Emergency Department Overcrowding Research Articles

Health mediation does not reduce the readmission rate of frequent users of emergency departments living in precarious conditions: what lessons can be learned from this randomised controlled trial?

BackgroundSevere overcrowding of emergency departments (EDs) affects the quality of healthcare. One factor of overcrowding is precariousness, but it has rarely been considered a key factor in designing interventions to improve ED care. Health mediation (HM) aims to facilitate access to rights, prevention, and care for the most vulnerable persons and to raise awareness among healthcare providers about obstacles in accessing healthcare. The primary aim was to determine whether HM intervention for frequent users of EDs (FUED) living in precarious conditions could reduce the readmission rate at 90 days.MethodsBetween February 2019 and May 2022, we enrolled and interviewed 726 FUED in four EDs of southeastern France in this randomised controlled trial. The HM intervention started in the ED and lasted 90 days. In addition to the primary endpoint (first readmission at 90 days), secondary endpoints (readmission at 30 and 180 days, number of hospitalisations at 30, 90, 180 days, admissions for the same reasons as the first admission) were also studied. The outcomes were measured in the ED information systems. Statistical methods included an intention-to-treat analysis and a per-protocol analysis. Comparisons were adjusted for gender, age, ED, and health mediator.Results46% of patients reported attending the ED because they felt their life was in danger, and 42% had been referred to the ED by the emergency medical dispatch centre or their GP; 40% of patients were considered to be in a serious condition by ED physicians. The proportion of patients who were readmitted at 90 days was high but did not differ between the control and the HM intervention groups (31.7% vs. 36.3%, p = 0.23). There was no significant difference in any of the secondary outcome measures between the control and HM intervention groups. Per-protocol analysis also showed no significant difference for the primary and secondary endpoints.ConclusionsThis randomised controlled trial did not show that our health mediation intervention was effective in reducing the use of emergency services by FUED living in precarious conditions. Some limitations are discussed: the duration of the intervention (90 days), the long-term effects (> 6 months), the involvement of the ED staff.Trial registrationRegistered on clinicaltrials.gov as NCT03660215 on 4th September 2018.

The Tasmanian Emergency Care Outcomes Registry (TECOR) Protocol

Emergency Departments (ED) play a vital role within the health system, representing the ‘front door’ to hospitals, the first point of hospital contact for patients who are undifferentiated and may be critically ill. They also serve as a safety net for the healthcare system. Together with ED overcrowding, this patient care environment is highly vulnerable to the provision of suboptimal care and breaches in patient safety. Government agencies in Australia currently collect data that are broad and administratively focused and are limited in capacity to identifying clinical quality. Clinical quality registries (CQR) help fill this gap but are often funded by not-for-profit organisations or research grants. There is no emergency care CQR in Tasmania, Australia. We propose the establishment of the Tasmanian Emergency Care Outcomes Registry (TECOR) to monitor emergency care processes and outcomes. The primary objective of TECOR is to monitor the unexpected 30-day mortality of patients who are cared for in the ED as well as 30-day safety events where emergency care was the primary contributor. The TECOR is expected to provide ongoing data on other important processes of emergency care in Tasmania such as length of stay in EDs, 28-day representation to EDs and hospital length of stay. The registry was designed to national standards and will meet the needs of the clinical community and have a positive impact on the communities it serves.

Patient Flow Control in Emergency Departments Using Simulation Modeling and the Random Forest Algorithm

The proposed thesis aims to optimize patient flow and reduce waiting times in emergency departments using simulation modeling and the Random Forest algorithm. Emergency departments face significant challenges in managing patient flow and reducing waiting times, which can lead to increased patient dissatisfaction and decreased quality of care. The proposed solution uses simulation modeling to create a virtual model of the emergency department and simulate patient flow under different scenarios. The Random Forest algorithm is then used to analyze the simulation results and identify the factors impacting patient flow and waiting times. By optimizing these factors, the proposed solution aims to reduce waiting times and improve the overall patient experience. The research involves the development and validation of the simulation model and the implementation of the Random Forest algorithm using real-world emergency department data. The outcomes of the implemented Random Forest Model in Chapter Four showcase its efficacy with an accuracy rate of 0.85, sensitivity rate of 0.99, and other favorable metrics. The proposed solution has the potential to improve patient outcomes and reduce costs associated with emergency department overcrowding and delays.

Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits

The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to facilitate appropriate and timely care, which subsequently reduces patient revisits, optimizes resource allocation, and enhances patient outcomes. This study used ∼ 250,000 emergency department visit records from Taipei Medical University-Shuang Ho Hospital to develop a natural language processing model using BlueBERT, a biomedical domain-specific pre-trained language model, to predict patient disposition status and unplanned readmissions. Data preprocessing and the integration of both structured and unstructured data were central to our approach. Compared to other models, BlueBERT outperformed due to its pre-training on a diverse range of medical literature, enabling it to better comprehend the specialized terminology, relationships, and context present in ED data. We found that translating Chinese-English clinical narratives into English and textualizing numerical data into categorical representations significantly improved the prediction of patient disposition (AUROC = 0.9014) and 72-hour unscheduled return visits (AUROC = 0.6475). The study concludes that the BlueBERT-based model demonstrated superior prediction capabilities, surpassing the performance of prior patient disposition predictive models, thus offering promising applications in the realm of ED clinical practice.

Lactate Levels as a Predictor of Emergency Department Revisits in Infants With Acute Bronchiolitis.

This study aimed to identify predictive biomarkers for unscheduled emergency department (ED) revisits within 24 hours of discharge in infants diagnosed with acute bronchiolitis (AB). A retrospective observational study was conducted on infants diagnosed with AB who visited 3 emergency medical centers between January 2020 and December 2022. The study excluded infants with comorbidities, congenital diseases, and prematurity and infants who revisited the ED after 24 hours of discharge. Demographic data, vital signs, and laboratory results were collected from the medical records. Univariable and multivariable logistic regression analyses were performed on factors with P of less than 0.1 in univariable analysis. Receiver operator curve analysis was used to assess the accuracy of lactate measurements in predicting ED revisits within 24 hours of discharge. Out of 172 participants, 100 were in the revisit group and 72 in the discharge group. The revisit group was significantly younger and exhibited higher lactate levels, lower pH values, and higher pCO2 levels compared to the discharge group. Univariable logistic regression identified several factors associated with revisits. Multivariable analysis found that only lactate was a variable correlated with predicting ED revisits (odds ratio, 18.020; 95% confidence interval [CI], 5.764-56.334). The receiver operator curve analysis showed an area under the curve of 0.856, with an optimal lactate cutoff value of 2.15. Lactate value in infants diagnosed with AB were identified as a potential indicator of predicting unscheduled ED revisits within 24 hours of discharge. The predictive potential of lactate levels holds promise for enhancing prognosis prediction, reducing health care costs, and alleviating ED overcrowding. However, given the study's limitations, a more comprehensive prospective investigation is recommended to validate these findings.

Diagnosing an overcrowded emergency department from its Electronic Health Records

Emergency department overcrowding is a complex problem that persists globally. Data of visits constitute an opportunity to understand its dynamics. However, the gap between the collected information and the real-life clinical processes, and the lack of a whole-system perspective, still constitute a relevant limitation. An analytical pipeline was developed to analyse one-year of production data following the patients that came from the ED (n = 49,938) at Uppsala University Hospital (Uppsala, Sweden) by involving clinical experts in all the steps of the analysis. The key internal issues to the ED were the high volume of generic or non-specific diagnoses from non-urgent visits, and the delayed decision regarding hospital admission caused by several imaging assessments and lack of hospital beds. Furthermore, the external pressure of high frequent re-visits of geriatric, psychiatric, and patients with unspecified diagnoses dramatically contributed to the overcrowding. Our work demonstrates that through analysis of production data of the ED patient flow and participation of clinical experts in the pipeline, it was possible to identify systemic issues and directions for solutions. A critical factor was to take a whole systems perspective, as it opened the scope to the boundary effects of inflow and outflow in the whole healthcare system.

An ensemble model for predicting dispositions of emergency department patients

ObjectiveThe healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning’s potential to predict ED dispositions, thus leading to promising substantial benefits. This study’s objective is to create a predictive model for ED patient dispositions by employing ensemble learning. It harnesses diverse data types, including structured and unstructured information gathered during ED visits to address the evolving needs of localized healthcare systems.MethodsIn this cross-sectional study, 80,073 ED patient records were amassed from a major southern Taiwan hospital in 2018–2019. An ensemble model incorporated structured (demographics, vital signs) and pre-processed unstructured data (chief complaints, preliminary diagnoses) using bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF). Two random forest base-learners for structured and unstructured data were employed and then complemented by a multi-layer perceptron meta-learner.ResultsThe ensemble model demonstrates strong predictive performance for ED dispositions, achieving an area under the receiver operating characteristic curve of 0.94. The models based on unstructured data encoded with BOW and TF-IDF yield similar performance results. Among the structured features, the top five most crucial factors are age, pulse rate, systolic blood pressure, temperature, and acuity level. In contrast, the top five most important unstructured features are pneumonia, fracture, failure, suspect, and sepsis.ConclusionsFindings indicate that utilizing ensemble learning with a blend of structured and unstructured data proves to be a predictive method for determining ED dispositions.

The Impact of Involving a Senior Emergency Physician in the Triage Process

BACKGROUND: Emergency Department (ED) overcrowding has been demonstrated in several studies to be associated with undesirable effects such as longer waiting times, reduced patient satisfaction, and, most importantly, poor patient outcomes. Furthermore, long waiting times for walk-ins result in more complaints and patient dissatisfaction than illness management itself, with the majority of issues arising as a result of real and perceived waiting periods before being seen by the doctor. AIM: We set out to investigate whether introducing a senior emergency physician into the triage system would reduce waiting time, door-to-decision time, and door-to-doctor time, as well as increase patient satisfaction across the ED. METHOD: This was an interventional pre-post study that utilised retrospective data to evaluate the effect on ED throughput of triage by senior emergency physicians. We aimed to measure its impact on waiting time, door-to-decision time, and door-to-doctor time, along with ED patient satisfaction. RESULTS: Patient satisfaction, the overall assessment of treatment received during the visit, increased, from 74.975 to 77.425, and the likelihood of patients recommending the ED increased from 71.36 to 75.21. Operational metrics revealed a considerable drop in door-to-decision time (admit or discharge) of 46 minutes and 3 seconds, as well as a 1 minute and 21 second reduction in time from door to doctor (arrival to first provider). CONCLUSION: The mixed results hint at an effective but iterative process of enhancing patient flow and experience in the ED through senior physician triage.

An observational study on the impact of overcrowding towards door-to-antibiotic time among sepsis patients presented to emergency department of a tertiary academic hospital

BackgroundThe latest Surviving Sepsis Campaign 2021 recommends early antibiotics administration. However, Emergency Department (ED) overcrowding can delay sepsis management. This study aimed to determine the effect of ED overcrowding towards the management and outcome of sepsis patients presented to ED.MethodsThis was an observational study conducted among sepsis patients presented to ED of a tertiary university hospital from 18th January 2021 until 28th February 2021. ED overcrowding status was determined using the National Emergency Department Overcrowding Score (NEDOCS) scoring system. Sepsis patients were identified using Sequential Organ Failure Assessment (SOFA) scores and their door-to-antibiotic time (DTA) were recorded. Patient outcomes were hospital length of stay (LOS) and in-hospital mortality. Statistical analysis was done using Statistical Package for Social Sciences (SPSS) version 26. P-value of less than 0.05 for a two-sided test was considered statistically significant.ResultsTotal of 170 patients were recruited. Among them, 33 patients presented with septic shock and only 15% (n = 5) received antibiotics within one hour. Of 137 sepsis patients without shock, 58.4% (n = 80) received antibiotics within three hours. We found no significant association between ED overcrowding with DTA time (p = 0.989) and LOS (p = 0.403). However, in-hospital mortality increased two times during overcrowded ED (95% CI 1–4; p = 0.041).ConclusionED overcrowding has no significant impact on DTA and LOS which are crucial indicators of sepsis care quality but it increases overall mortality outcome. Further research is needed to explore other factors such as lack of resources, delay in initiating fluid resuscitation or vasopressor so as to improve sepsis patient care during ED overcrowding.

Changes in alcohol-related emergency department presentations—a comparison of three waves in 2013, 2017 and 2022

aims: Emergency departments (EDs) around the world are increasingly overcrowded, which is associated with significant patient harm. Alcohol use is a known contributor to ED overcrowding. This study aimed to assess trends in the characteristics of alcohol-related ED presentations over time. methods: A cross-sectional observational study of Christchurch ED attendances during 3-week waves of data collection in November–December 2013, 2017 and 2022 was conducted. Potential participants were those patients attending the Christchurch Hospital ED who had ingested alcohol in the 4 hours prior to arrival, and/or the presentation was thought to be related to alcohol. Those who consented to take part were interviewed to examine amount and source of alcohol. results: There has been a change in the age profile towards a greater proportion of older patients attending the ED with alcohol-related issues. In 2022, a greater proportion of alcohol was purchased from on-licence venues compared to previous years, although off-licence alcohol purchase and consumption in private locations remained the most common. conclusion: Alcohol use and harm places a significant, yet preventable, burden on EDs and the wider healthcare system. Implementation of evidence-based alcohol policies is urgently needed to reduce the impact of alcohol in the ED and improve the health of communities.

Effect of Paramedics in Emergency Department Triage on Ambulance Patient Offload Times

Background: Emergency Department (ED) overcrowding limits patient care in the prehospital and hospital system. A program was implemented to decrease the time to patient handoff from EMS arrival to ED staff, also known as the delivery interval and total turnaround interval. Paramedics were added to the ED ambulance triage staff to receive verbal reports and perform certain tasks done traditionally by nurses. We hypothesized adding paramedics to the ED triage process would reduce delivery interval times and total turnaround times. Methods: This was a retrospective observational study comparing delivery and turnaround intervals for patients brought to the ED by ambulance, before and after the addition of a paramedic in triage. The study period included all adult ED patients brought in by ambulance between 11 AM and 11 PM. Pediatric patients (<21 years old), direct-to-inpatient interfacility transfers, and critical patients requiring immediate care in the resuscitation area and thus bypassing normal triage processes were excluded. The data was analyzed with two-sample t-tests with a confidence interval of a = 0.05. Results: Delivery interval pre-implementation of the program was 15:48 minutes (95% CI [15:28, 16:09]) compared to 14:04 minutes (95% CI [13:44, 14:25]) post-implementation. The mean turnaround interval pre-implementation was 35:21 minutes (95% CI [35:01, 35:42]) and 36:04 minutes (95% CI [35:40, 36:29]) post-implementation. The mean difference for the delivery interval was shortened by 01:44 minutes (p<0.0001; 95% CI [01:15, 02:13]). The mean turnaround interval increased by 00:43 seconds (p<0.01; 95% CI [00:11, 01:16]). Conclusion: Staffing a paramedic in ED triage decreased delivery interval by 1:44 minutes but did not affect ambulance turnaround times. Further research is needed to determine if the decrease in delivery interval improved patient outcomes and ways to translate the time saved in the delivery interval to total turnaround times.

Health Status of Nonemergency Patients in the Emergency Department Using the EQ-5D.

Emergency department (ED) overcrowding is influenced by several factors including the hospital's capacity, staff, patient discharges, and community resources. The number of annual ED visits has increased, with patients' medical needs exceeding emergency capacity, resulting in a widespread concern about emergency room overcrowding. Nonemergency patients tend to use large amounts of emergency medical resources, which is one reason for ED overcrowding. Most patients consider their medical cases urgent, whereas medical professionals consider many cases to be nonemergency. Only a few studies have examined self-rated health among nonemergency patients. This cross-sectional study was conducted in the ED of a tertiary hospital in China using the European Quality of Life Five-Dimensional Questionnaire to investigate the health status of nonemergency patients. Among the 545 respondents, 246 (45.14%) self-assessed their health as excellent, 186 (34.13%) as very good, 70 (12.84%) as good, 32 (5.87%) as average, and 11 (2.02%) as poor. Problems related to pain/discomfort were reported by 317 (58.17%) participants, 214 (39.27%) responded that they had problems related to daily activities, 212 (38.90%) responded that they felt anxious or depressed, 211 (38.35%) responded that they had problems related to self-care, and some or extreme problems related to mobility were stated by 193 people (35.41%). Nonemergency patients generally reported good health. Pain/discomfort was the most significant factor affecting the health of nonemergency patients, followed by limitation of daily activities. The duration of illness onset and self-rated health status were common factors influencing the health status of nonemergency patients. This trial is registered with ChiCTR1900023578.

Low-Acuity Pediatric Emergency Department Utilization: Caregiver Motivations.

Proper emergency department (ED) utilization is a hallmark of population health. Emergency department overcrowding due to nonurgent visits causes increased stress to healthcare staff, higher costs, and longer wait times for more urgent cases. This study sought to better understand post pandemic reasons caregivers have when bringing in their children for nonurgent visits and devise effective interventions to improve caregiver choice for non-ED care for nonurgent conditions. Surveys were conducted at an urban pediatric hospital for Emergency Severity Index (ESI) level 3 to 5 visits. A total of 602 surveys were completed with 8 being excluded from analysis. Survey responses and anonymized demographic information were collected. Responses were compared between surveys grouped by respondent age category, relation to child, child's race, insurance type, and ESI levels. Primary reasons given for nonurgent ED visits were perceived urgency (74.2%, n = 441), ED superiority to other locations (23.9%, n = 142), and referral to the ED by a third party (17.7%, n = 105). Of those who cited perceived urgency as a reason, 80.5% (n = 355) wanted to lessen their child's pain/discomfort as soon as possible, but only 13.6% said that their child was too ill to be seen anywhere else (n = 60). Demographic differences occurred in the proportions of respondents citing some of the primary and secondary reasons for bringing their child to the ED. This study highlights 3 key findings. An immediate desire for care plays a key role in caregiver decision making for low-acuity visits. There is potential socioeconomic and racial bias in where care is recommended that needs to be further explored in this region. Cross community interventions that target key reasons for seeking low-acuity care have the highest likelihood of impacting the use of the ED for low-acuity conditions.

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

BackgroundEmergency 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.ObjectiveThis 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.MethodThe 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.ResultsThe 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).ConclusionEDOR 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.

Overcrowding in emergency departments: strategies and solutions for an effective reorganization

Overcrowding in emergency departments (EDs) is a common and worldwide phenomenon, widely reported even by the non-specialist press. It contributes to a number of consequences that can affect both the number of resources available and the quality of care. Strategies to address this incriminating situation for patients, nurses, doctors, and hospital administrators are urgently needed. For this reason, and based on the input from the Ministry of Health, a series of projects and procedures have been developed in various Italian regions, aimed at reducing the waiting times and the diagnostic-therapeutic process of patients arriving in the ED. In this article, we will examine the main critical issues within EDs and discuss the most impactful strategies and solutions to manage these difficulties.

One-year emergency department visits for children < 18 years of age, associated factors and frequency of primary general practitioner or pediatrician visits before: a French observational study (2018–19)

BackgroundThis study was designed to identify factors associated with at least one emergency department (ED) visit and those associated without consultation by a general practitioner or paediatrician (GPP) before ED visit. Levels of annual consumption of healthcare services as a function of the number of ED visit were reported.MethodsThis retrospective study focused on children < 18 years of age living in mainland France and followed for one-year after their birth or birthday in 2018. Children were selected from the national health data system, which includes data on healthcare reimbursements, long-term chronic diseases (LTD) eligible for 100% reimbursement, and individual complementary universal insurance (CMUc) status granted to households with a low annual income. Adjusted odds ratios (OR) were estimated using multivariate logistic regression.ResultsThere were 13.211 million children included (94.2% of children; girls 48.8%). At least one annual ED visit was found for 24% (1: 16%, 2: 5%, 3 or more: 3%) and 14% of visits led to hospitalization. Factors significantly associated with at least one ED visit were being a girl (47.1%; OR = 0.92), age < 1 year (9.1%; OR = 2.85), CMUc (22.7%, OR = 1.45), an ED in the commune of residence (33.3%, OR = 1.15), type 1 diabetes (0.25%; OR = 2.4), epilepsy (0.28%; OR = 2.1), and asthma (0.39%; OR = 2.0). At least one annual short stay hospitalisation (SSH) was found for 8.8% children of which 3.4% after an ED visit. A GPP visit the three days before or the day of the ED visit was found for 19% of children (< 1 year: 29%, 14–17 years: 13%). It was 30% when the ED was followed by SSH and 17% when not. Significant factors associated with the absence of a GPP visit were being a girl (OR = 0.9), age (1 year OR = 1.4, 14–17 years OR = 3.5), presence of an ED in the commune of residence (OR = 1.12), epilepsy LTD (OR = 1.1).ConclusionThe low level of visits to GPP prior to a visit to the ED and the associated factors are the elements to be taken into account for appropriate policies to limit ED overcrowding. The same applies to factors associated with a visit to the ED, in order to limit daily variations.

The Evaluation of In-Hospital Transportation of Emergency Room Critically Ill Patients

Backround/Aims:The overcrowding of emergency departments, insufficient bed capacity in these units, lack of integrated radiology units, and the distance of other departments and intensive care units from the emergency department make it inevitable to transport patients within the hospital for either short-term or long-term purposes. Patients can be transported at least once for diagnostic and treatment procedures to radiology units, operating rooms, or intensive care units for admission. However, even during short-term patient transport in critical situations, complications may arise. Methods:This study evaluates the data obtained prospectively by examining the transport information of 588 patients who met the study criteria in an eight-month period in the emergency department of a university hospital in 2020. The study is designed to assess survival, disability, and the safe transport process of critically ill patients transported from the emergency department to hospital imaging, interventional procedures, surgery, and admission units. For statistical analysis of the data, independent sample t-test was used for normally distributed variables, Mann-Whitney U test when the normality assumption was not met, chi-square, ANOVA tests for the comparison of categorical variables. The significance level for all hypothesis tests was set at 0.05. Results:Of the 588 patients included in the study, 36.9% were female and 63.1% were male, with an average age of 61.9 years. The average transport time for patients transferred for examination, admission, or interventional procedures was 18.5 minutes. 63.3% of the transferred patients sought medical attention during the night shift. During transport, 51.7% of patients experienced problems. Among the issues encountered during transport, 48.3% were related to the system, 27% were related to equipment, and 24.7% were related to human factors. The most common problem, accounting for 23.0%, was waiting in radiology units or corridors for radiology examinations and interventional procedures. Conclusion:In critically ill patients in the emergency department, the most common transport problems occur when planned examinations take place outside the emergency department. Therefore, the necessity of these requests should be carefully evaluated to reduce complications that may occur during transfer. The physical organization of emergency departments should be designed to facilitate the transfer of critical patients as quickly as possible to prevent problems that arise due to prolonged transfer times.

Pattern, Outcome and Associated Factors of Oncologic Emergencies Among Patients Visiting Saint Paul ‘s Hospital Millennium Medical College Adult Emergency Department: One Year Cross Sectional Study

Introduction: Cancer patients are at high risk of developing a wide range of medicalemergencies.Patients with cancer face unique disease and treatment-related complications that promptfrequent visits to the emergency department (ED), constituting a significant patient andhealth care burden, resulting in more utilization of resources and ED overcrowding, whichmay hamper the administration of quality and focused care.Objective: The study aimed to assess the patterns, outcomes, and associated factors ofoncologic emergencies among patients visiting Saint Paul's Hospital Millennium MedicalCollege adult emergency department from March 1/2021, to April 30/2022.Methods: A retrospective institutional-based cross-sectional study was used. Data wascollected using a standardized data extraction tool by trained data collectors from patientmedical records and health management information system registry books using asystematic sampling method. A total of 173 cancer patients were included. Data wasanalyzed using SPSS version 25.0.Results: A total of 173 cancer patients were included in the study. The mean age of thestudy participants was 53.05 ± 14.801 years. 56.6% were females, and 43.4% were males.The most prevalent primary tumors were those of the gastrointestinal tract (49.7%) andgenitourinary system (19.1%). About 39.9% of the cases had metastasis. Only 39.3% ofcases started cancer treatment. Oncologic emergencies account for 68.8% of the cases. Themost frequently observed oncologic emergencies were structural (Mass effect) in 64.7% ofcases and hematologic emergencies in 34.45%. About 19.3% of patients with oncologicemergencies have died. The commonest cause of death was due to Gastrointestinalmalignancies, seen in 34.6% of the cases. Those with Hematologic Emergencies had a 4.2times risk of death as compared to patients with local mass effects (P value &lt; 0.006).Conclusion: Oncologic emergencies comprised 68.8% of the cases, of which 19.3% resultedin mortality. There should be a well-organized system with chemotherapy, radiotherapy,and palliative care facility service for patients with oncologic emergencies to reduce patientmortality.

Profiles of Emergency Department Users with Psychiatric Disorders Related to Barriers to Outpatient Care.

Emergency department (ED) overcrowding is a growing problem worldwide. High ED users have been historically targeted to reduce ED overcrowding and associated high costs. Patients with psychiatric disorders, including substance-related disorders (SRDs), are among the largest contributors to high ED use. Since EDs are meant for urgent cases, they are not an appropriate setting for treating recurrent patients or replacing outpatient care. Identifying ED user profiles in terms of perceived barriers to care, service use, and sociodemographic and clinical characteristics is crucial to reduce ED use and unmet needs. Data were extracted from medical records and a survey was conducted among 299 ED patients from 2021 to 2022 in large Quebec networks. Cluster algorithms and comparison tests identified three profiles. Profile 1 had the most patients without barriers to care, with case managers, and received the best primary care. Profile 2 reported moderate barriers to care and low primary care use, best quality of life, and more serious psychiatric disorders. Profile 3 had the most barriers to care, high ED users, and lower service satisfaction and perceived mental/health conditions. Our findings and recommendations inform decision-makers on evidence-based strategies to address the unmet needs of these vulnerable populations.

A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department

This study addresses the challenges associated with emergency department (ED) overcrowding and emphasizes the need for efficient risk stratification tools to identify high-risk patients for early intervention. While several scoring systems, often based on logistic regression (LR) models, have been proposed to indicate patient illness severity, this study aims to compare the predictive performance of ensemble learning (EL) models with LR for in-hospital mortality in the ED. A cross-sectional single-center study was conducted at the ED of Imam Reza Hospital in northeast Iran from March 2016 to March 2017. The study included adult patients with one to three levels of emergency severity index. EL models using Bagging, AdaBoost, random forests (RF), Stacking and extreme gradient boosting (XGB) algorithms, along with an LR model, were constructed. The training and validation visits from the ED were randomly divided into 80% and 20%, respectively. After training the proposed models using tenfold cross-validation, their predictive performance was evaluated. Model performance was compared using the Brier score (BS), The area under the receiver operating characteristics curve (AUROC), The area and precision–recall curve (AUCPR), Hosmer–Lemeshow (H–L) goodness-of-fit test, precision, sensitivity, accuracy, F1-score, and Matthews correlation coefficient (MCC). The study included 2025 unique patients admitted to the hospital’s ED, with a total percentage of hospital deaths at approximately 19%. In the training group and the validation group, 274 of 1476 (18.6%) and 152 of 728 (20.8%) patients died during hospitalization, respectively. According to the evaluation of the presented framework, EL models, particularly Bagging, predicted in-hospital mortality with the highest AUROC (0.839, CI (0.802–0.875)) and AUCPR = 0.64 comparable in terms of discrimination power with LR (AUROC (0.826, CI (0.787–0.864)) and AUCPR = 0.61). XGB achieved the highest precision (0.83), sensitivity (0.831), accuracy (0.842), F1-score (0.833), and the highest MCC (0.48). Additionally, the most accurate models in the unbalanced dataset belonged to RF with the lowest BS (0.128). Although all studied models overestimate mortality risk and have insufficient calibration (P > 0.05), stacking demonstrated relatively good agreement between predicted and actual mortality. EL models are not superior to LR in predicting in-hospital mortality in the ED. Both EL and LR models can be considered as screening tools to identify patients at risk of mortality.