflective Learning in Simulation (PEARLS) for Systems Integration (PSI), describes a systematic approach to SFD. It includes an essential “pre-work” phase, encompassing evidence-informed steps that lead up to a SFD. Despite inclusion in the PSI framework, a detailed description of the pre-work phase, and how each component facilitates change management, was limited. The goal of this paper is to elucidate the PSI “Pre-work” phase, everything leading up to the systems-focused simulation and debriefing. It describes how the integration of project and change management principles ensures that a comprehensive collection of safety and quality issues are reliably identified and captured.
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    Cognitive Load Theory for debriefing simulations: implications for faculty development
    (2018-12-29) Fraser, Kristin L; Meguerdichian, Michael J; Haws, Jolene T; Grant, Vincent J; Bajaj, Komal; Cheng, Adam
    Abstract The debriefing is an essential component of simulation-based training for healthcare professionals, but learning this complex skill can be challenging for simulation faculty. There are multiple competing priorities for a debriefer’s attention that can contribute to a high mental workload, which may adversely affect debriefer performance and consequently learner outcomes. In this paper, we conceptualize the debriefer as a learner of debriefing skills and we discuss Cognitive Load Theory to categorize the many potential mental loads that can affect the faculty debriefer as learner. We then discuss mitigation strategies that can be considered by faculty development programmes to enhance professional development of debriefing staff.
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    Impact of the PEARLS Healthcare Debriefing cognitive aid on facilitator cognitive load, workload, and debriefing quality: a pilot study
    (2022-12-12) Meguerdichian, Michael; Bajaj, Komal; Ivanhoe, Rachel; Lin, Yiqun; Sloma, Audrey; de Roche, Ariel; Altonen, Brian; Bentley, Suzanne; Cheng, Adam; Walker, Katie
    Abstract 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.