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.

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.

The Emergency Medicine Education and Research by Global Experts (EMERGE) Network: Challenges and Lessons Learned.

INTRODUCTION: The Emergency Medicine Education and Research by Global Experts (EMERGE) network was formed to generate and translate evidence to improve global emergency care. We share the challenges faced and lessons learned in establishing a global research network. METHODS: We describe the challenges encountered when EMERGE proposed the development of a global emergency department (ED) visit registry. The proposed registry was to be a six-month, retrospective, deidentified, minimal dataset of routinely collected variables, such as patient demographics, diagnosis, and disposition. RESULTS: Obtaining reliable, accurate, and pertinent data from participating EDs is challenging in a global context. Barriers experienced ranged from variable taxonomies, need for language translation, varying site processes for curation and transfer of deidentified data, navigating institution- and country-specific data protection regulations, and substantial variation in each participating institution's research infrastructure including training in research-related activities. We have overcome many of these challenges by creating detailed data-sharing agreements with bilateral regulatory oversight agreements between EMERGE and participating EDs, developing relationships with and training health informaticians at each site to ensure secure transfer of deidentified data, and formalizing an electronic transfer process ensuring data privacy. CONCLUSION: We believe that networks like EMERGE are integral to providing the necessary platforms for education, training, and research collaborations for emergency care. We identified substantial challenges in data sharing and variation in local sites' research infrastructure and propose potential approaches to address these challenges.

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.

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.

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.

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.

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.

Stroke Code From EMS to Thrombectomy: An Interdisciplinary In Situ Simulation for Prompt Management of Acute Ischemic Stroke.

INTRODUCTION: Treatment of acute ischemic stroke is challenging because it requires prompt management, interdisciplinary collaboration, and adherence to specific guidelines. This resource addresses these challenges by providing in situ simulated practice with stroke codes by practicing clinicians at unannounced times. METHODS: An emergency department team was presented with a 55-year-old simulated patient with speech difficulty and right-sided weakness. The team had to assess her efficiently and appropriately, including activating the stroke team via the hospital paging system. The stroke team responded to collaboratively coordinate evaluation, obtain appropriate imaging, administer thrombolytic therapy, and recognize the need for thrombectomy. Learners moved through the actual steps in the real clinical environment, using real hospital equipment. Upon simulation completion, debriefing was utilized to review the case and team performance. Latent safety threats were recorded, if present. Participants completed an evaluation to gauge the simulation's effectiveness. RESULTS: Six simulations involving 40 total participants were conducted and debriefed across New York City Health + Hospitals. One hundred percent of teams correctly identified the presenting condition and assessed eligibility for thrombolytic and endovascular therapy. Evaluations indicated that 100% of learners found the simulation to be an effective clinical, teamwork, and communication teaching tool. Debriefing captured several latent safety threats, which were rectified by collaboration with hospital leadership. DISCUSSION: Impromptu, in situ simulation helps develop interdisciplinary teamwork and clinical knowledge and is useful for reviewing crucial times and processes required for best-practice patient care. It is particularly useful when timely management is essential, as with acute ischemic stroke.

Optimising expert dyad performance in acute care settings: a scoping review protocol.

INTRODUCTION: When there is miscommunication and poor coordination between experienced clinician dyads, teamwork suffers. Research on expert learning practices for the smallest team, and arguably the most important team, the healthcare dyad, is limited. The objective of this study is to map the extent and range of evidence available on learning practices which experienced dyads use, to achieve excellent performance, and to identify the gaps in effective practice. This will guide future research, policy and practice. METHODS AND ANALYSIS: We are using the JBI methodology for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for Scoping Reviews Extension Fillable Checklist, searching for literature that meets the inclusion criteria. The searches will be conducted using Maastricht University's Libsearch, which includes MEDLINE, Education Resources Information Center and PsycINFO and a second search on Web of Science online databases. We will search grey literature and references of selected sources. Search limits include sources from 2016 to 2021, using English language only. A data extraction tool was developed, and charting will use a thematic analysis approach. IMPLICATIONS AND DISSEMINATION: This review will be the first to examine the learning practices that experienced dyads use, which ensures excellent performance in acute care settings. The findings will be used to develop best-practices and shared with New York City hospital system. Dissemination will occur through peer-reviewed publications and at healthcare conferences.

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.

Soman-induced toxicity, cholinesterase inhibition and neuropathology in adult male Göttingen minipigs.

Animal models are essential for evaluating the toxicity of chemical warfare nerve agents (CWNAs) to extrapolate to human risk and are necessary to evaluate the efficacy of medical countermeasures. The Göttingen minipig is increasingly used for toxicological studies because it has anatomical and physiological characteristics that are similar to those of humans. Our objective was to determine whether the minipig would be a useful large animal model to evaluate the toxic effects of soman (GD). We determined the intramuscular (IM) median lethal dose (LD50) of GD in adult male Göttingen minipigs using an up-and-down dosing method. In addition to lethality estimates, we characterized the observable signs of toxicity, blood and tissue cholinesterase (ChE) activity and brain pathology following GD exposure. The 24 h LD50 of GD was estimated to be 4.7 µg/kg, with 95 % confidence limits of 3.6 and 6.3 µg/kg. As anticipated, GD inhibited ChE activity in blood and several tissues. Neurohistopathological analysis showed neurodegeneration and neuroinflammation in survivors exposed to 4.7 µg/kg of GD, including in the primary visual cortex and various thalamic nuclei. These findings suggest that the minipig will be a useful large animal model for assessing drugs to mitigate neuropathological effects of exposure to CWNAs.

Fundamental underpinnings of simulation education: describing a four-component instructional design approach to healthcare simulation fellowships.

Although in 2020, there are more than 120 healthcare simulation fellowships established globally, there is a paucity of literature on how to design fellowship programs most effectively, to equip graduates with the knowledge, skills, and attitudes of a competent simulation educator. Offering a systematic structure to approach simulation fellowship programmatic design may aid in better achieving program goals. In this manuscript, we present the application of the 4-component instructional design model as a blueprint to the development of Simulation Education Fellowships. We offer examples used at the NYC Health + Hospitals simulation fellowship to illustrate how the 4-component model informs fellowship program design which promotes the development of a simulation educator. This manuscript will provide a roadmap to designing curricula and assessment practices including self-reflective logbooks to focus the path toward achieving desired skills and shape future conversations around programmatic development.