Overcrowding in emergency department: an international issue

Improving the introduction of telemedicine in pre-hospital emergency medicine: understanding users and how acceptability, usability and effectiveness influence this process

INTRODUCTION

Increasing numbers of ambulance calls, vacant positions and growing workloads in Emergency Medicine (EM) are increasing the pressure to find adequate solutions. With telemedicine providing health-care services by bridging large distances, connecting remote providers and even patients while using modern communication technologies, such a technology seems beneficial. As the process of developing an optimal solution is challenging, a need to quantify involved processes could improve implementation. Existing models are based on qualitative studies although standardised questionnaires for factors such as Usability, Acceptability and Effectiveness exist.

METHODS

A survey was provided to participants within a German county. It was based on telemedical surveys, the System Usabilty Scale (SUS) and earlier works describing Usability, Acceptability and Effectiveness. Meanwhile a telemedical system was introduced in the investigated county. A comparison between user-groups aswell as an exploratory factor analysis (EFA) was performed.

RESULTS

Of n = 91 included participants n = 73 (80,2%) were qualified as emergency medical staff (including paramedics n = 36 (39,56%), EMTs n = 28 (30,77%), call handlers n = 9 (9,89%)) and n = 18 (19,8%) as emergency physicians. Most participants approved that telemedicine positively impacts EM and improved treatment options with an overall Usabilty Score of 68,68. EFA provided a 3-factor solution involving Usability, Acceptability and Effectiveness.

DISCUSSION

With our results being comparable to earlier studies but telemedicine only having being sparsely introduced, a positive attitude could still be attested. While our model describes 51,28% of the underlying factors, more research is needed to identify further influences. We showed that Usability is correlated with Acceptability (strong effect), Usability and Effectiveness with a medium effect, likewise Acceptability and Effectiveness. Therefore available systems need to improve. Our approach can be a guide for decision makers and developers, that a focus during implementation must be on improving usability and on a valid data driven implementation process.

Exploring clinicians' knowledge and attitudes toward the care needs of complex adult users of an Emergency Department: A descriptive mixed methods study

BACKGROUND

Adults who frequently present (FPAs) to emergency departments (EDs) often have a history of adverse childhood experiences (ACEs) and related adult health sequelae. Implications for ED care of this group remains poorly understood. This study explored clinicians' knowledge and attitudes toward the care needs of FPAs who have an ACEs history, providing preliminary evidence to inform further research and interventions.

METHODS

A purposive sample of ED clinicians completed an investigator developed mixed-methods survey. Descriptive statistics and content analysis were applied.

RESULTS

Forty-three ED clinicians completed the survey. Most perceived that ACEs were common among FPAs and influenced their ED presentations. Clinicians were more aware of the psychosocial impacts of ACEs than the risks to physical health. While most clinicians agreed that FPAs should be asked about ACEs for management planning, most never asked, describing multiple barriers to doing so. Consumer's healthcare needs were often described as unmet by clinicians who desired additional support to provide care for this group.

CONCLUSIONS

This study highlights clinicians' perceptions of gaps in healthcare for this patient group and introduces requirements for appropriate knowledge and resources to partner with consumers to provide patient-centred and trauma-informed health care responses.

Nurses' moral judgements during emergency department triage - A prospective mixed multicenter study

INTRODUCTION

In EDs, triage ensures that patients whose condition requires immediate care are prioritized while reducing overcrowding. Previous studies have described the manifestation of caregivers' moral judgements of patients in EDs. The equal treatment of patients in clinical practice presents a major issue. Studying the impact of prejudice on clinical practice in the ED setting provides an opportunity to rethink clinical tools, organizations and future training needs. Our study sought to describe the moral judgements expressed by triage nurses during admission interviews in emergency departments and to assess their impact on patient management.

METHODS

An exploratory sequential mixed-method study was performed. The study was conducted between January 1, 2018, and February 18, 2018, in the EDs of three French hospitals. Five hundred and three patients and 79 triage nurses participated in the study. Audio recordings, observations and written handover reports made by nurses during admission triage interviews were analyzed with a view to discerning whether moral judgements were expressed in them. We studied the impact of moral judgements on patient management in the emergency department.

RESULTS

Abstract Moral judgements were made in 70% of the triage situations studied (n=351/503). They could be classified in seven categories. Patients were more likely to be subjected to moral judgements if they were over 75 years old, visibly disabled or if they had visible signs of alcohol intoxication. Being subjected to moral judgement was associated with differential treatment, including assignment of a triage score that differed from the theoretical triage score.

CONCLUSION

More than two thirds of patients admitted to EDs were triaged using moral criteria. Patients who were morally judged at the admission interview were more likely to be treated differently.

Diagnosing patient flow issues in the emergency department: an Australasian hospital case study

PURPOSE

This study investigates how a hospital can increase the flow of patients through its emergency department by using benchmarking and process improvement techniques borrowed from the manufacturing sector.

DESIGN/METHODOLOGY/APPROACH

An in-depth case study of an Australasian public hospital utilises rigorous, multi-method data collection procedures with systems thinking to benchmark an emergency department (ED) value stream and identify the performance inhibitors.

FINDINGS

High levels of value stream uncertainty result from inefficient processes and weak controls. Reduced patient flow arises from senior management's commitment to simplistic government targets, clinical staff that lack basic operations management skills, and fragmented information systems. High junior/senior staff ratios aggravate the lack of inter-functional integration and poor use of time and material resources, increasing the risk of a critical patient incident.

RESEARCH LIMITATIONS/IMPLICATIONS

This research is limited to a single case; hence, further research should assess value stream maturity and associated performance enablers and inhibitors in other emergency departments experiencing patient flow delays.

PRACTICAL IMPLICATIONS

This study illustrates how hospital managers can use systems thinking and a context-free performance benchmarking measure to identify needed interventions and transferable best practices for achieving seamless patient flow.

ORIGINALITY/VALUE

This study is the first to operationalise the theoretical concept of the seamless healthcare system to acute care as defined by Parnaby and Towill (2008). It is also the first to use the uncertainty circle model in an Australasian public healthcare setting to objectively benchmark an emergency department's value stream maturity.

Managing low-acuity patients in an Emergency Department through simulation-based multiobjective optimization using a neural network metamodel

This paper deals with Emergency Department (ED) fast-tracks for low-acuity patients, a strategy often adopted to reduce ED overcrowding. We focus on optimizing resource allocation in minor injuries units, which are the ED units that can treat low-acuity patients, with the aim of minimizing patient waiting times and ED operating costs. We formulate this problem as a general multiobjective simulation-based optimization problem where some of the objectives are expensive black-box functions that can only be evaluated through a time-consuming simulation. To efficiently solve this problem, we propose a metamodeling approach that uses an artificial neural network to replace a black-box objective function with a suitable model. This approach allows us to obtain a set of Pareto optimal points for the multiobjective problem we consider, from which decision-makers can select the most appropriate solutions for different situations. We present the results of computational experiments conducted on a real case study involving the ED of a large hospital in Italy. The results show the reliability and effectiveness of our proposed approach, compared to the standard approach based on derivative-free optimization.

The association between nurse staffing and quality of care in emergency departments: A systematic review

BACKGROUND

The relationship between nurse staffing, skill-mix and quality of care has been well-established in medical and surgical settings, however, there is relatively limited evidence of this relationship in emergency departments. Those that have been published identified that lower nurse staffing levels in emergency departments are generally associated with worse outcomes with the conclusion that the evidence in emergency settings was, at best, weak.

METHODS

We searched thirteen electronic databases for potentially eligible papers published in English up to December 2023. Studies were included if they reported on patient outcomes associated with nurse staffing within emergency departments. Observational, cross-sectional, prospective, retrospective, interrupted time-series designs, difference-in-difference, randomised control trials or quasi-experimental studies and controlled before and after studies study designs were considered for inclusion. Team members independently screened titles and abstracts. Data was synthesised using a narrative approach.

RESULTS

We identified 16 papers for inclusion; the majority of the studies (n = 10/16) were observational. The evidence reviewed identified that poorer staffing levels within emergency departments are associated with increased patient wait times, a higher proportion of patients who leave without being seen and an increased length of stay. Lower levels of nurse staffing are also associated with an increase in time to medications and therapeutic interventions, and increased risk of cardiac arrest within the emergency department.

CONCLUSION

Overall, there remains limited high-quality empirical evidence addressing the association between emergency department nurse staffing and patient outcomes. However, it is evident that lower levels of nurse staffing are associated with adverse events that can result in delays to the provision of care and serious outcomes for patients. There is a need for longitudinal studies coupled with research that considers the relationship with skill-mix, other staffing grades and patient outcomes as well as a wider range of geographical settings.

TWEETABLE ABSTRACT

Lower levels of nurse staffing in emergency departments are associated with delays in patients receiving treatments and poor quality care including an increase in leaving without being seen, delay in accessing treatments and medications and cardiac arrest.

Models to predict length of stay in the emergency department: a systematic literature review and appraisal

INTRODUCTION

Prolonged Length of Stay (LOS) in ED (Emergency Department) has been associated with poor clinical outcomes. Prediction of ED LOS may help optimize resource utilization, clinical management, and benchmarking. This study aims to systematically review models for predicting ED LOS and to assess the reporting and methodological quality about these models.

METHODS

The online database PubMed, Scopus, and Web of Science (10 Sep 2023) was searched for English language articles that reported prediction models of LOS in ED. Identified titles and abstracts were independently screened by two reviewers. All original papers describing either development (with or without internal validation) or external validation of a prediction model for LOS in ED were included.

RESULTS

Of 12,193 uniquely identified articles, 34 studies were included (29 describe the development of new models and five describe the validation of existing models). Different statistical and machine learning methods were applied to the papers. On the 39-point reporting score and 11-point methodological quality score, the highest reporting scores for development and validation studies were 39 and 8, respectively.

CONCLUSION

Various studies on prediction models for ED LOS were published but they are fairly heterogeneous and suffer from methodological and reporting issues. Model development studies were associated with a poor to a fair level of methodological quality in terms of the predictor selection approach, the sample size, reproducibility of the results, missing imputation technique, and avoiding dichotomizing continuous variables. Moreover, it is recommended that future investigators use the confirmed checklist to improve the quality of reporting.

An Effective Methodology for Scoring to Assist Emergency Physicians in Identifying Overcrowding in an Academic Emergency Department in Thailand

BACKGROUND

Emergency Department (ED) overcrowding is a global concern, with tools like NEDOCS, READI, and Work Score used as predictors. These tools aid healthcare professionals in identifying overcrowding and preventing negative patient outcomes. However, there's no agreed-upon method to define ED overcrowding. Most studies on this topic are U.S.-based, limiting their applicability in EDs without waiting rooms or ambulance diversion roles. Additionally, the intricate calculations required for these scores, with multiple variables, make them impractical for use in developing nations.

OBJECTIVE

This study sought to examine the relationship between prevalent ED overcrowding scores such as EDWIN, occupancy rate, and Work Score, and a modified version of EDWIN newly introduced by the authors, in comparison to the real-time perspectives of emergency physicians. Additionally, the study explored the links between these overcrowding scores and adverse events related to ED code activations as secondary outcomes.

METHOD

The method described in the provided text is a correlational study. The study aims to examine the relationship between various Emergency Department (ED) overcrowding scores and the real-time perceptions of emergency physicians in every two-hour period. Additionally, it seeks to explore the associations between these scores and adverse events related to ED code activations.

RESULTS

The study analyzed 459 periods, with 5.2% having Likert scores of 5-6. EDOR had the highest correlation coefficient (0.69, p < 0.001) and an AUC of 0.864. Only EDOR significantly correlated with adverse events (p = 0.033).

CONCLUSION

EDOR shows the most robust link with 'emergency physicians' views on overcrowding. Additionally, elevated EDOR scores correlate with a rise in adverse events. Emergency physicians' perceptionof overcrowding could hint at possible adverse events. Notably, all overcrowding scores have high negative predictive values, efficiently negating the likelihood of adverse incidents.

Patient flow in emergency departments: a comprehensive umbrella review of solutions and challenges across the health system

BACKGROUND

Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient flow.

METHODS

An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classified findings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/throughput/output (I/T/O) model of ED patient flow and synthesised intervention outcomes based on the Quadruple Aim framework.

RESULTS

The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient flow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignificant outcomes. The majority of interventions for enhancing ED patient flow were primarily related to the 'within-ED' phase of the patient journey. Fewer interventions were identified for the 'post-ED' phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the 'pre-ED' phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efficiency, and enhance staff satisfaction.

CONCLUSIONS

This study found that there was a wide range of interventions used to address patient flow, but the effectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efficiency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the effectiveness of interventions outside the ED in improving ED patient flow. It is essential to develop interventions that relate to all three phases of patient flow: pre-ED, within-ED, and post-ED.

An explainable machine learning approach for hospital emergency department visits forecasting using continuous training and multi-model regression

BACKGROUND AND OBJECTIVE

In the last years, the Emergency Department (ED) has become an important source of admissions for hospitals. Since late 90s, the number of ED visits has been steadily increasing, and since Covid19 pandemic this trend has been much stronger. Accurate prediction of ED visits, even for moderate forecasting time-horizons, can definitively improve operational efficiency, quality of care, and patient outcomes in hospitals.

METHODS

In this paper we propose two different interpretable approaches, based on Machine Learning algorithms, to accurately forecast hospital emergency visits. The proposed approaches involve a first step of data segmentation based on two different criteria, depending on the approach considered: first, a threshold-based strategy is adopted, where data is divided depending on the value of specific predictor variables. In a second approach, a cluster-based ensemble learning is proposed, in such a way that a clustering algorithm is applied to the training dataset, and ML models are then trained for each cluster.

RESULTS

The two proposed methodologies have been evaluated in real data from two hospital ED visits datasets in Spain. We have shown that the proposed approaches are able to obtain accurate ED visits forecasting, in short-term and also long-term prediction time-horizons up to one week, improving the efficiency of alternative prediction methods for this problem.

CONCLUSIONS

The proposed forecasting approaches have a strong emphasis on providing explainability to the problem. An analysis on which variables govern the problem and are pivotal for obtaining accurate predictions is finally carried out and included in the discussion of the paper.

Awareness of Urgent Care Services Among Primary Healthcare Center Patients in Al-Ahsa, Saudi Arabia

Background Urgent care clinics (UCCs) provide services for patients without the need to book an appointment in advance to treat acute diseases and injuries that do not need ED service and provide care for chronic conditions. This study aimed to assess the patients's level of awareness regarding UCCs in the Al-Ahsa region and provide information contributing to decision-makers' support about the urgent care services and their patterns of use within primary healthcare. Methods A descriptive cross-sectional study was conducted in the Al-Ahsa region from August 2023 to December 2023. A validated questionnaire was used. Cluster sampling was used to select three primary healthcare centers from four health sectors (southern cluster, middle cluster, northern cluster, and eastern cluster), and then simple random sampling was used to select participants. sample size calculated by Cochran's sample size formula, which estimated 377 participants. However, to accommodate a non-response rate of 10.0% and stronger statistical power and effect size, the final sample size was 469 participants. Data were analyzed by SPSS Statistics version 28 (IBM Corp. Released 2021. IBM SPSS Statistics for Windows, Version 28.0. Armonk, NY: IBM Corp.). Both descriptive and inferential statistics were used. A p-value ≤0.05 is considered statistically significant. Results Of the 469 participants in the study, more than half (54.8%) were aged between 18 and 38 years old, and more than half (54.8%) were male. More than half (67.4%) reported having no chronic diseases, whereas the most common chronic diseases reported were diabetes mellitus (11.9%) and hypertension (14.3%). Most of the participants (84.9%) weren't aware of UCCs. Among the participants who were aware of UCCs (n=71), 53.5% of them had visited a UCC in the last three months. The most common reasons for their visits were the common cold (40.8%), headaches (5.6%), and abdominal pain (5.6%). More than one-third of participants (38.6%) believed that UCCs provide services like those of the emergency center. According to patients' sex, there was a significant (0.031) difference in the awareness level; the highest was among females at 20.1% vs. 12.6%. Conclusion The study revealed that the majority of the participants were unaware of UCCs. Increasing patients' awareness of UCCs is necessary through different media to improve access to healthcare services and reduce overcrowding in the ED that is caused by non-urgent problems.

Additional Value From Free-Text Diagnoses in Electronic Health Records: Hybrid Dictionary and Machine Learning Classification Study

BACKGROUND

Physicians are hesitant to forgo the opportunity of entering unstructured clinical notes for structured data entry in electronic health records. Does free text increase informational value in comparison with structured data?

OBJECTIVE

This study aims to compare information from unstructured text-based chief complaints harvested and processed by a natural language processing (NLP) algorithm with clinician-entered structured diagnoses in terms of their potential utility for automated improvement of patient workflows.

METHODS

Electronic health records of 293,298 patient visits at the emergency department of a Swiss university hospital from January 2014 to October 2021 were analyzed. Using emergency department overcrowding as a case in point, we compared supervised NLP-based keyword dictionaries of symptom clusters from unstructured clinical notes and clinician-entered chief complaints from a structured drop-down menu with the following 2 outcomes: hospitalization and high Emergency Severity Index (ESI) score.

RESULTS

Of 12 symptom clusters, the NLP cluster was substantial in predicting hospitalization in 11 (92%) clusters; 8 (67%) clusters remained significant even after controlling for the cluster of clinician-determined chief complaints in the model. All 12 NLP symptom clusters were significant in predicting a low ESI score, of which 9 (75%) remained significant when controlling for clinician-determined chief complaints. The correlation between NLP clusters and chief complaints was low (r=-0.04 to 0.6), indicating complementarity of information.

CONCLUSIONS

The NLP-derived features and clinicians' knowledge were complementary in explaining patient outcome heterogeneity. They can provide an efficient approach to patient flow management, for example, in an emergency medicine setting. We further demonstrated the feasibility of creating extensive and precise keyword dictionaries with NLP by medical experts without requiring programming knowledge. Using the dictionary, we could classify short and unstructured clinical texts into diagnostic categories defined by the clinician.

Evaluation of different machine learning algorithms for predicting the length of stay in the emergency departments: a single-centre study

Background

Recently, crowding in emergency departments (EDs) has become a recognised critical factor impacting global public healthcare, resulting from both the rising supply/demand mismatch in medical services and the paucity of hospital beds available in inpatients units and EDs. The length of stay in the ED (ED-LOS) has been found to be a significant indicator of ED bottlenecks. The time a patient spends in the ED is quantified by measuring the ED-LOS, which can be influenced by inefficient care processes and results in increased mortality and health expenditure. Therefore, it is critical to understand the major factors influencing the ED-LOS through forecasting tools enabling early improvements.

Methods

The purpose of this work is to use a limited set of features impacting ED-LOS, both related to patient characteristics and to ED workflow, to predict it. Different factors were chosen (age, gender, triage level, time of admission, arrival mode) and analysed. Then, machine learning (ML) algorithms were employed to foresee ED-LOS. ML procedures were implemented taking into consideration a dataset of patients obtained from the ED database of the "San Giovanni di Dio e Ruggi d'Aragona" University Hospital (Salerno, Italy) from the period 2014-2019.

Results

For the years considered, 496,172 admissions were evaluated and 143,641 of them (28.9%) revealed a prolonged ED-LOS. Considering the complete data (48.1% female vs. 51.9% male), 51.7% patients with prolonged ED-LOS were male and 47.3% were female. Regarding the age groups, the patients that were most affected by prolonged ED-LOS were over 64 years. The evaluation metrics of Random Forest algorithm proved to be the best; indeed, it achieved the highest accuracy (74.8%), precision (72.8%), and recall (74.8%) in predicting ED-LOS.

Conclusions

Different variables, referring to patients' personal and clinical attributes and to the ED process, have a direct impact on the value of ED-LOS. The suggested prediction model has encouraging results; thus, it may be applied to anticipate and manage ED-LOS, preventing crowding and optimising effectiveness and efficiency of the ED.

Safety and Feasibility of an Emergency Department-to-Outpatient Pathway for Patients With TIA and Nondisabling Stroke

Background and Objectives

Evaluation of transient ischemic attack/nondisabling ischemic strokes (TIA/NDS) in the emergency department (ED) contributes to capacity issues and increasing health care expenditures, especially high-cost duplicative imaging.

Methods

As an institutional quality improvement project, we developed a novel pathway to evaluate patients with TIA/NDS in the ED using a core set of laboratory tests and CT-based neuroimaging. Patients identified as 'low risk' through a safety checklist were discharged and scheduled for prompt outpatient tests and stroke clinic follow-up. In this prespecified analysis designed to assess feasibility and safety, we abstracted data from patients consecutively enrolled in the first 6 months.

Results

We compared data from 106 patients with TIA/NDS enrolled in the new pathway from April through September 2020 (age 67.9 years, 45% female), against 55 unmatched historical controls with TIA encountered from April 2016 through March 2017 (age 68.3 years, 47% female). Both groups had similar median NIHSS scores (pathway and control 0) and ABCD2 scores (pathway and control 3). Pathway-enrolled patients had a 44% decrease in mean ED length of stay (pathway 13.7 hours, control 24.4 hours, p < 0.001) and decreased utilization of ED MRI-based imaging (pathway 63%, control 91%, p < 0.001) and duplicative ED CT plus MRI-based brain and/or vascular imaging (pathway 35%, control 53%, p = 0.04). Among pathway-enrolled patients, 89% were evaluated in our stroke clinic within a median of 5 business days; only 5.5% were lost to follow-up. Both groups had similar 90-day rates of ED revisits (pathway 21%, control 18%, p = 0.84) and recurrent TIA/ischemic stroke (pathway 1%, control 2%, p = 1.0). Recurrent ischemic events among pathway-enrolled patients were attributed to errors in following the safety checklist before discharge.

Discussion

Our TIA/NDS pathway, implemented during the initial outbreak of COVID-19, seems feasible and safe, with significant positive impact on ED throughput and ED-based high-cost duplicative imaging. The safety checklist and option of virtual telehealth follow-up are novel features. Broader adoption of such pathways has important implications for value-based health care.

A Physiotherapy-Led Transition to Home Intervention for Older Adults Following Emergency Department Discharge: A Pilot Feasibility Randomised Controlled Trial (ED PLUS)

Background

Older adults frequently attend the emergency department (ED) and experience high rates of subsequent adverse outcomes including functional decline, ED re-presentation and unplanned hospital admission. The development of effective interventions to prevent such outcomes is a key priority for research and service provision. Our aim was to evaluate the feasibility of a physiotherapy-led integrated care intervention for older adults discharged from the ED (ED PLUS).

Patients and Methods

Older adults presenting to the ED of a university teaching hospital with undifferentiated medical complaints and discharged within 72 hours were computer randomised in a ratio of 1:1:1 to deliver usual care, Comprehensive Geriatric Assessment (CGA) in the ED, or ED PLUS. ED PLUS is an evidence-based and stakeholder-informed intervention to bridge the care transition between the ED and community by initiating a CGA in the ED and implementing a six-week, multi-component, self-management programme in the patient's home. Feasibility and acceptability were assessed quantitatively and qualitatively. All clinical and process outcomes were assessed by a research nurse blinded to group allocation. Data analyses were primarily descriptive.

Results

Twenty-nine participants were recruited indicating a 67% recruitment rate. At 6 months, there was 100% retention in the usual care group, 88% in the CGA group and 90% in the ED PLUS group. ED PLUS participants expressed positive feedback, and there was a trend towards improved function and quality of life and less ED revisits and unscheduled hospitalisations in the ED PLUS group.

Conclusion

ED PLUS bridges the transition of care between the index visit to the ED and the community and is feasible using systematic recruitment strategies. Despite recruitment challenges in the context of COVID-19, the intervention was successfully delivered and well received by participants. There was a lower incidence of functional decline and improved quality of life in the ED PLUS group.

Trial Registration

The trial was registered in Clinical Trials Protocols and Results System as of 21st July 2021, with registration number NCT04983602.

Development of a machine learning-based acuity score prediction model for virtual care settings

OBJECTIVE

Healthcare is increasingly digitized, yet remote and automated machine learning (ML) triage prediction systems for virtual urgent care use remain limited. The Canadian Triage and Acuity Scale (CTAS) is the gold standard triage tool for in-person care in Canada. The current work describes the development of a ML-based acuity score modelled after the CTAS system.

METHODS

The ML-based acuity score model was developed using 2,460,109 de-identified patient-level encounter records from three large healthcare organizations (Ontario, Canada). Data included presenting complaint, clinical modifiers, age, sex, and self-reported pain. 2,041,987 records were high acuity (CTAS 1-3) and 416,870 records were low acuity (CTAS 4-5). Five models were trained: decision tree, k-nearest neighbors, random forest, gradient boosting regressor, and neural net. The outcome variable of interest was the acuity score predicted by the ML system compared to the CTAS score assigned by the triage nurse.

RESULTS

Gradient boosting regressor demonstrated the greatest prediction accuracy. This final model was tuned toward up triaging to minimize patient risk if adopted into the clinical context. The algorithm predicted the same score in 47.4% of cases, and the same or more acute score in 95.0% of cases.

CONCLUSIONS

The ML algorithm shows reasonable predictive accuracy and high predictive safety and was developed using the largest dataset of its kind to date. Future work will involve conducting a pilot study to validate and prospectively assess reliability of the ML algorithm to assign acuity scores remotely.

Diagnostic and Cost Efficiency of the 0-h/1-h Rule-out and Rule-in Algorithm for Patients With Chest Pain in the Emergency Department

BACKGROUND

This study investigated the economic impact of the European Society of Cardiology (ESC) clinical practice guideline recommendation of using the 0-h/1-h rule-out and rule-in algorithm with high-sensitivity cardiac troponin assays (0/1-h algorithm) to triage patients presenting with chest pain.Methods and Results: This post hoc cost-effectiveness evaluation (DROP-ACS; UMIN000030668) used deidentified electronic medical records from health insurance claims from 2 diagnostic centers in Japan. A cost-effectiveness analysis was conducted with 472 patients with care provided following the 0/1-h algorithm (Hospital A) and 427 patients following point-of-care testing (Hospital B). The clinical outcome of interest was all-cause mortality or subsequent myocardial infarction within 30 days of the index presentation. The sensitivity and specificity for the clinical outcome were 100% (95% confidence interval [CI] 91.1-100%) and 95.0% (95% CI 94.3-95.0%), respectively, in Hospital A and 92.9% (95% CI 69.6-98.7%) and 89.8% (95% CI 89.0-90.0%), respectively, in Hospital B. If the diagnostic accuracy of the 0/1-h algorithm was implemented in Hospital B, it is expected that the number of urgent (<24-h) coronary angiograms would decrease by 50%. Incorporating this assumption, implementing the 0/1-h algorithm could potentially reduce medical costs by JPY4,033,874 (95% CI JPY3,440,346-4,627,402) in Hospital B (JPY9,447 per patient; 95% CI JPY 8,057-10,837 per patient).

CONCLUSIONS

The ESC 0/1-h algorithm was efficient for risk stratification and for reducing medical costs.

Non-urgent presentations to the paediatric emergency department: a literature review

It is estimated that between 58% and 82% of children and young people who present to paediatric emergency department (PEDs) have a non-urgent condition. This systematic review of the literature explores why parents of children with non-urgent conditions present to the PED rather than to community healthcare services. Five databases were searched for studies on children and young people's presentations to the PED for the treatment of a non-urgent condition, as identified by a low priority triage code. This article describes and discusses the findings of the 18 included studies.

Appropriateness of packed red blood cells transfusions in chronic anemic patients in the emergency department: the TRANSFUS-ED retrospective analysis

Patients suffering from chronic anemia can benefit from scheduled transfusions of packed red blood cells (PRBCs), while urgent transfusions have specific indications. These patients frequently seek medical attention in the emergency department (ED), where they can be inappropriately transfused, but research in this field is limited. This study aimed to assess the appropriateness of PRBCs transfusions in chronic anemic patients in the ED. A retrospective analysis was performed on patients who accessed the ED of the Azienda Ospedaliera di Padova (Padova, Italy) between 2016 and 2019 and received PRBCs transfusions. Patients aged ≥ 18 years old and with chronic anemia were included, while those with acute anemia or admitted to the hospital after the transfusion were excluded. Chronic anemia was defined as satisfying one of the following in the past medical history: diagnosis of chronic anemia; two or more previous blood samplings demonstrating anemia; periodic transfusions. As primary outcome, the appropriateness of transfusions was assessed according to the American Association of Blood Banks (AABB) 2016 criteria, using the recommended threshold of 7 g/dL for hemodynamically stable adults and 8 g/dL for patients with pre-existing cardiovascular disease. Out of 1153 transfusions, 344 transfusions were included in the study. According to our criteria, 139 (40.4%) patients were inappropriately transfused, resulting in a total estimated cost of 54,528.71 € in the study period. This study showed that transfusions in chronic anemic patients are recurrent events in the ED and are frequently inappropriate. A possible explanation could be the lack of a well-structured primary care network granting periodic transfusions in ambulatory centers. In the future, implementing and improving chronic anemic patients' access to transfusion services through dedicated pathways could reduce the burden on the ED and also decrease costs.

Comparing effects and application of telemedicine for different specialties in emergency medicine using the Emergency Talk Application (U-Sim ETA Trial)

Telemedicine as a technology can support processes in the field of emergency medicine (EM) including therapies and diagnostics, but technically is often based on hardware solutions for local EM structures, especially when involving the field of pre-hospital EM. By developing an open-source, data protection compliant solution (EU GDPR and HIPAA) as well as using standardized web and open-source based technology the Emergency Talk Application (ETA) can be used as a technology that can connect emergency medical providers and include already available regional structures. By actively involving patients and connecting these with emergency or urgent care physicians ETA can be used not only as a teleconsultation system for paramedics and physicians, but in a wider network. Randomised simulation trial, comparing EM scenarios from the field of internal medicine, trauma and neurology. Participants were qualified as certified paramedics or emergency physicians (EP). Paramedics performed as ambulances crews and involved an EP if needed via ETA as Tele-Emergency Physicians (TEP). EP participated from a device of their choice, while being able to stay within their clinical workspace. From 141 scenarios 129 used ETA. Significant differences were found for the length of scenarios, duration of time the TEP was on scene, TEP arrival after scenario start, duration until TEP was called and the duration until a diagnosis was made. Also a strong positive and significant correlation between duration of the scenario and the time a TEP was bound could be described. Telemedicine is a technology that is increasingly used in the field of EM. Improving the use of telemedicine by using up-to date technology while allowing an integration of available technical and human resources is a challenge in the field of emergency medicine especially with its regional but also broad medical variety. When using one technical solution, understanding that different cases need a different medical and also telemedical approach can help in the understanding and improving therapies, diagnostics but also the involved processes and solutions. Such results are not only relevant for healthcare providers but especially by law and decision makers as to which type of solution could be introduced in each regional setting.

Experience-based codesign approach to improve care in Australian emergency departments for complex consumer cohorts: the MyED project protocol, Stages 1.1-1.3

INTRODUCTION

Emergency department (ED) care must adapt to meet current and future demands. In Australia, ED quality measures (eg, prolonged length of stay, re-presentations or patient experience) are worse for older adults with multiple comorbidities, people who have a disability, those who present with a mental health condition, Indigenous Australians, and those with a culturally and linguistically diverse (CALD) background. Strengthened ED performance relies on understanding the social and systemic barriers and preferences for care of these different cohorts, and identifying viable solutions that may result in sustained improvement by service providers. A collaborative 5-year project (MyED) aims to codesign, with ED users and providers, new or adapted models of care that improve ED performance, improve patient outcomes and improve patient experience for these five cohorts.

METHODS AND ANALYSIS

Experience-based codesign using mixed methods, set in three hospitals in one health district in Australia. This protocol introduces the staged and incremental approach to the whole project, and details the first research elements: ethnographic observations at the ED care interface, interviews with providers and interviews with two patient cohorts-older adults and adults with a CALD background. We aim to sample a diverse range of participants, carefully tailoring recruitment and support.

ETHICS AND DISSEMINATION

Ethics approval has been obtained from the Western Sydney Local Health District Human Research Ethics Committee (2022/PID02749-2022/ETH02447). Prior informed written consent will be obtained from all research participants. Findings from each stage of the project will be submitted for peer-reviewed publication. Project outputs will be disseminated for implementation more widely across New South Wales, Australia.

Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages

Overcrowding of emergency department (ED) has put a strain on national healthcare systems and adversely affected the clinical outcomes of critically ill patients. Early identification of critically ill patients prior to ED visits can help induce optimal patient flow and allocate medical resources effectively. This study aims to develop ML-based models for predicting critical illness in the community, paramedic, and hospital stages using Korean National Emergency Department Information System (NEDIS) data. Random forest and light gradient boosting machine (LightGBM) were applied to develop predictive models. The predictive model performance based on AUROC in community stage, paramedic stage, and hospital stage was estimated to be 0.870 (95% CI: 0.869-0.871), 0.897 (95% CI: 0.896-0.898), and 0.950 (95% CI: 0.949-0.950) in random forest and 0.877 (95% CI: 0.876-0.878), 0.899 (95% CI: 0.898-0.900), and 0.950 (95% CI: 0.950-0.951) in LightGBM, respectively. The ML models showed high performance in predicting critical illness using variables available at each stage, which can be helpful in guiding patients to appropriate hospitals according to their severity of illness. Furthermore, a simulation model can be developed for proper allocation of limited medical resources.

'But what if you miss something …?': factors that influence medical student consideration of cost in decision making

CONTEXT

Cost-conscious care is critical for healthcare sustainability but evidence suggests that most doctors do not consider cost in their clinical decision making. A critical step in changing this is understanding the barriers to encouraging behaviours and attitudes related to cost-conscious care. We therefore conducted a qualitative study to address the research question: what factors influence consideration of cost in emergency medicine (ED) clinical decision making?

METHODS

This was a qualitative focus group study using patient vignettes to explore attitudes towards cost-conscious clinical decision making. Participants were Year 4 and Year 5 medical students from Singapore, a country with a fee-for-service healthcare system. After a data-driven initial data analysis, and to make sense of a multitude of factors impacting on cost conscious care, we selected Fishbein's integrative model of behavioural prediction to underpin secondary data analysis.

RESULTS

Via four focus groups with 21 participants, we identified five main themes relevant to the integrative model of behavioural prediction. These were: attitudes towards considering cost when managing a patient (e.g., "better safe than sorry"); normative beliefs (e.g., doing what others do, perceptions of patient wishes); efficacy beliefs (e.g., no authority to take decisions or challenge); skills and knowledge (e.g., little knowledge of costs), and environmental constraints (e.g., the nature of the healthcare system).

DISCUSSION

Medical students do not consider cost in their clinical decision making due to numerous factors, of which lack of knowledge of costs is but one. While some of the factors identified reflect those found in previous studies with residents and fully-trained staff, and in other contexts, theory driven analysis added value in that it facilitated a richer exploration of why students do not consider cost in clinical decision making. Our findings provide insight to inform how best to engage and empower educators and learners in teaching and learning about cost-conscious care.

Throughput delays: causes, predictors, and outcomes - observational cohort in a Swiss emergency department

BACKGROUND

Optimal throughput times in emergency departments can be adjudicated by emergency physicians. Emergency physicians can also define causes of delays during work-up, such as waiting for imaging, clinical chemistry, consultations, or exit blocks. For adequate streaming, the identification of predictors of delays is important, as the attribution of resources depends on acuity, resources, and expected throughput times.

OBJECTIVE

This observational study aimed to identify the causes, predictors, and outcomes of emergency physician-adjudicated throughput delays.

METHODS

Two prospective emergency department cohorts from January to February 2017 and from March to May 2019 around the clock in a tertiary care centre in Switzerland were investigated. All consenting patients were included. Delay was defined as the subjective adjudication of the responsible emergency physician regarding delay during emergency department work-up. Emergency physicians were interviewed for the occurrence and cause of delays. Baseline demographics, predictor values, and outcomes were recorded. The primary outcome - delay - was presented using descriptive statistics. Univariable and multivariable logistic regression analyses were performed to assess the associations between possible predictors and delays and hospitalization, intensive care, and death with delay.

RESULTS

In 3656 (37.3%) of 9818 patients, delays were adjudicated. The patients with delays were older (59 years, interquartile range [IQR]: 39-76 years vs 49 years, IQR: 33-68 years) and more likely had impaired mobility, nonspecific complaints (weakness or fatigue), and frailty than the patients without delays. The main causes of delays were resident work-up (20.4%), consultations (20.2%), and imaging (19.4%). The predictors of delays were an Emergency Severity Index of 2 or 3 at triage (odds ratio [OR]: 3.00; confidence interval [CI]: 2.21-4.16; OR: 3.25; CI: 2.40-4.48), nonspecific complaints (OR: 1.70; CI: 1.41-2.04), and consultation and imaging (OR: 2.89; CI: 2.62-3.19). The patients with delays had an increased risk for admission (OR: 1.56; CI: 1.41-1.73) but not for mortality than those without delays.

CONCLUSION

At triage, simple predictors such as age, immobility, nonspecific complaints, and frailty may help to identify patients at risk of delay, with the main reasons being resident work-up, imaging, and consultations. This hypothesis-generating observation will allow the design of studies aimed at the identification and elimination of possible throughput obstacles.

Examining Indigenous emergency care equity projects: a scoping review protocol

INTRODUCTION

Indigenous peoples across the globe face inequitable access to high-quality care. Emergency departments are the first point of access for many Indigenous peoples and are the interface between the individual and the healthcare system. There is a reliance on emergency services due to a lack of primary healthcare, a history of mistreatment from providers and increased disease complexity. As such, a potential place for health equity reform is within these departments and other acute care settings. It is the purpose of this review to determine what projects have occurred that address emergency care inequities in four countries such as Australia, Canada, New Zealand and the USA and explore their successes and failures.

METHODS AND ANALYSIS

Using search strategies developed with a research librarian, publications will be identified from indexed databases including Medline, Embase, Web of Science, Cochrane Central, CINAHL and Scopus. Grey literature will also be searched and scanned for inclusion. To be included in the review, articles must describe interventions developed to address Indigenous health equity occurring within emergency care settings. Articles will include both programme descriptions and programme evaluations and be quality appraised by analysing study design and Indigenous research methodologies.

ETHICS AND DISSEMINATION

This review does not require ethics approval. This protocol describes a review that attempts to map Indigenous health equity interventions taking place within emergency care settings. It will contribute to Indigenous health scholarship and equity research. Results will be made available in multiple dissemination methods to ensure accessibility by researchers and community members.

Integrating the clinical frailty scale with emergency department triage systems for elder patients: A prospective study

BACKGROUND

This prospective study investigated whether integrating the Clinical Frailty Scale (CFS) with a triage system would improve triage for older adult emergency department (ED) patients.

METHODS

We enrolled ED patients aged 65 years or older at 5 study sites in Taiwan between December 2020 and April 2021. All eligible patients were assigned a triage level by using the Taiwan Triage and Acuity Scale (TTAS) in accordance with usual practice. A CFS score was collected from them. The primary outcome was critical events, defined as ICU admission or in-hospital mortality. The secondary outcomes were ED medical expenditures, number of orders in the ED, and length of hospital stay (LOS). We applied a reclassification concept and integrated the CFS and TTAS to create the Triage Frailty Acuity Scale (TFAS). We compared the outcomes achieved between the TTAS and TFAS.

RESULTS

Of 1023 screened ED patients, 890 were enrolled. The majority were assigned to TTAS level 3 (73.26%) and had CFS scores of 4 to 9 (55.96%). The primary outcomes were better predicted by the TFAS than the TTAS (area under the curve [AUC] 0.82 vs. 064). Using multivariable approach, TTAS level 1 (odds ratio [OR], 4.8; 95% confidence interval [CI], 1.7-13.4) and CFS score (OR, 5.8; 95% CI, 1.9-17.2) were significantly associated with the primary outcomes. For older adults at the highest triage level, the TFAS was not associated with an increase in the primary outcomes compared with the TTAS; however, the TFAS was associated with a significant decrease in the number of older ED patients assigned to triage levels 3 to 5. In addition, TFAS had a longer average LOS but did not have a higher average number of orders or ED medical expenditures compared to TTAS.

CONCLUSIONS

The TFAS identified more older ED patients who had been triaged as less emergent but proceeded to need ICU admission or in-hospital death. Incorporating the CFS into triage may reduce the under-triage of older adults in the ED.

Detecting Distal Radius Fractures Using a Segmentation-Based Deep Learning Model

Deep learning algorithms can be used to classify medical images. In distal radius fracture treatment, fracture detection and radiographic assessment of fracture displacement are critical steps. The aim of this study was to use pixel-level annotations of fractures to develop a deep learning model for precise distal radius fracture detection. We randomly divided 3785 consecutive emergency wrist radiograph examinations from six hospitals to a training set (3399 examinations) and test set (386 examinations). The training set was used to develop the deep learning model and the test set to assess its validity. The consensus of three hand surgeons was used as the gold standard for the test set. The area under the ROC curve was 0.97 (CI 0.95-0.98) and 0.95 (CI 0.92-0.98) for examinations without a cast. Fractures were identified with higher accuracy in the postero-anterior radiographs than in the lateral radiographs. Our deep learning model performed well in our multi-hospital and multi-radiograph system manufacturer settings. Thus, segmentation-based deep learning models may provide additional benefit. Further research is needed with algorithm comparison and external validation.

An integrative review of adult patient-reported reasons for non-urgent use of the emergency department

OBJECTIVE

To conduct an integrative review of the scientific literature to explore adult patient-reported reasons for using the emergency department (ED) non-urgently.

METHOD

A literature search of CINAHL, Cochrane, Embase, PsycINFO, and MEDLINE was conducted with filters for humans, published January 1, 1990-September 1, 2021, and English language. Methodological quality was assessed using Critical Appraisal Skills Programme Qualitative Checklist for qualitative and National Institutes Health (NIH) Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies for quantitative studies. Data was abstracted on study and sample characteristics, and themes/reasons for ED use. Cited reasons were coded using thematic analysis.

RESULTS

Ninety-three studies met inclusion criteria. Seven themes were found: need to be risk averse with respect to the health issue; knowledge and awareness of alternative sources of care; dissatisfaction with primary care provider; satisfaction with ED; ED accessibility and convenience resulting in low access burden; referred to the ED by others; and relationships between patients and health care providers.

DISCUSSION

This integrative review examined patient-reported reasons for attending the ED on a non-urgent basis. The results suggest that ED patients are heterogenous and many factors influence their decision-making. Considering the complexity with which patients live, treating them as a single entity may be problematic. Limiting excessive non-urgent visits likely requires a multi-pronged approach.

CONCLUSION

For many ED patients, they have a very clear problem which needed to be addressed. Future studies should explore psychosocial factors driving decision-making (e.g., health literacy, health-related personal beliefs, stress and coping ability).

Lived Experience of Caring for Dying Muslim Patients in Emergency Room: A Phenomenological Study

Death is a natural part of life, which mostly occurs in the ER. This study described the meaning of nurses' lived experience of caring for critical and dying patients in the ERs. In this qualitative study, 13 nurses who was purposefully selected. Data were collected using in-depth individual interviews. Data analysis used van Manen's hermeneutic phenomenological approach. The experiences of caring for the dying patient were divided into two parts: experiences in patients with acute and chronic problems. In patients with acute problems, four themes were extracted: fight to the death, no time for palliative and spiritual care, lacking support for the family, no privacy for peaceful death. In patients with acute problems, four themes were extracted: Facilitating a peaceful death, Allocating time for palliative and spiritual care, support for the family, Attention to privacy. Therefore, attention should be paid to the fields of care and its inadequacies.

Evaluation of prognostic scoring systems in patients hospitalized from the emergency department in a low-income region: northern Syria after internal turmoil as a different universe

BACKGROUND

In low-income or underdeveloped countries with conflict and internal unrest, healthcare facilities and staff are limited. For these reasons, it is necessary to use the most straightforward scoring systems to ensure that health facilities and staff are used effectively and to expedite processes through early and effective interventions for patients. In this study, we evaluate and compare the scoring systems used to predict patient prognosis for Emergency Department (ED) patients in northern Syria, which is an area marred by conflict and internal unrest.

METHODS

In this study, patients hospitalized in the Afrin, Azez Vatan, Jarablus, Tel Abyad, Rasulayn, El Bab, and Çobanbey hospitals in northern Syria were investigated. Only patients that were hospitalized in the emergency departments of these hospitals, including wards and intensive care units, were included in the study. Patients that were hospitalized from 03/01/2021 to 08/31/2021, the study period, were prospectively analyzed. Vital signs, medical histories and demographic data of the patients were recorded by calculating National Early Warning Score 2 (NEWS2), Rapid Acute Physiology Score (RAPS), Rapid Emergency Medicine Score (REMS), and HOTEL Score (hypotension, oxygen saturation, low temperature, electrocardiogram, loss of independence). Acceptance parameters and scores were analyzed using statistical methods and by comparing groups.

RESULTS

: All four scoring systems were found to be effective in predicting mortality regarding ROC curve analysis. However, the statistical significance of the RAPS was slightly stronger than that of the other scores and REMS had the highest sensitivity and specificity amongst the four systems, at 86.2% and 84.1%, respectively. Regarding the risk of hospitalization in the ICU (p < 0.05), the sensitivity values of the cut-off values offered by the scoring systems remained below 0.70 regarding ROC curve analysis. RAPS had the highest sensitivity (65.2%) of the four systems with a cut-off value of 1.5.

DISCUSSION

This study in northern Syria has shown that although RAPS had stronger statistical power, REMS had better sensitivity and specificity for the prediction of mortality. Additionally, RAPS had better sensitivity for ICU risk. This study will contribute to the evaluation of healthcare in similar regions and to cost-effective healthcare delivery by using scoring systems for ED patients' admission.

The preanalytical process in the emergency department, a European survey

OBJECTIVES

Clinical decision-making in emergency medicine is under constant pressure from demand and performance requirements, with blood tests being a fundamental part of this. However, the preanalytical process has received little attention. Therefore, this study aimed to investigate the quality of preanalytical phase processes in European emergency departments (EDs) from the perspectives of the three main providers: clinicians, nurses, and laboratory specialists.

METHODS

This online survey, distributed among European EDs and laboratories, was supported by the European Society for Emergency Nursing (EUSEN), European Society for Emergency Medicine (EuSEM), and the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM). The size of the centres, the European region, the responder's profession and the country's economic condition were used as co-variables.

RESULTS

We included 376 responses from all ED-related professions from 306 European centres. In 66.9% of all ED visits, at least one blood test was performed. Tests were requested mostly by nurses (44.6%) using electronic Order/Entry systems (65.4%). Only a minority (19%) reported not using laboratory quality indicators (QIs). Most responders defined the TAT starting point "when the laboratory receives the sample" (66.1%), defining the goal to be "less than 60 min" (69.9%), but only 42.4% of the centres estimated achieving this goal.

CONCLUSIONS

Our survey illustrates the current situation on preanalytical blood sample processing in European EDs from the clinical and laboratory perspectives. The results emphasise the importance of the IT infrastructure and QI usage in this process and highlight some differences between European regions.

Lean Six Sigma to reduce the acute myocardial infarction mortality rate: a single center study

Purpose

Cardiovascular diseases are the leading cause of death worldwide. In Italy, acute myocardial infarction (AMI) is a major cause of hospitalization and healthcare costs. AMI is a myocardial necrosis event caused by an unstable ischemic syndrome. The Italian government has defined an indicator called “AMI: 30-day mortality” to assess the quality of the overall care pathway of the heart attacked patient. In order to guarantee high standards, all hospitals had to implement techniques to increase the quality of care pathway. The aim of the paper is to identify the root cause and understand the mortality rate for AMI and redesign the patient management process in order to improve it.

Design/methodology/approach

A Lean Six Sigma (LSS) approach was used in this study to analyze the patient flow in order to reduce 30-days mortality rate from AMI registered by Complex Operative Unit (COU) of Cardiology of an Italian hospital. Value stream mapping (VSM) and Ishikawa diagrams were implemented as tools of analysis.

Findings

Process improvement using LSS methodology made it possible to reduce the overall times from 115 minutes to 75 minutes, with a reduction of 35%. In addition, the corrective actions such as the activation of a post-discharge outpatient clinic and telephone contacts allowed the 30-day mortality rate to be lowered from 16% before the project to 8% after the project. In this way, the limit value set by the Italian government was reached.

Research limitations/implications

The limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.

Practical implications

The LSS approach has brought significant benefits to the process of managing patients with AMI. Corrective actions such as the activation of an effective shared protocol or telephone interview with checklist can become the gold standard in reducing mortality. The limitation of the study is that it is single-centered and was applied to a facility with a limited number of cases.

Originality/value

LSS, applied for the first time to the management of cardiovascular diseases in Italy, is a methodology which has proved to be strategic for the improvement of healthcare process. The simple solutions implemented could serve as a guide for other hospitals to pursue the national AMI mortality target.

Effect of coronavirus (COVID-19) pandemic on orthopedic trauma patients presenting in the emergency department of a maximum care hospital and level 1 trauma center

INTRODUCTION

While overcrowding of emergency departments was often reported in the recent years, during the early phase of the pandemic, a reduction in patient numbers was seen. The aim of the current study was to describe the orthopedic trauma patient cohort presenting to the emergency department (ED) during the early pandemic period as compared to the cohort from the analogue time period 2019.

MATERIALS AND METHODS

A single-center case-control study was performed. All the consecutive orthopedic trauma patients > 12 years presenting to the ED were included. Patients in the same time period in 2019 served as the control group.

RESULTS

Compared to 2019, in 2020, 33% less patients presented in the emergency department. Patients treated in 2020 were significantly older, significantly more often brought to ED by emergency medical services and significantly more often admitted. The number of fractures and diagnoses requiring surgical treatment decreased only slightly and the proportion of these patients among all the patients was significantly higher during the pandemic than in the control period. Furthermore, a higher percentage of polytrauma patients could be found in 2020 as well. Analysis of Manchester Triage System showed significantly less not urgent patients in 2020.

CONCLUSION

The present study shows a significant decline in the number of patients treated in the ED during the pandemic period but at the same time almost identical numbers of patients with fractures or diagnoses requiring surgical treatment. In the context of an overall decline in patient numbers, a stronger concentration on level 1 trauma centers seems to be evident during the pandemic.

Implementation of Vertical Split Flow Model for Patient Throughput at a Community Hospital Emergency Department

BACKGROUND

Hospitals have implemented innovative strategies to address overcrowding by optimizing patient flow through the emergency department (ED). Vertical split flow refers to the concept of assigning patients to vertical chairs instead of horizontal beds based on patient acuity.

OBJECTIVE

Evaluate the impact of vertical split flow implementation on ED Emergency Severity Index (ESI) level 3, patient length of stay, and throughput at a community hospital.

METHODS

Retrospective cohort study of all ESI level 3 patients presenting to a community hospital ED over a 3-month period prior to and after vertical split flow implementation between 2018 and 2019.

RESULTS

In total, data were collected from 10,638 patient visits: 5262 and 5376 patient visits pre- and postintervention, respectively. There was a significant reduction in mean overall length of stay when ESI-3 patients were triaged with vertical split flow (251 min vs 283 min, p < 0.001).

CONCLUSIONS

Community hospital ED implementation of vertical split flow for ESI level 3 patients was associated with a significant reduction in overall length of stay and improved throughput. This model provides a solution to increase the number of patients that can be simultaneously cared for in the ED without increasing staffing or physical space.

Factors Affecting the Length of Stay in the Emergency Department in Psychiatric Emergency Patients in the COVID-19 Pandemic Context

To reduce overcrowding in emergency departments (ED), which is a serious international problem, it is important to reduce the length of ED stay (ED LOS) of emergency patients. In particular, due to the COVID 19 pandemic, psychiatric emergency patients spent much longer in ED. This study was conducted to identify the characteristics of psychiatric emergency patients who visited the ED during the COVID-19 pandemic and to identify factors affecting ED LOS. This retrospective study was conducted on adult patients aged 19 years or older who visited a psychiatric emergency center operated by an ED from 1 May 2020 to 31 April 2021 because of the COVID-19 pandemic. In this study, the average ED LOS of psychiatric emergency patients was 7.8 h. Factors affecting ED LOS for over 12 h were isolation (OR = 2.39, CI = 1.409-4.052), unaccompanied police officers (OR = 2.106, CI = 1.338-3.316), night-time visits (OR = 2.127, CI = 1.357-3.332), use of sedatives (OR = 1.671, CI = 1.030-2.713), and restraints (OR = 1.968, CI = 1.172-4.895). The ED LOS of psychiatric emergency patients is longer than that of general emergency patients, and a long ED LOS causes ED overcrowding. To reduce the ED LOS of psychiatric emergency patients, they must be accompanied by a police officer when visiting the ED, and the treatment process should be reorganized so that a psychiatrist can promptly intervene. Furthermore, it is necessary to reorganize the isolation guidelines and admission criteria for mental emergency patients.

Evaluation of the Validity and Reliability of ANKUTRIAGE, a New Decision Support System in Pediatric Emergency Triage

BACKGROUND

The intensity of emergency services is an increasing health problem all over the world, necessitating an effective triage system. The aim of this study was to evaluate the validity and reliability of the "ANKUTRIAGE" in children.

METHODS

This prospective, longitudinal study was carried out at a pediatric emergency department. ANKUTRIAGE, a 5-level computer-aided triage decision support system, was developed. Patients younger than 18 years who do not need emergency intervention, who had complete vital sign measurements, who gave consent for the study, and who were admitted to the emergency service during working hours with trained personnel were included. For validity, agreement between the urgency levels determined by ANKUTRIAGE and the reference triage systems: Pediatric Canadian Triage and Acuity Scale and Emergency Severity Index, was evaluated. In addition, the association of urgency levels with clinical outcomes was studied. To assess reliability, patients were evaluated by 2 blinded healthcare professionals using ANKUTRIAGE and a quadratic weighted κ was estimated.

RESULTS

A total of 1232 children with a median age of 4.00 years were included. ANKUTRIAGE acuity levels significantly correlated with the number of resources used, the number of patients undergoing life-saving procedures, pediatric intensive care unit, and overall hospitalization rates, respectively ( P < 0.001, P < 0.001, P < 0.001, P < 0.001). The agreement of ANKUTRIAGE with Pediatric Canadian Triage and Acuity Scale was found to be 0.94 (95% confidence interval [CI], 0.93-0.94), with an Emergency Severity Index of 0.75 (95% CI, 0.70-0.80). The interrater agreement between 2 evaluators who used ANKUTRIAGE reflected as excellent consistency 0.92 (95% CI, 0.89-0.95; κ > 0.8).

CONCLUSIONS

ANKUTRIAGE demonstrated high agreement with clinical outcomes and with proven triage systems and reflected high reliability between users. ANKUTRIAGE will enable a more standardized and practical triage, especially in crowded pediatric emergency departments and in situations where triage is performed by health professionals with different experience and professions.

Length-of-Stay in the Emergency Department and In-Hospital Mortality: A Systematic Review and Meta-Analysis

The effect of emergency department (ED) length of stay (EDLOS) on in-hospital mortality (IHM) remains unclear. The aim of this systematic review and meta-analysis was to determine the association between EDLOS and IHM. We searched the PubMed, Medline, Embase, Web of Science, Cochrane Controlled Register of Trials, CINAHL, PsycInfo, and Scopus databases from their inception until 14−15 January 2022. We included studies reporting the association between EDLOS and IHM. A total of 11,337 references were identified, and 52 studies (total of 1,718,518 ED patients) were included in the systematic review and 33 in the meta-analysis. A statistically significant association between EDLOS and IHM was observed for EDLOS over 24 h in patients admitted to an intensive care unit (ICU) (OR = 1.396, 95% confidence interval [CI]: 1.147 to 1.701; p < 0.001, I2 = 0%) and for low EDLOS in non-ICU-admitted patients (OR = 0.583, 95% CI: 0.453 to 0.745; p < 0.001, I2 = 0%). No associations were detected for the other cut-offs. Our findings suggest that there is an association between IHM low EDLOS and EDLOS exceeding 24 h and IHM. Long stays in the ED should not be allowed and special attention should be given to patients admitted after a short stay in the ED.

Assessing data gathering of chatbot based symptom checkers - a clinical vignettes study

BACKGROUND

The burden on healthcare systems is mounting continuously owing to population growth and aging, overuse of medical services, and the recent COVID-19 pandemic. This overload is also causing reduced healthcare quality and outcomes. One solution gaining momentum is the integration of intelligent self-assessment tools, known as symptom-checkers, into healthcare-providers' systems. To the best of our knowledge, no study so far has investigated the data-gathering capabilities of these tools, which represent a crucial resource for simulating doctors' skills in medical-interviews.

OBJECTIVES

The goal of this study was to evaluate the data-gathering function of currently available chatbot symptom-checkers.

METHODS

We evaluated 8 symptom-checkers using 28 clinical vignettes from the repository of MSD-Manual case studies. The mean number of predefined pertinent findings for each case was 31.8 ± 6.8. The vignettes were entered into the platforms by 3 medical students who simulated the role of the patient. For each conversation, we obtained the number of pertinent findings retrieved and the number of questions asked. We then calculated the recall-rates (pertinent-findings retrieved out of all predefined pertinent-findings), and efficiency-rates (pertinent-findings retrieved out of the number of questions asked) of data-gathering, and compared them between the platforms.

RESULTS

The overall recall rate for all symptom-checkers was 0.32(2,280/7,112;95 %CI 0.31-0.33) for all pertinent findings, 0.37(1,110/2,992;95 %CI 0.35-0.39) for present findings, and 0.28(1140/4120;95 %CI 0.26-0.29) for absent findings. Among the symptom-checkers, Kahun platform had the highest recall rate with 0.51(450/889;95 %CI 0.47-0.54). Out of 4,877 questions asked overall, 2,280 findings were gathered, yielding an efficiency rate of 0.46(95 %CI 0.45-0.48) across all platforms. Kahun was the most efficient tool 0.74 (95 %CI 0.70-0.77) without a statistically significant difference from Your.MD 0.69(95 %CI 0.65-0.73).

CONCLUSION

The data-gathering performance of currently available symptom checkers is questionable. From among the tools available, Kahun demonstrated the best overall performance.

Overcrowding analysis in emergency department through indexes: a single center study

Introduction

Overcrowding in the Emergency Department (ED) is one of the major issues that must be addressed in order to improve the services provided in emergency circumstances and to optimize their quality. As a result, in order to help the patients and professionals engaged, hospital organizations must implement remedial and preventative measures. Overcrowding has a number of consequences, including inadequate treatment and longer hospital stays; as a result, mortality and the average duration of stay in critical care units both rise. In the literature, a number of indicators have been used to measure ED congestion. EDWIN, NEDOCS and READI scales are considered the most efficient ones, each of which is based on different parameters regarding the patient management in the ED.

Methods

In this work, EDWIN Index and NEDOCS Index have been calculated every hour for a month period from February 9th to March 9th, 2020 and for a month period from March 10th to April 9th, 2020. The choice of the period is related to the date of the establishment of the lockdown in Italy due to the spread of Coronavirus; in fact on 9 March 2020 the Italian government issued the first decree regarding the urgent provisions in relation to the COVID-19 emergency. Besides, the Pearson correlation coefficient has been used to evaluate how much the EDWIN and NEDOCS indexes are linearly dependent.

Results

EDWIN index follows a trend consistent with the situation of the first lockdown period in Italy, defined by extreme limitations imposed by Covid-19 pandemic. The 8:00–20:00 time frame was the most congested, with peak values between 8:00 and 12:00. on the contrary, in NEDOCS index doesn’t show a trend similar to the EDWIN one, resulting less reliable. The Pearson correlation coefficient between the two scales is 0,317.

Conclusion

In this study, the EDWIN Index and the NEDOCS Index were compared and correlated in order to assess their efficacy, applying them to the case study of the Emergency Department of “San Giovanni di Dio e Ruggi d’Aragona” University Hospital during the Covid-19 pandemic. The EDWIN scale turned out to be the most realistic model in relation to the actual crowding of the ED subject of our study. Besides, the two scales didn’t show a significant correlation value.

Effects of Emergency Transfer Coordination Center on Length of Stay of Critically Ill Patients in the Emergency Department

Introduction: Critically ill patients are frequently transferred from other hospitals to the emergency departments (ED) of tertiary hospitals. Due to the unforeseen transfer, the ED length of stay (LOS) of the patient is likely to be prolonged in addition to other potentially adverse effects. In this study we sought to confirm whether the establishment of an organized unit — the Emergency Transfer Coordination Center (ETCC) — to systematically coordinate emergency transfers would be effective in reducing the ED LOS of transferred, critically ill patients. Methods: The present study is a retrospective observational study focusing on patients who were transferred from other hospitals and admitted to the intensive care unit (ICU) of the ED in a tertiary hospital located in northwestern Seoul, the capital city of South Korea, from January 2019 – December 2020. The exposure variable of the study was ETCC approval before transfer, and ED LOS was the primary outcome. We used propensity score matching for comparison between the group with ETCC approval and the control group. Results: Included in the study were 1,097 patients admitted to the ICU after being transferred from other hospitals, of whom 306 (27.9%) were transferred with ETCC approval. The median ED LOS in the ETCC-approved group was significantly reduced to 277 minutes compared to 385 minutes in the group without ETCC approval. The ETCC had a greater effect on reducing evaluation time than boarding time, which was the same for populations with different clinical features. Conclusion: An ETCC can be effective in systematically reducing the ED LOS of critically ill patients who are transferred from other hospitals to tertiary hospitals that are experiencing severe crowding.

Impact of COVID-19 pandemic on emergency department length of stay and clinical outcomes of patients with severe pneumonia: A single-center observational study

We examined the impact of COVID-19 pandemic on the emergency department length of stay (EDLOS) and clinical outcomes of patients with severe pneumonia admitted to the intensive care unit (ICU) through the emergency department (ED). This single-center retrospective observational study included adult patients with pneumonia admitted to the ICU through the ED between January and December 2019 (pre-pandemic) and between March 2020 and February 2021 (during-pandemic). We compared and analyzed the EDLOS by dividing it into pre-, mid-, and post-EDLOS and in-hospital mortality of patients with pneumonia admitted to the ICU according to the time of ED visits before and during the COVID-19 pandemic. Risk factors for in-hospital mortality according to the time of ED visits were analyzed using multiple logistic regression analysis. In total, 227 patients (73 patients pre-pandemic and 154 patients during the pandemic) with pneumonia admitted to the ICU through the ED were analyzed. During the COVID-19 pandemic, pre-, mid-, and post-EDLOS increased (P < .05), and the in-hospital mortality rate increased by 10.4%; however, this was not significant (P = .155). Multivariate logistic regression analysis revealed post-EDLOS (ED waiting time after making ICU admission decision) as an independent risk factor for in-hospital mortality of patients with pneumonia admitted to the ICU, pre-pandemic (odds ratio [OR] = 2.282, 95% confidence interval [CI]: 1.367-3.807, P = .002) and during the pandemic (OR = 1.126, 95% CI: 1.002-1.266, P = .047). Mid-EDLOS (ED time to assess, care, and ICU admission decision) was an independent risk factor for in-hospital mortality of patients with pneumonia admitted to the ICU during the COVID-19 pandemic (OR = 1.835, 95% CI: 1.089-3.092, P = .023). During the pandemic of emerging respiratory infectious diseases, to reduce in-hospital mortality of severe pneumonia patients, it is necessary to shorten the ED waiting time for admission by increasing the number of isolation ICU beds. It is also necessary to accelerate the assessment and care process in the ED, and make prompt decisions regarding admission to the ICU.

Impact of systematic medication review in emergency department on patients’ post-discharge outcomes—A randomized controlled clinical trial

Introduction

The main objective of this study was to investigate whether systematic medication review conducted by clinical pharmacists can impact clinical outcomes and post-discharge outcomes for patients admitted to the emergency department.

Method

This parallel group, non-blinded, randomized controlled trial was conducted in the emergency department, Diakonhjemmet Hospital, Oslo, Norway. The study was registered in ClinicalTrials.gov, Identifier: NCT03123640 in April 2017. From April 2017 to May 2018, patients ≥18 years were included and randomized (1:1) to intervention- or control group. The control group received standard care from emergency department physicians and nurses. In addition to standard care, the intervention group received systematic medication review including medication reconciliation conducted by pharmacists, during the emergency department stay. The primary outcome was proportion of patients with an unplanned contact with hospital within 12 months from inclusion stay discharge.

Results

In total, 807 patients were included and randomized, 1:1, to intervention or control group. After excluding 8 patients dying during hospital stay and 10 patients lacking Norwegian personal identification number, the primary analysis comprised 789 patients: 394 intervention group patients and 395 control group patients. Regarding the primary outcome, there was no significant difference in proportion of patients with an unplanned contact with hospital within 12 months after inclusion stay discharge between groups (51.0% of intervention group patients vs. 53.2% of control group patients, p = 0.546).

Conclusion

As currently designed, emergency department pharmacist-led medication review did not significantly influence clinical- or post-discharge outcomes. This study did, however pinpoint important practical implementations, which can be used to design tailored pharmacist-led interventions and workflow regarding drug-related issues in the emergency department setting.

Overcrowding in Emergency Department: Causes, Consequences, and Solutions—A Narrative Review

Overcrowding in Emergency Departments (EDs) is a phenomenon that is now widespread globally and causes a significant negative impact that goes on to affect the entire hospital. This contributes to a number of consequences that can affect both the number of resources available and the quality of care. Overcrowding is due to a number of factors that in most cases lead to an increase in the number of people within the ED, an increase in mortality and morbidity, and a decrease in the ability to provide critical services in a timely manner to patients suffering from medical emergencies. This phenomenon results in the Emergency Department reaching, and in some cases exceeding, its optimal capacity. In this review, the main causes and consequences involving this phenomenon were collected, including the effect caused by the SARS-CoV-2 virus in recent years. Finally, special attention was paid to the main operational strategies that have been developed over the years, strategies that can be applied both at the ED level (microlevel strategies) and at the hospital level (macrolevel strategies).

Nationwide study of the characteristics of frequent attenders with multiple emergency department attendance patterns

INTRODUCTION

The burden of frequent attenders (FAs) of emergency departments (EDs) on healthcare resources is underestimated when single-centre analyses do not account for utilisation of multiple EDs by FAs. We aimed to quantify the extent of multiple ED use by FAs and to characterise FAs.

METHODS

We reviewed nationwide ED attendance in Singapore data from 1 January 2006 to 31 December 2018 (13 years). FAs were defined as patients with ≥4 ED visits in any calendar year. Single ED FAs and multiple ED FAs were patients who attended a single ED exclusively and ≥2 distinct EDs within the year, respectively. Mixed ED FAs were patients who attended a mix of a single ED and multiple EDs in different calendar years. We compared the characteristics of FAs using multivariable logistic regression.

RESULTS

We identified 200,130 (6.3%) FAs who contributed to1,865,704 visits (19.6%) and 2,959,935 (93.7%) non-FAs who contributed to 7,671,097 visits (80.4%). After missing data were excluded, the study population consisted of 199,283 unique FAs. Nationwide-linked data identified an additional 15.5% FAs and 29.7% FA visits, in addition to data from single centres. Multiple ED FAs and mixed ED FAs were associated with male sex, younger age, Malay or Indian ethnicity, multiple comorbidities, median triage class of higher severity, and a higher frequency of ED use.

CONCLUSION

A nationwide approach is needed to quantify the national FA burden. The multiple comorbidities and higher frequency of ED use associated with FAs who visited multiple EDs and mixed EDs, compared to those who visited a single ED, suggested a higher level of ED burden in these subgroups of patients. The distinct characteristics and needs of each FA subgroup should be considered in future healthcare interventions to reduce FA burden.

Lessons from the frontline: Documenting the pandemic emergency care experience from the Pacific region - Infrastructure and equipment

Background

The COVID-19 pandemic highlighted challenges for all health systems worldwide. This research aimed to explore the impact of COVID-19 across the Pacific especially with regards to emergency care (EC) and clinicians' preparations and responses.

Methods

A collaboration of Australia and Pacific researchers conducted prospective qualitative research over 18 months of the pandemic. In this three phase study data were gathered from Emergency Clinicians and stakeholders through online support forums, in-depth interviews and focus groups. A phenomenological methodological approach was employed to explore the lived experience of participants. This paper discusses the findings of the study regarding the EC building block of 'Infrastructure and Equipment.'

Findings

Pre-existing infrastructure and equipment were not sufficient to help control the pandemic. Adequate space and correct equipment were essential needs for Pacific Island emergency clinicians, with donations, procurement and local ingenuity required for suitable, sustainable supplies and facilities. Adequate personal protective equipment (PPE) conferred a sense of security and increased Health Care Workers willingness to attend to patients.

Interpretation

Investing in adequate infrastructure and appropriate equipment is crucial for an effective response to the COVID-19 pandemic. The sustainability of such investments in the Pacific context is paramount for ongoing EC and preparation for future surge responses and disasters.

Funding

Phases 1 and 2A of this study were part of an Epidemic Ethics/World Health Organization (WHO) initiative, supported by Foreign, Commonwealth and Development Office/Wellcome Grant 214711/Z/18/Z. Co-funding for this research was received from the Australasian College for Emergency Medicine Foundation via an International Development Fund Grant.

Experimental Implementation of NSER Mobile App for Efficient Real-Time Sharing of Prehospital Patient Information With Emergency Departments: Interrupted Time-Series Analysis

Background

With the aging society, the number of emergency transportations has been growing. Although it is important that a patient be immediately transported to an appropriate hospital for proper management, accurate diagnosis in the prehospital setting is challenging. However, at present, patient information is mainly communicated by telephone, which has a potential risk of communication errors such as mishearing. Sharing correct and detailed prehospital information with emergency departments (EDs) should facilitate optimal patient care and resource use. Therefore, the implementation of an app that provides on-site, real-time information to emergency physicians could be useful for early preparation, intervention, and effective use of medical and human resources.

Objective

In this paper, we aimed to examine whether the implementation of a mobile app for emergency medical service (EMS) would improve patient outcomes and reduce transportation time as well as communication time by phone (ie, phone-communication time).

Methods

We performed an interrupted time-series analysis (ITSA) on the data from a tertiary care hospital in Japan from July 2021 to October 2021 (8 weeks before and 8 weeks after the implementation period). We included all patients transported by EMS. Using the mobile app, EMS can send information on patient demographics, vital signs, medications, and photos of the scene to the ED. The outcome measure was inpatient mortality and transportation time, as well as phone-communication time, which was the time for EMS to negotiate with ED staffs for transport requests.

Results

During the study period, 1966 emergency transportations were made (n=1033, 53% patients during the preimplementation period and n=933, 47% patients after the implementation period). The ITSA did not reveal a significant decrease in patient mortality and transportation time before and after the implementation. However, the ITSA revealed a significant decrease in mean phone-communication time between pre- and postimplementation periods (from 216 to 171 seconds; −45 seconds; 95% CI −71 to −18 seconds). From the pre- to postimplementation period, the mean transportation time from EMS request to ED arrival decreased by 0.29 minutes (from 36.1 minutes to 35.9 minutes; 95% CI −2.20 to 1.60 minutes), without change in time trends. We also introduced cases where the app allowed EMS to share accurate and detailed prehospital information with the emergency department, resulting in timely intervention and reducing the burden on the ED.

Conclusions

The implementation of a mobile app for EMS was associated with reduced phone-communication time by 45 seconds (22%) without increasing mortality or overall transportation time despite the implementation of new methods in the real clinical setting. In addition, real-time patient information sharing, such as the transfer of monitor images and photos of the accident site, could facilitate optimal patient care and resource use.