Emergency medicine patient wait time multivariable prediction models: a multicentre derivation and validation study.

OBJECTIVE: Patients, families and community members would like emergency department wait time visibility. This would improve patient journeys through emergency medicine. The study objective was to derive, internally and externally validate machine learning models to predict emergency patient wait times that are applicable to a wide variety of emergency departments. METHODS: Twelve emergency departments provided 3 years of retrospective administrative data from Australia (2017-2019). Descriptive and exploratory analyses were undertaken on the datasets. Statistical and machine learning models were developed to predict wait times at each site and were internally and externally validated. Model performance was tested on COVID-19 period data (January to June 2020). RESULTS: There were 1 930 609 patient episodes analysed and median site wait times varied from 24 to 54 min. Individual site model prediction median absolute errors varied from±22.6 min (95% CI 22.4 to 22.9) to ±44.0 min (95% CI 43.4 to 44.4). Global model prediction median absolute errors varied from ±33.9 min (95% CI 33.4 to 34.0) to ±43.8 min (95% CI 43.7 to 43.9). Random forest and linear regression models performed the best, rolling average models underestimated wait times. Important variables were triage category, last-k patient average wait time and arrival time. Wait time prediction models are not transferable across hospitals. Models performed well during the COVID-19 lockdown period. CONCLUSIONS: Electronic emergency demographic and flow information can be used to approximate emergency patient wait times. A general model is less accurate if applied without site-specific factors.

Predicting Ambulance Patient Wait Times: A Multicenter Derivation and Validation Study.

STUDY OBJECTIVE: To derive and internally and externally validate machine-learning models to predict emergency ambulance patient door-to-off-stretcher wait times that are applicable to a wide variety of emergency departments. METHODS: Nine emergency departments provided 3 years (2017 to 2019) of retrospective administrative data from Australia. Descriptive and exploratory analyses were undertaken on the datasets. Statistical and machine-learning models were developed to predict wait times at each site and were internally and externally validated. RESULTS: There were 421,894 episodes analyzed, and median site off-load times varied from 13 (interquartile range [IQR], 9 to 20) to 29 (IQR, 16 to 48) minutes. The global site prediction model median absolute errors were 11.7 minutes (95% confidence interval [CI], 11.7 to 11.8) using linear regression and 12.8 minutes (95% CI, 12.7 to 12.9) using elastic net. The individual site model prediction median absolute errors varied from the most accurate at 6.3 minutes (95% CI, 6.2 to 6.4) to the least accurate at 16.1 minutes (95% CI, 15.8 to 16.3). The model technique performance was the same for linear regression, random forests, elastic net, and rolling average. The important variables were the last k-patient average waits, triage category, and patient age. The global model performed at the lower end of the accuracy range compared with models for the individual sites but was within tolerable limits. CONCLUSION: Electronic emergency demographic and flow information can be used to estimate emergency ambulance patient off-stretcher times. Models can be built with reasonable accuracy for multiple hospitals using a small number of point-of-care variables.

The relation between young adults' trust beliefs in others and interpersonal hostility.

The research examined whether, and if so how, young adults' trust beliefs in others were associated with interpersonal hostility. The participants in Study 1 were 139 young adults from the UK (76 women; Mage = 20.8). In Study 2, 88 young adult women from the UK (Mage = 21.5) served as participants. The participants completed a standardized measure of trust beliefs in others (total with reliability, honesty, and emotional subscales). In Study 1, participants imagined they were victims of peer provocation. They were required to judge the intention for the provocation and their retaliation to it. In Study 2, the participants were engaged in a lab-based acquaintanceship interaction that involved the exchange of disclosures. They completed an adjective checklist that assessed anger and evaluated the quality of the conversation. Trust beliefs were linearly and negatively associated with the attribution of hostile intentions, retaliation, anger toward others, and critical evaluation of a developing peer relationship. As expected though, quadratic relations were found. Young adults with very low and those with very high trust beliefs (primarily emotionally based) showed greater attribution of hostile intentions, retaliation, anger toward others, and critical evaluation of a developing peer relationship than did young adults with the middle range of trust beliefs. The linear relations supported the hypothesis that trust promotes psychosocial adjustment. The quadratic relations supported the deviation from the normative trust (centralist) approach primarily for emotional trust beliefs in others.

Acetyl-CoA carboxylase inhibition disrupts metabolic reprogramming during hepatic stellate cell activation.

BACKGROUND & AIMS: Non-alcoholic steatohepatitis (NASH) is a chronic liver disease characterized by hepatic lipid accumulation, inflammation, and progressive fibrosis. Acetyl-CoA carboxylase (ACC) catalyzes the rate-limiting step of de novo lipogenesis and regulates fatty acid ß-oxidation in hepatocytes. ACC inhibition reduces hepatic fat content and markers of liver injury in patients with NASH; however, the effect of ACC inhibition on liver fibrosis has not been reported. METHODS: A direct role for ACC in fibrosis was evaluated by measuring de novo lipogenesis, procollagen production, gene expression, glycolysis, and mitochondrial respiration in hepatic stellate cells (HSCs) in the absence or presence of small molecule inhibitors of ACC. ACC inhibitors were evaluated in rodent models of liver fibrosis induced by diet or the hepatotoxin, diethylnitrosamine. Fibrosis and hepatic steatosis were evaluated by histological and biochemical assessments. RESULTS: Inhibition of ACC reduced the activation of TGF-ß-stimulated HSCs, as measured by both α-SMA expression and collagen production. ACC inhibition prevented a metabolic switch necessary for induction of glycolysis and oxidative phosphorylation during HSC activation. While the molecular mechanism by which inhibition of de novo lipogenesis blocks glycolysis and oxidative phosphorylation is unknown, we definitively show that HSCs require de novo lipogenesis for activation. Consistent with this direct antifibrotic mechanism in HSCs, ACC inhibition reduced liver fibrosis in a rat choline-deficient, high-fat diet model and in response to chronic diethylnitrosamine-induced liver injury (in the absence of hepatic lipid accumulation). CONCLUSIONS: In addition to reducing lipid accumulation in hepatocytes, ACC inhibition also directly impairs the profibrogenic activity of HSCs. Thus, small molecule inhibitors of ACC may lessen fibrosis by reducing lipotoxicity in hepatocytes and by preventing HSC activation, providing a mechanistic rationale for the treatment of patients with advanced liver fibrosis due to NASH. LAY SUMMARY: Hepatic fibrosis is the most important predictor of liver-related outcomes in patients with non-alcoholic steatohepatitis (NASH). Small molecule inhibitors of acetyl-CoA carboxylase (ACC) reduce hepatic fat content and markers of liver injury in patients with NASH. Herein, we report that inhibition of ACC and de novo lipogenesis also directly suppress the activation of hepatic stellate cells - the primary cell responsible for generating fibrotic scar in the liver - and thus fibrosis. These data provide further evidence for the use of ACC inhibitors to treat patients with NASH and advanced fibrosis.

Ketamine as adjunct to midazolam treatment following soman-induced status epilepticus reduces seizure severity, epileptogenesis, and brain pathology in plasma carboxylesterase knockout mice.

Delayed treatment of cholinergic seizure results in benzodiazepine-refractory status epilepticus (SE) that is thought, at least in part, to result from maladaptive trafficking of N-methyl-d-aspartate (NMDA) and gamma-aminobutyric acid type A (GABAA) receptors, the effects of which may be ameliorated by combination therapy with the NMDA receptor antagonist ketamine. Our objective was to establish whether ketamine and midazolam dual therapy would improve outcome over midazolam monotherapy following soman (GD) exposure when evaluated in a mouse model that, similar to humans, lacks plasma carboxylesterase, greatly reducing endogenous scavenging of GD. In the current study, continuous cortical electroencephalographic activity was evaluated in male and female plasma carboxylesterase knockout mice exposed to a seizure-inducing dose of GD and treated with midazolam or with midazolam and ketamine combination at 40 min after seizure onset. Ketamine and midazolam combination reduced GD-induced lethality, seizure severity, and the number of mice that developed spontaneous recurrent seizure (SRS) compared with midazolam monotherapy. In addition, ketamine-midazolam combination treatment reduced GD-induced neuronal degeneration and microgliosis. These results support that combination of antiepileptic drug therapies aimed at correcting the maladaptive GABAA and NMDA receptor trafficking reduces the detrimental effects of GD exposure. Ketamine may be a beneficial adjunct to midazolam in reducing the epileptogenesis and neuroanatomical damage that follows nerve agent exposure and pharmacoresistant SE.

Soman-induced status epilepticus, epileptogenesis, and neuropathology in carboxylesterase knockout mice treated with midazolam.

OBJECTIVE: Exposure to chemical warfare nerve agents (CWNAs), such as soman (GD), can induce status epilepticus (SE) that becomes refractory to benzodiazepines when treatment is delayed, leading to increased risk of epileptogenesis, severe neuropathology, and long-term behavioral and cognitive deficits. Rodent models, widely used to evaluate novel medical countermeasures (MCMs) against CWNA exposure, normally express plasma carboxylesterase, an enzyme involved in the metabolism of certain organophosphorus compounds. To better predict the efficacy of novel MCMs against CWNA exposure in human casualties, it is crucial to use appropriate animal models that mirror the human condition. We present a comprehensive characterization of the seizurogenic, epileptogenic, and neuropathologic effects of GD exposure with delayed anticonvulsant treatment in the plasma carboxylesterase knockout (ES1-/-) mouse. METHODS: Electroencephalography (EEG) electrode-implanted ES1-/- and wild-type (C57BL/6) mice were exposed to various seizure-inducing doses of GD, treated with atropine sulfate and the oxime HI-6 at 1 minute after exposure, and administered midazolam at 15-30 minutes following the onset of seizure activity. The latency of acute seizure onset and spontaneous recurrent seizures (SRS) was assessed, as were changes in EEG power spectra. At 2 weeks after GD exposure, neurodegeneration and neuroinflammation were assessed. RESULTS: GD-exposed ES1-/- mice displayed a dose-dependent response in seizure severity. Only ES1-/- mice exposed to the highest tested dose of GD developed SE, subchronic alterations in EEG power spectra, and SRS. Degree of neuronal cell loss and neuroinflammation were dose-dependent; no significant neuropathology was observed in C57BL/6 mice or ES1-/- mice exposed to lower GD doses. SIGNIFICANCE: The US Food and Drug Administration (FDA) animal rule requires the use of relevant animal models for the advancement of MCMs against CWNAs. We present evidence that argues for the use of the ES1-/- mouse model to screen anticonvulsant, antiepileptic, and/or neuroprotective drugs against GD-induced toxicity, as well as to identify mechanisms of GD-induced epileptogenesis.

Validating Obstetric Emergency Checklists using Simulation: A Randomized Controlled Trial.

Background The World Health Organization's Surgical Safety Checklist has demonstrated significant reduction in surgical morbidity. The American Congress of Obstetricians and Gynecologists District II Safe Motherhood Initiative (SMI) safety bundles include eclampsia and postpartum hemorrhage (PPH) checklists. Objective To determine whether use of the SMI checklists during simulated obstetric emergencies improved completion of critical actions and to elicit feedback to facilitate checklist revision. Study Design During this randomized controlled trial, teams were assigned to use a checklist during one of two emergencies: eclampsia and PPH. Raters scored teams on critical step completion. Feedback was elicited through structured debriefing. Results In total, 30 teams completed 60 scenarios. For eclampsia, trends toward higher completion were noted for blood pressure and airway management. For PPH, trends toward higher completion rates were noted for PPH stage assessment and fundal massage. Feedback resulted in substantial checklist revision. Participants were enthusiastic about using checklists in a clinical emergency. Conclusion Despite trends toward higher rates of completion of critical tasks, teams using checklists did not approach 100% task completion. Teams were interested in the application of checklists and provided feedback necessary to substantially revise the checklists. Intensive implementation planning and training in use of the revised checklists will result in improved patient outcomes.

Infectious and sepsis presentations to, and hospital admissions from emergency departments in Victoria, Australia.

OBJECTIVE: To investigate the frequency and outcomes of adult infectious and sepsis presentations to, and hospital admissions from, Emergency Departments (EDs) in Victoria, Australia. METHODS: Retrospective cohort study using the Victorian Emergency Minimum Dataset and Victorian Admitted Episodes Dataset. We included adults (age ≥ 18 years) presenting to an ED, or admitted to hospital from ED in Victoria between July 2017 and June 2018. One-year mortality was analysed until June 2019 using the Victorian Death Index, and ICD-10 coding was used to identify cases. RESULTS: Among 1.28 million ED presentations over 1 year, 12.00% and 0.45% were coded with infectious and sepsis diagnoses, respectively. Despite having lower triage categories, patients with infections were more likely to be admitted to hospital (50.4% vs 44.9%), but not directly to ICU (0.8%). Patients coded with sepsis were assigned higher triage categories and required hospital admission much more frequently (96.4% vs 44.9%), including to ICU (15.9% vs 0.8%). Patients presenting with infections and sepsis had increased risk of 1-year mortality (adjusted hazard ratio 1.44 and 4.13, respectively). Of the 648 280 hospital admissions from the ED, infection and sepsis were coded in 23.69% and 2.66%, respectively, and the adjusted odds ratio for 1-year mortality were 1.64 and 4.79, respectively. CONCLUSIONS: Infections and sepsis are common causes of presentation to, and admission from the ED in Victoria. Such patients experience higher mortality than non-infectious patients, even after adjusting for age. There is a need to identify modifiable factors contributing to these outcomes.

Attitudes towards artificial intelligence in emergency medicine.

OBJECTIVE: To assess Australian and New Zealand emergency clinicians' attitudes towards the use of artificial intelligence (AI) in emergency medicine. METHODS: We undertook a qualitative interview-based study based on grounded theory. Participants were recruited through ED internal mailing lists, the Australasian College for Emergency Medicine Bulletin, and the research teams' personal networks. Interviews were transcribed, coded and themes presented. RESULTS: Twenty-five interviews were conducted between July 2021 and May 2022. Thematic saturation was achieved after 22 interviews. Most participants were from either Western Australia (52%) or Victoria (16%) and were consultants (96%). More participants reported feeling optimistic (10/25) than neutral (6/25), pessimistic (2/25) or mixed (7/25) towards the use of AI in the ED. A minority expressed scepticism regarding the feasibility or value of implementing AI into the ED. Multiple potential risks and ethical issues were discussed by participants including skill loss from overreliance on AI, algorithmic bias, patient privacy and concerns over liability. Participants also discussed perceived inadequacies in existing information technology systems. Participants felt that AI technologies would be used as decision support tools and not replace the roles of emergency clinicians. Participants were not concerned about the impact of AI on their job security. Most (17/25) participants thought that AI would impact emergency medicine within the next 10 years. CONCLUSIONS: Emergency clinicians interviewed were generally optimistic about the use of AI in emergency medicine, so long as it is used as a decision support tool and they maintain the ability to override its recommendations.

Applications of natural language processing at emergency department triage: A narrative review.

INTRODUCTION: Natural language processing (NLP) uses various computational methods to analyse and understand human language, and has been applied to data acquired at Emergency Department (ED) triage to predict various outcomes. The objective of this scoping review is to evaluate how NLP has been applied to data acquired at ED triage, assess if NLP based models outperform humans or current risk stratification techniques when predicting outcomes, and assess if incorporating free-text improve predictive performance of models when compared to predictive models that use only structured data. METHODS: All English language peer-reviewed research that applied an NLP technique to free-text obtained at ED triage was eligible for inclusion. We excluded studies focusing solely on disease surveillance, and studies that used information obtained after triage. We searched the electronic databases MEDLINE, Embase, Cochrane Database of Systematic Reviews, Web of Science, and Scopus for medical subject headings and text keywords related to NLP and triage. Databases were last searched on 01/01/2022. Risk of bias in studies was assessed using the Prediction model Risk of Bias Assessment Tool (PROBAST). Due to the high level of heterogeneity between studies and high risk of bias, a metanalysis was not conducted. Instead, a narrative synthesis is provided. RESULTS: In total, 3730 studies were screened, and 20 studies were included. The population size varied greatly between studies ranging from 1.8 million patients to 598 triage notes. The most common outcomes assessed were prediction of triage score, prediction of admission, and prediction of critical illness. NLP models achieved high accuracy in predicting need for admission, triage score, critical illness, and mapping free-text chief complaints to structured fields. Incorporating both structured data and free-text data improved results when compared to models that used only structured data. However, the majority of studies (80%) were assessed to have a high risk of bias, and only one study reported the deployment of an NLP model into clinical practice. CONCLUSION: Unstructured free-text triage notes have been used by NLP models to predict clinically relevant outcomes. However, the majority of studies have a high risk of bias, most research is retrospective, and there are few examples of implementation into clinical practice. Future work is needed to prospectively assess if applying NLP to data acquired at ED triage improves ED outcomes when compared to usual clinical practice.

The Role of Maternal Grandmothers' Childcare Provision for Korean Working Adult Daughters.

Despite the Korean government's investment in childcare facilities for dual-earner households, maternal grandmothers are increasingly taking on the responsibility of caring for their grandchildren. This trend is examined in the current research. While many studies have been conducted on grandparents' experiences providing childcare for their grandchildren, significantly less research has been conducted on adult daughters' experiences with their mothers' childcare provision. This study utilized the concepts of intergenerational solidarity and a life-course approach to understand the experiences of 24 working adult daughters in Korea (ages 30-43) whose mothers provide childcare. Three major themes were identified following a grounded theory approach: gratitude vs. guilt, dependence vs. independence, and closeness vs. disagreement. The results indicated that adult daughters were found to have ambivalence toward their mothers, reflecting the lack of alternative options for childcare. The results from this study suggest that not only improving the quality of public childcare services, but also diversifying services to reflect the needs of dual-income families.

Future Time Perspective, Priority of Social Goals, and Friend Networks in Old Age: Evidence for Socioemotional Selectivity Theory Using Subjective Age Gap.

Several studies have focused on population aging, with a focus on the relationship between age and the main concepts of the socioemotional selectivity theory, but many do not report consistent results. Therefore, this study sought to better understand how the socioemotional selective theory informs our understanding of the elderly in Korea. More specifically, it aimed at observing how age groups differ in regards to future time perspective, social goals, and friend networks. Data were collected from 271 elderly people (M = 72.98 years old, SD = 5.63) using questionnaires. The statistical program SPSS 25.0 was used to perform descriptive statistical analyses, reliability analyses, and ANOVAs. The findings indicated that the Korean elderly participants perceived their subjective age to be younger than their chronological age. Furthermore, if they perceived their subjective age to be older than their chronological age, they were more likely to report that their network of friends was smaller than they desired. Lastly, depending on their age, the Korean elderly participants reported different priorities of the goals they wished to pursue. These results could help researchers, clinical practitioners, and policymakers to better understand the unique differences in the Korean elderly.

Learning practices of experienced healthcare teams and dyads in acute care settings: a scoping review.

OBJECTIVES: To map the evidence on learning practices currently used by experienced healthcare teams and dyads. The hypothesis is that through reviewing the literature we will identify the number and array of current learning practices. Through the lens of collaboration, the authors' goal is to map current practice to guide future research, policy and practice. SETTING: The review included studies from North America, Europe, Australasia and Asia. All studies were conducted in acute care settings such as operating rooms, emergency rooms, intensive care units and simulation centres. PARTICIPANTS: The participants were experienced healthcare professionals who work in acute care settings of any age or any sex. The group was interprofessional including two or more disciplines and/or professions. Characteristics of the participants who were excluded were students, novices, healthcare professionals who work in non-acute care settings and single profession studies. PRIMARY AND SECONDARY OUTCOME MEASURES: Aligned to the protocol quantitative and qualitative analyses were conducted. Thematic analysis was used to evaluate and categorise the study findings. Secondary outcome measures were the different types of learning practices used together to produce excellence. RESULTS: Most empirical studies were qualitative studies (46%), 31% were mixed methods and 23% were quantitative studies. There were also 24 reviews and 10 commentaries. The most frequent learning practices were structured observation and case scenarios (21%) followed by audio/video analysis and surveys (17%). Next was interviews and didactic presentations (12%) followed by prebriefing/debriefing and checklists (11%). Other learning practices accounted for less than 10%. Overall, 84 of the 86 publications, examined learning practices of teams larger than two participants. CONCLUSIONS: While the quality of studies was high, and there was a broad range of empirical studies, reviews and commentaries, there was no consensus on best practice in determining which learning practices to use and measurement of the effect of these practices.

From little things, big things grow: An exploratory analysis of the national cost of peripheral intravenous catheter insertion in Australian adult emergency care.

OBJECTIVE: To estimate the total economic impact of peripheral intravenous catheter (PIVC) or cannula insertion and use in adult Australian EDs, including those cannulas that remain unused for therapeutic purposes. METHODS: Searches on Australian government websites were conducted to find rates of insertion, complications and cost of cannula; following this, gaps in national data sets were filled with MEDLINE and PubMed searches to estimate the total cost of cannula use in Australian EDs. Once the data were collected, totals were combined to establish an estimated cost for the listed categories. RESULTS: The estimated cost of cannulation in Australia may be up to A$594 million per year, including the cost of insertion (equipment and staff), cost of complications such as Staphylococcus aureus bacteraemia and phlebitis, and patient-centred costs (lost patient productivity, infiltration, occlusion and dislodgement). Approximately A$305.9 million is attributed to unused cannulas and approximately 11 790 days of clinician time is spent annually inserting cannula that remains idle. CONCLUSION: The figures developed in the present study represent an important educational opportunity to encourage thoughtful consideration of all interventions, no matter how small. ED cannula insertion represents a large economic and health cost to Australia's health system, many of which remain unused. There are no national data sets that record complications associated with PIVCs and we highlight the urgent need for improved data.

Management of patients presenting with low back pain to a private hospital emergency department in Melbourne, Australia.

OBJECTIVE: Recent studies suggest many patients with non-specific low back pain presenting to public hospital EDs receive low-value care. The primary aim was to describe management of patients presenting with low back pain to the ED of a private hospital in Melbourne, Australia, and received a final ED diagnosis of non-specific low back pain. We also determined predictors of hospital admission. METHODS: Retrospective review of patients who presented with low back pain and received a final ED diagnosis of non-specific low back pain to Cabrini Malvern ED in 2015. Demographics, lumbar spinal imaging, pathology tests and medications were extracted from hospital records. Multivariate logistic regression was used to determine independent predictors of hospital admission. RESULTS: Four hundred and fifty presentations were included (60% female); 238 (52.9%) were admitted to hospital. One hundred and seventy-seven (39.3%) patients received lumbar spine imaging. Two hundred and eighty (62.2%) patients had pathology tests and 391 (86.9%) received medications, which included opioids (n = 298, 66.2%), paracetamol (n = 219, 48.7%), NSAIDs (n = 161, 35.8%), benzodiazepines (n = 118, 26.2%) and pregabalin (n = 26, 5.8%). Predictors of hospital admission included older age (odds ratio [OR] 1.03, 95% confidence interval [CI] 1.02-1.05), arrival by ambulance (OR 2.03, 95% CI 1.06-3.90) and receipt of pathology tests (OR 3.32, 95% CI 2.01-5.49) or computed tomography scans (OR 1.86, 95% CI 1.12-3.11). CONCLUSION: We observed high rates of imaging, pathology tests and hospital admissions compared with previous public hospital studies, while medication use was similar. Implementation of strategies to optimise evidence-based ED care is needed to reduce low-value care and improve patient outcomes.

Impact of the PEARLS Healthcare Debriefing cognitive aid on facilitator cognitive load, workload, and debriefing quality: a pilot study.

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.