Clinical review: Emergency department overcrowding and the potential impact on the critically ill

Acceptance of electronic referrals across the Kingdom of Saudi Arabia: results from a national e-health database

Introduction

An effective referral system is necessary to ensure quality and an optimum continuum of care. In the Kingdom of Saudi Arabia, an e-referral system known as the Saudi Medical Appointments and Referrals Centre (SMARC), has been fully functioning since 2019. This study aims to explore the rate of medical e-referral request acceptance in the KSA, and to study the factors associated with acceptance.

Methods

This period cross-sectional study utilised secondary collected data from the SMARC e-referral system. The data spans both 2020 and 2021 and covers the entirety of the KSA. Bivariate analyses and binary logistic regression analyses were performed to compute adjusted Odds Ratios (aORs) and 95% confidence intervals.

Results

Of the total 632,763 referral requests across the 2 years, 469,073 requests (74.13%) were accepted. Absence of available machinery was a significant predictor for referral acceptance compared to other reasons. Acceptance was highest for children under 14 with 28,956 (75.48%) and 63,979 (75.48%) accepted referrals, respectively. Patients requiring critical care from all age groups also had the highest acceptance including 6,237 referrals for paediatric intensive care unit (83.54%) and 34,126 referrals for intensive care unit (79.65%). All lifesaving referrals, 42,087 referrals, were accepted (100.00%). Psychiatric patients were observed to have the highest proportion for accepted referrals with 8,170 requests (82.50%) followed by organ transplantations with 1,005 requests (80.92%). Sex was seen to be a significant predictor for referrals, where the odds of acceptances for females increased by 2% compared to their male counterparts (95% CI = 1.01-1.04). Also, proportion of acceptance was highest for the Eastern business unit compared to all other units. External referrals were 32% less likely to be accepted than internal referrals (95% CI = 0.67-0.69).

Conclusion

The current findings indicate that the e-referral system is mostly able to cater to the health services of the most vulnerable of patients. However, there remains areas for health policy improvement, especially in terms of resource allocation.

Cardiology department versus intensive care unit admission after successful uncomplicated transcatheter aortic valve replacement (TAVR)

BACKGROUND

Most patients after transcatheter aortic valve replacement (TAVR) are admitted directly to the cardiac intensive care unit (CICU) despite low complication rates. Reducing unnecessary CICU hospitalization reduces healthcare costs. This study aimed to compare the outcomes between patients admitted directly to the cardiology department (CD) and those admitted to CICU based on prespecified protocols.

METHODS

Historical cohort study of all patients who underwent TAVR and were admitted directly to the CD according to a prespecified protocol (uncomplicated procedure, hemodynamically stable, without new conduction abnormalities) in 2017-2018, and the same number of patients meeting the same criteria who were admitted to the CICU in 2015-2016 before direct CD admission was initiated. Pacemaker implantation during the procedure was not considered a new conduction abnormality. In-hospital outcomes and 30-day post-discharge outcomes were compared.

RESULTS

Overall, 260 patients (130 CICU + 130 CD) were included in the study. There was no in-hospital mortality in either group, and the post-procedure length of stay was shorter for patients admitted to CD (median and IQR: 2, 2-4 vs. 4, 3-5 days, p <0.001). There was no significant difference in 30-day emergency department visits between groups (CICU:13.9% vs. CD:16.2%, p = 0.602), rehospitalization rate (9.3%) was the same in both groups, and one patient from the CICU group died. Similar results were observed in multivariable analysis and after matching.

CONCLUSION

Direct admission to the CD after TAVR, according to the proposed criteria, may be considered as a safe and less expensive alternative for stable patients after an uncomplicated TAVR procedure.

Measuring Emergency Department Workload Perception Using Electronic Medical Record Measures of Patient Volume and Acuity

BACKGROUND

Workload in the emergency department (ED) fluctuates and there is no established model for measurement of clinician-level ED workload.

OBJECTIVE

The aim of this study was to measure perceived ED workload and assess the relationship between perceived workload and objective measures of workload from the electronic medical record (EMR).

METHODS

This study was conducted at a tertiary care, academic ED from July 1, 2020 through April 13, 2021. Attending workload perceptions were collected using a 5-point scale in three care areas with variable acuity. We collected eight EMR measures thought to correlate with perceived workload. EMR values were compared across areas of the department using ANOVA and correlated with attending workload ratings using linear regression.

RESULTS

We collected 315 unique workload ratings, which were normally distributed. For the entire department, there was a weak positive correlation between reported workload perception and mean percentage of inpatient admissions (r = 0.23; p < 0.001), intensive care unit admissions (r = 0.2; p < 0.001), patient arrivals per shift (r = 0.14; p = 0.017), critical care billed visits (r = 0.22; p < 0.001), cardiopulmonary resuscitation code activations (r = 0.2; p < 0.001), and level 5 visits (r = 0.13; p = 0.02). There was weak negative correlation for ED discharges (r = -0.23; p < 0.001). Several correlations were stronger in individual care areas, including percent admissions in the lowest-acuity area (r = 0.43; p = 0.033) and patient arrivals in the highest-acuity area (r = 0.44; p < .01). No significant correlation was found in any area for observation admissions or trauma activations.

CONCLUSIONS

In this study, EMR measures of workload were not closely correlated with ED attending physician workload perception. Future study should examine additional factors contributing to physician workload outside of the EMR.

Characteristics and patient impact of boarding in the pediatric emergency department, 2018-2022

OBJECTIVES

Boarding admitted patients in the emergency department is an important cause of throughput delays and safety risks in adults, though has been less studied in children. We assessed changes in boarding in a pediatric ED (PED) from 2018 to 2022 and modeled associations between boarding and select quality metrics.

METHODS

We performed a retrospective analysis of PED patients admitted to non-psychiatric services, broken into four periods: pre-COVID-19 (Period I, 01/2018-02/2020), early pandemic (II, 03/2020-06/2021), COVID-19 variants (III, 07/2021-06/2022), and non-COVID respiratory viruses (IV, 07/2022-12/2022). Patients were classified as critical (intensive care units (ICU)) or acute care (non-ICU inpatient services) based on their initial bed request. We compared median boarding times with Kruskal-Wallis tests. We assessed the relationship between boarding time and hospital length-of-stay (LOS) through hazard regression models, and the association between boarding time and PED return visit, readmission, and patient safety events through adjusted logistic regressions.

RESULTS

Median PED boarding time significantly increased from Period I (acute: 2.4 h; critical: 3.0 h) to Period II (acute: 3.0 h, critical: 4.0 h) to Period III (acute: 4.4 h, critical: 6.6 h) to Period IV (acute: 6.2 h; critical: 9.5 h). On survival analysis, as boarding time increased, hospital LOS increased for acute admissions and decreased for critical admissions. Increased acute care boarding time was associated with higher odds of a filed safety report.

CONCLUSIONS

Since July 2021, PED boarding time increased for admitted children across acute and critical admissions. The relationship between acute care boarding and longer hospital LOS suggests a resource-inefficient, self-perpetuating cycle that demands multi-disciplinary solutions.

The association between the workload of emergency physicians and the outcomes of acute myocardial infarction: a population-based study

Acute myocardial infarction (AMI) is the second leading cause of mortality in Taiwan. The correlation between the workload of emergency physicians and the outcome of AMI remains unknown. To determine the effects of the workload of emergency physicians on the outcomes of AMI. We included 17 661 patients (age > 18 years) with STEMI undergoing PCI, who visited the emergency department between 2012 and 2018. We used the logistic regression model with generalized estimating equations (GEEs) to analyze the risk of death within 30 days after emergency department visit, the risk of emergency department revisits within 3 days, and the risk of readmission within 14 days in all subgroups. After covariate adjustment, the risk of mortality within 30 days after visiting the emergency department was significantly higher in the subgroup whose visiting emergency physicians had the highest workload (odds ratio [OR]: 1.39; 95% confidence interval [CI]: 1.12 to 1.72). Furthermore, the risk of revisiting the emergency department within 3 days after discharge from the hospital was significantly higher in the subgroup whose visiting emergency physicians' workload was within the second and third quartiles (OR 1.85; 95% CI 1.18 to 2.89). The workload of emergency physicians appears to be positively correlated with the mortality risk of patients with STEMI undergoing PCI.

Decreased Utilization of Low Tidal Volume Ventilation Outside of the Intensive Care Unit as Compared to Inside

Background: Investigations into the use of low tidal volume ventilation (LTVV) have been performed for patients in emergency departments (EDs) or intensive care units (ICUs). Practice differences between the ICU and non-ICU care areas have not been described. We hypothesized that the initial implementation of LTVV would be better inside ICUs than outside. Methods: This is a retrospective observational study of patients initiated on invasive mechanical ventilation (IMV) between January 1, 2016, and July 17, 2019. Initial recorded tidal volumes after intubation were used to compare the use of LTVV between care areas. Low tidal volume was considered 6.5 cc/kg of ideal body weight (IBW) or less. The primary outcome was the initiation of low tidal volume. Sensitivity analyses used a tidal volume of 8 cc/kg of IBW or less, and direct comparisons were performed between the ICU, ED, and wards. Results: There were 6392 initiations of IMV: 2217 (34.7%) in the ICU and 4175 (65.3%) outside. LTVV was more likely to be initiated in the ICU than outside (46.5% vs 34.2%; adjusted odds ratio [aOR] 0.62, 95% confidence interval [CI] 0.56-0.71, P < .01). The ICU also had more implementation when PaO2/FiO2 ratio was less than 300, (48.0% vs 34.6%; aOR 0.59, 95% CI 0.48-0.71, P < .01). When comparing individual locations, wards had lower odds of LTVV than the ICU (aOR 0.82, 95% CI 0.70-0.96, P  =  .02), the ED had lower odds than the ICU (aOR 0.55, 95% CI 0.48-0.63, P < .01), and the ED had lower odds than the wards (aOR 0.66, 95% CI 0.56-0.77, P < .01). Interpretation: Initial low tidal volumes were more likely to be initiated in the ICU than outside. This finding remained when examining only patients with a PaO2/FiO2 ratio less than 300. Care areas outside of the ICU do not employ LTVV as often as ICUs and are, therefore, a possible target for process improvement.

Evaluation of the Emergency Severity Index in US Emergency Departments for the Rate of Mistriage

Importance

Accurate emergency department (ED) triage is essential to prioritize the most critically ill patients and distribute resources appropriately. The most used triage system in the US is the Emergency Severity Index (ESI).

Objectives

To derive and validate an algorithm to assess the rate of mistriage and to identify characteristics associated with mistriage.

Design, Setting, and Participants

This retrospective cohort study created operational definitions for each ESI level that use ED visit electronic health record data to classify encounters as undertriaged, overtriaged, or correctly triaged. These definitions were applied to a retrospective cohort to assess variation in triage accuracy by facility and patient characteristics in 21 EDs within the Kaiser Permanente Northern California (KPNC) health care system. All ED encounters by patients 18 years and older between January 1, 2016, and December 31, 2020, were assessed for eligibility. Encounters with missing ESI or incomplete ED time variables and patients who left against medical advice or without being seen were excluded. Data were analyzed between January 1, 2021, and November 30, 2022.

Exposures

Assigned ESI level.

Main Outcomes and Measures

Rate of undertriage and overtriage by assigned ESI level based on a mistriage algorithm and patient and visit characteristics associated with undertriage and overtriage.

Results

A total of 5 315 176 ED encounters were included. The mean (SD) patient age was 52 (21) years; 44.3% of patients were men and 55.7% were women. In terms of race and ethnicity, 11.1% of participants were Asian, 15.1% were Black, 21.4% were Hispanic, 44.0% were non-Hispanic White, and 8.5% were of other (includes American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multiple races or ethnicities), unknown, or missing race or ethnicity. Mistriage occurred in 1 713 260 encounters (32.2%), of which 176 131 (3.3%) were undertriaged and 1 537 129 (28.9%) were overtriaged. The sensitivity of ESI to identify a patient with high-acuity illness (correctly assigning ESI I or II among patients who had a life-stabilizing intervention) was 65.9%. In adjusted analyses, Black patients had a 4.6% (95% CI, 4.3%-4.9%) greater relative risk of overtriage and an 18.5% (95% CI, 16.9%-20.0%) greater relative risk of undertriage compared with White patients, while Black male patients had a 9.9% (95% CI, 9.8%-10.0%) greater relative risk of overtriage and a 41.0% (95% CI, 40.0%-41.9%) greater relative risk of undertriage compared with White female patients. High relative risk of undertriage was found among patients taking high-risk medications (30.3% [95% CI, 28.3%-32.4%]) and those with a greater comorbidity burden (22.4% [95% CI, 20.1%-24.4%]) and recent intensive care unit utilization (36.7% [95% CI, 30.5%-41.4%]).

Conclusions and Relevance

In this retrospective cohort study of over 5 million ED encounters, mistriage with ESI was common. Quality improvement should focus on limiting critical undertriage, optimizing resource allocation by patient need, and promoting equity.

Patient and hospital characteristics predict prolonged emergency department length of stay and in-hospital mortality: a nationwide analysis in Korea

BACKGROUND

Prolonged emergency department length of stay (EDLOS) in critically ill patients leads to increased mortality. This nationwide study investigated patient and hospital characteristics associated with prolonged EDLOS and in-hospital mortality in adult patients admitted from the emergency department (ED) to the intensive care unit (ICU).

METHODS

We conducted a retrospective cohort study using data from the National Emergency Department Information System. Prolonged EDLOS was defined as an EDLOS of ≥ 6 h. We constructed multivariate logistic regression models of patient and hospital variables as predictors of prolonged EDLOS and in-hospital mortality.

RESULTS

Between 2016 and 2019, 657,622 adult patients were admitted to the ICU from the ED, representing 2.4% of all ED presentations. The median EDLOS of the overall study population was 3.3 h (interquartile range, 1.9-6.1 h) and 25.3% of patients had a prolonged EDLOS. Patient characteristics associated with prolonged EDLOS included night-time ED presentation and Charlson comorbidity index (CCI) score of 1 or higher. Hospital characteristics associated with prolonged EDLOS included a greater number of staffed beds and a higher ED level. Prolonged EDLOS was associated with in-hospital mortality after adjustment for selected confounders (adjusted odds ratio: 1.18, 95% confidence interval: 1.16-1.20). Patient characteristics associated with in-hospital mortality included age ≥ 65 years, transferred-in, artificially ventilated in the ED, assignment of initial triage to more urgency, and CCI score of 1 or higher. Hospital characteristics associated with in-hospital mortality included a lesser number of staffed beds and a lower ED level.

CONCLUSIONS

In this nationwide study, 25.3% of adult patients admitted to the ICU from the ED had a prolonged EDLOS, which in turn was significantly associated with an increased in-hospital mortality risk. Hospital characteristics, including the number of staffed beds and the ED level, were associated with prolonged EDLOS and in-hospital mortality.

Safety and outcomes of short-term use of peripheral vasoactive infusions in critically ill paediatric population in the emergency department

Early restoration of oxygen delivery to end organs in paediatric patients experiencing shock states is critical to optimizing outcomes. However, obtaining central access in paediatric patients may be challenging in non-intensive care settings. There is limited literature on the use of peripheral vasoactive infusions in the initial resuscitation of paediatric patients in the emergency department. The aims of this study were to report the associated complications of peripheral vasoactive infusions and describe our local experience on its use. This was a single-centre, retrospective study on all paediatric patients who received peripheral vasoactive infusions at our paediatric emergency department from 2009 to 2016. 65 patients were included in this study. No patients had any local or regional complications. The mean patient age was 8.29 years old (± 5.99). The most frequent diagnosis was septic shock (45, 69.2%). Dopamine was the most used peripheral vasoactive agent (71.2%). The median time to central agents was 2 h (IQR 1–4). 16(24.2%) received multiple peripheral infusions. We reported no complications of peripheral vasoactive infusions. Its use could serve as a bridge till central access is obtained. Considerations on the use of multiple peripheral vasoactive infusions in the emergency department setting needs further research.

Association between prehospital recognition of acute myocardial infarction and length of stay in the emergency department

OBJECTIVE

This study aimed to evaluate the association between prehospital recognition of acute myocardial infarction (AMI) and length of stay (LOS) in the emergency department (ED) of emergency medical service (EMS)-transported AMI patients.

METHODS

A multicenter retrospective observational study was conducted using prehospital and hospital data from three tertiary emergency departments. Patients diagnosed with AMI between January 2015 and December 2018 were enrolled. Study groups were categorized according to prehospital recognition and prehospital 12-lead electrocardiography (ECG) into three groups based on an EMS cardiovascular registry: group A, no prehospital recognition (reference group); group B, prehospital recognition without 12-lead ECG; and group C, prehospital recognition with 12-lead ECG. The primary outcome was an ED LOS of less than 4 hours.

RESULTS

Among 1,237 study participants, 722 (58.4%) were in group A, 325 (26.3%) were in group B, and 190 (15.4%) were in group C. Multivariable logistic regression showed that groups B and C had a higher likelihood of a short ED LOS (adjusted odds ratio [95% confidence interval]: group B, 1.64 [1.21-2.22] and group C, 1.88 [1.30-2.71]) than group A. There was no significant difference in ED LOS according to whether prehospital 12-lead ECG was conducted.

CONCLUSION

Prehospital recognition of AMI by EMS personnel, with or without 12-lead ECG, was associated with a short ED LOS.

Reducing Crowding in Emergency Departments With Early Prediction of Hospital Admission of Adult Patients Using Biomarkers Collected at Triage: Retrospective Cohort Study

BACKGROUND

Emergency department crowding continues to threaten patient safety and cause poor patient outcomes. Prior models designed to predict hospital admission have had biases. Predictive models that successfully estimate the probability of patient hospital admission would be useful in reducing or preventing emergency department "boarding" and hospital "exit block" and would reduce emergency department crowding by initiating earlier hospital admission and avoiding protracted bed procurement processes.

OBJECTIVE

To develop a model to predict imminent adult patient hospital admission from the emergency department early in the patient visit by utilizing existing clinical descriptors (ie, patient biomarkers) that are routinely collected at triage and captured in the hospital's electronic medical records. Biomarkers are advantageous for modeling due to their early and routine collection at triage; instantaneous availability; standardized definition, measurement, and interpretation; and their freedom from the confines of patient histories (ie, they are not affected by inaccurate patient reports on medical history, unavailable reports, or delayed report retrieval).

METHODS

This retrospective cohort study evaluated 1 year of consecutive data events among adult patients admitted to the emergency department and developed an algorithm that predicted which patients would require imminent hospital admission. Eight predictor variables were evaluated for their roles in the outcome of the patient emergency department visit. Logistic regression was used to model the study data.

RESULTS

The 8-predictor model included the following biomarkers: age, systolic blood pressure, diastolic blood pressure, heart rate, respiration rate, temperature, gender, and acuity level. The model used these biomarkers to identify emergency department patients who required hospital admission. Our model performed well, with good agreement between observed and predicted admissions, indicating a well-fitting and well-calibrated model that showed good ability to discriminate between patients who would and would not be admitted.

CONCLUSIONS

This prediction model based on primary data identified emergency department patients with an increased risk of hospital admission. This actionable information can be used to improve patient care and hospital operations, especially by reducing emergency department crowding by looking ahead to predict which patients are likely to be admitted following triage, thereby providing needed information to initiate the complex admission and bed assignment processes much earlier in the care continuum.

ES-RED (Early Seizure Recurrence in the Emergency Department) Calculator: A Triage Tool for Seizure Patients

Seizure is a common neurological presentation in patients visiting the emergency department (ED) that requires time for evaluation and observation. Timely decision and disposition standards for seizure patients need to be established to prevent overcrowding in the ED and achieve patients’ safety. Here, we conducted a retrospective cohort study to predict early seizure recurrence in the ED (ES-RED). We randomly assigned 688 patients to the derivation and validation cohorts (2:1 ratio). Prediction equations extracted routine clinical and laboratory information from EDs using logistic regression (Model 1) and machine learning (Model 2) methods. The prediction equations showed good predictive performance, the area under the receiver operating characteristics curve showing 0.808 in Model 1 [95% confidential interval (CI): 0.761–0.853] and 0.805 in Model 2 [95% CI: 0.747–0.857] in the derivation cohort. In the external validation, the models showed strong prediction performance of 0.739 [95% CI: 0.640–0.824] in Model 1 and 0.738 [95% CI: 0.645–0.819] in Model 2. Intriguingly, the lowest quartile group showed no ES-RED after 6 h. The ES-RED calculator, our proposed prediction equation, would provide strong evidence for safe and appropriate disposition of adult resolved seizure patients from EDs, reducing overcrowding and delays and improving patient safety.

Comparative analysis of machine learning approaches for predicting frequent emergency department visits

BACKGROUND

Emergency Department (ED) overcrowding is an emerging risk to patient safety. This study aims to assess and compare the predictive ability of machine learning (ML) models for predicting frequent ED users.

METHOD

Korean Health Panel data from 2008 to 2015 were used for this study. Individuals with four or more visits per year were considered frequent ED users. Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM) as well as two ensemble models, namely Bagging and Voting, were trained and tested to examine their predictive performance.

RESULTS

The ML classification algorithms identified frequent ED users with high precision (90%-98%) and sensitivity (87%-91%), whereas LR showed fair precision (65%) and sensitivity (67%). The ML algorithms showed a high area under the curve (AUC) values from 89% for SVM to 96% for Random Forest, while LR showed the lowest AUC (65%). The classification error varied among algorithms; LR had the highest classification error (24.07%) while RF had the least (3.8%).

CONCLUSIONS

Results show that ML classification algorithms are robust techniques to predict frequent ED users, and the variables in administrative health panels are reliable indicators for this purpose.

The Use of a Fixed 50:50 Mixture of Nitrous Oxide and Oxygen to Reduce Lumbar Puncture-Induced Pain in the Emergency Department: A Randomized Controlled Trial

Lumbar puncture (LP) is stressful and often painful. We evaluated the efficacy of a fixed 50% nitrous oxide−oxygen mixture (50%N2O-O2) versus placebo to reduce immediate procedural pain and anxiety during LP performed in an emergency setting. We conducted a randomized controlled trial involving adults who needed a cerebrospinal fluid analysis in an emergency department. Patients were randomly assigned to inhale either 50%N2O-O2 or medical air. The primary endpoint, assessed using a numerical scale, was the maximum pain felt by the patient during the procedure and the maximum anxiety and satisfaction as secondary outcomes. Eighty-eight patients were randomized and analyzed (ITT). The maximal pain was 5.0 ± 2.9 for patients receiving air and 4.2 ± 3.0 for patients receiving 50%N2O-O2 (effect-size = −0.27 [−0.69; 0.14], p = 0.20). LP-induced anxiety was 4.7 ± 2.8 vs. 3.7 ± 3.7 (p = 0.13), and the proportion of patients with significant anxiety (score ≥ 4/10) was 72.7% vs. 50.0% (p = 0.03). Overall satisfaction was higher among patients receiving 50%N2O-O2 (7.4 ± 2.4 vs. 8.9 ± 1.6, p < 0.001). No serious adverse events were attributable to 50%N2O-O2 inhalation. Although inhalation of 50%N2O-O2 failed to reduce LP-induced pain in an emergency setting, it tended to reduce anxiety and significantly increased patient satisfaction.

Delayed Admission to the Intensive Care Unit and Mortality of Critically Ill Adults: Systematic Review and Meta-analysis

Delayed admission of patients to the intensive care unit (ICU) is increasing worldwide and can be followed by adverse outcomes when critical care treatment is not provided timely. This systematic review and meta-analysis appraised and synthesized the published literature about the association between delayed ICU admission and mortality of adult patients. Articles published from inception up to August 2021 in English-language, peer-reviewed journals indexed in CINAHL, PubMed, Scopus, Cochrane Library, and Web of Science were searched by using key terms. Delayed ICU admission constituted the intervention, while mortality for any predefined time period was the outcome. Risk for bias was evaluated with the Newcastle-Ottawa Scale and additional criteria. Study findings were synthesized qualitatively, while the odds ratios (ORs) for mortality with 95% confidence intervals (CIs) were combined quantitatively. Thirty-four observational studies met inclusion criteria. Risk for bias was low in most studies. Unadjusted mortality was reported in 33 studies and was significantly higher in the delayed ICU admission group in 23 studies. Adjusted mortality was reported in 18 studies, and delayed ICU admission was independently associated with significantly higher mortality in 13 studies. Overall, pooled OR for mortality in case of delayed ICU admission was 1.61 (95% CI 1.44-1.81). Interstudy heterogeneity was high (I² = 66.96%). According to subgroup analysis, OR for mortality was remarkably higher in postoperative patients (OR, 2.44, 95% CI 1.49-4.01). These findings indicate that delayed ICU admission is significantly associated with mortality of critically ill adults and highlight the importance of providing timely critical care in non-ICU settings.

Capacity and Organisation of Madrid’s Community Hospitals During First Wave of COVID-19 Pandemic

Introduction and objectives

The first wave of the SARS-CoV-2 pandemic exerted enormous stress on the healthcare system. Community of Madrid hospitals responded by restructuring and scaling their capacity to adapt to the high demand for care.

Methods

This was a retrospective observational study conducted between 18 March and 21 June 2020 with data from public and private hospitals in CoM, Spain. Absolute and relative frequencies were calculated for inpatients with and without COVID-19, available and occupied beds in intensive care unit (ICU) and non-ICU wards, daily new admissions (NA), individuals awaiting hospitalisation in the emergency department (ED), and discharges.

Results

Compared to pre-pandemic years, during the maximum care pressure period (18 March–17 April 2020), the average number of total available and occupied beds increased by 27% and 36%, respectively. Also, the average number of available and occupied ICU beds increased by 174% and 257% respectively, and average occupancy was 81%. The average daily NAs were 1,503 (90% from the ED) and 949 (63% due to COVID-19), and of these, 61 (6.4%) were admitted to the ICU. On average, at 6:00 p.m., 1112 patients were waiting in the ED to be admitted and 299 (26.8%) patients waited for more than 24 h. Discharges due to death for COVID-19 inpatients in the non-ICU and ICU wards were 16% and 36%, respectively.

Conclusions

This study confirmed the critical role of the ICU and ED, especially in the care of patients before being hospitalizated, in pandemic or health crisis scenarios.

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units

STUDY OBJECTIVE

This study aimed to develop and validate 2 machine learning models that use historical and current-visit patient data from electronic health records to predict the probability of patient admission to either an inpatient unit or ICU at each hour (up to 24 hours) of an emergency department (ED) encounter. The secondary goal was to provide a framework for the operational implementation of these machine learning models.

METHODS

Data were curated from 468,167 adult patient encounters in 3 EDs (1 academic and 2 community-based EDs) of a large academic health system from August 1, 2015, to October 31, 2018. The models were validated using encounter data from January 1, 2019, to December 31, 2019. An operational user dashboard was developed, and the models were run on real-time encounter data.

RESULTS

For the intermediate admission model, the area under the receiver operating characteristic curve was 0.873 and the area under the precision-recall curve was 0.636. For the ICU admission model, the area under the receiver operating characteristic curve was 0.951 and the area under the precision-recall curve was 0.461. The models had similar performance in both the academic- and community-based settings as well as across the 2019 and real-time encounter data.

CONCLUSION

Machine learning models were developed to accurately make predictions regarding the probability of inpatient or ICU admission throughout the entire duration of a patient's encounter in ED and not just at the time of triage. These models remained accurate for a patient cohort beyond the time period of the initial training data and were integrated to run on live electronic health record data, with similar performance.

LBA: Online Learning-Based Assignment of Patients to Medical Professionals

Central to any medical domain is the challenging patient to medical professional assignment task, aimed at getting the right patient to the right medical professional at the right time. This task is highly complex and involves partially conflicting objectives such as minimizing patient wait-time while providing maximal level of care. To tackle this challenge, medical institutions apply common scheduling heuristics to guide their decisions. These generic heuristics often do not align with the expectations of each specific medical institution. In this article, we propose a novel learning-based online optimization approach we term Learning-Based Assignment (LBA), which provides decision makers with a tailored, data-centered decision support algorithm that facilitates dynamic, institution-specific multi-variate decisions, without altering existing medical workflows. We adapt our generic approach to two medical settings: (1) the assignment of patients to caregivers in an emergency department; and (2) the assignment of medical scans to radiologists. In an extensive empirical evaluation, using real-world data and medical experts' input from two distinctive medical domains, we show that our proposed approach provides a dynamic, robust and configurable data-driven solution which can significantly improve upon existing medical practices.

Perception of safety climate among Indonesian nurses: A cross-sectional survey

Background: The measurement of nurse perception on safety, and the factors associated to safety climate, direct the development of effective strategies in reducing adverse events, and patient safety improvement.

Design and Method: This research was quantified, using the teamwork and safety climate domains of an Indonesian translated version of the Safety Attitudes Questionnaire (SAQ-INA). The teamwork and safety climate domain scores were calculated, using the published SAQ-INA scoring algorithm. The univariate and multivariate median regression models were performed to examine the association between potential predictors and safety climate.

Result: The results showed that 279 nurses responded to the survey (82% response rate). While most of them had a positive attitude towards teamwork (n=170, 61%), fewer possessed the same mentality towards safety climate (n=109, 39%). The lowest level of teamwork was perceived by nurses working in the emergency department (median 71, interquartile range 12.5), and safety climate (median 64, interquartile range 14.2). Furthermore, those that worked in the private hospitals, also reported lower levels of safety climate, compared to nurses in the public health centres (median difference=-3.571, p=0.009).

Conclusion: Ward and hospital type were associated with the level of safety climate, perceived by nurses. Understanding the key areas, the intervention is best directed to target hospital wards with poor safety climate, in a bid to reduce adverse events, and improve patient safety.

Causes of death among dengue patients causes of death among hospitalized adults with dengue fever in Tainan, 2015: Emphasis on cardiac events and bacterial infections

INTRODUCTION

The 2015 dengue outbreak in southern Taiwan caused substantial mortality. We analyzed the causes of death among these patients.

MATERIALS AND METHODS

This retrospective study was conducted at a medical center in Tainan from August 2015 to December 2015. Dengue was diagnosed based on the detection of serum dengue NS1 antigen, IgM, or viral RNA in the blood. Causes of death were retrieved from chart reviews by three clinicians.

RESULTS

There were 4488 cases of dengue in the study hospital, with an in-hospital fatality rate of 1.3% (60 cases). The mean age of the 60 fatal cases was 73 years, among whom 90% were aged ≥65 years. Twenty-eight (46.7%) patients died of severe dengue, and 29 (48.3%) deaths were possibly related to dengue. Of the latter, 24 (40%) died of secondary infections. Thirteen cardiac arrest events, including out-of-hospital (5 events) and in-hospital (8) cardiac arrests in the emergency department, occurred during the dengue epidemic. Seven (53.8%) patients did not receive medical aid before the event. Of the 40 deaths that occurred within one week after hospitalization, 60% died of severe dengue. In contrast, 50% of 20 deaths that occurred one week after hospitalization were related to hospital-acquired infections, mainly pneumonia.

CONCLUSION

Of 60 fatal cases, with a predominance of elderly patients, deaths were related to severe dengue within the first week after admission and secondary infections thereafter. The absence of medical care before cardiac arrest events highlights the importance of health education for warning signs of dengue.

Quantifying the impact of patient boarding on emergency department length of stay: All admitted patients are negatively affected by boarding

BACKGROUND

Patients boarding in the emergency department (ED) as a result of delays in bed placement are associated with increased morbidity and mortality. Prior literature on ED boarding does not explore the impact of boarding on patients admitted to the hospital from the ED. The objective of this study was to evaluate the impact of patient boarding on ED length of stay for all patients admitted to the hospital.

METHODS

This was an institutional review board-approved, retrospective review of all patients from January 1, 2015, through June 30, 2019, presenting to 2 large EDs in a single health system in Pennsylvania. Quantile regression models were created to estimate the impact of patients boarding in the ED on length of stay for all ED patients admitted to the hospital.

RESULTS

A total number of 466,449 ED encounters were analyzed across two EDs. At one ED, for every patient boarded, the median ED length of stay for all admitted patients increased by 14.0 minutes (P < 0.001). At the second ED, for every patient boarded in the ED, the median ED length of stay increased by 12.4 minutes (P < 0.001).

CONCLUSION

ED boarding impacts length of stay for all patients admitted through the ED and not just those admitted patients who are boarded. This study provides an estimate for the increased ED length of stay experienced by all patients admitted to the hospital as a function of patient boarding.

In-hospital mortality from severe COVID-19 in a tertiary care center in Mexico City; causes of death, risk factors and the impact of hospital saturation

BACKGROUND

As the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has remained in Latin America, Mexico has become the third country with the highest death rate worldwide. Data regarding in-hospital mortality and its risk factors, as well as the impact of hospital overcrowding in Latin America has not been thoroughly explored.

METHODS AND FINDINGS

In this prospective cohort study, we enrolled consecutive adult patients hospitalized with severe confirmed COVID-19 pneumonia at a SARS-CoV-2 referral center in Mexico City from February 26th, 2020, to June 5th, 2020. A total of 800 patients were admitted with confirmed diagnosis, mean age was 51.9 ± 13.9 years, 61% were males, 85% were either obese or overweight, 30% had hypertension and 26% type 2 diabetes. From those 800, 559 recovered (69.9%) and 241 died (30.1%). Among survivors, 101 (18%) received invasive mechanical ventilation (IMV) and 458 (82%) were managed outside the intensive care unit (ICU); mortality in the ICU was 49%. From the non-survivors, 45.6% (n = 110) did not receive full support due to lack of ICU bed availability. Within this subgroup the main cause of death was acute respiratory distress syndrome (ARDS) in 95% of the cases, whereas among the non-survivors who received full (n = 105) support the main cause of death was septic shock (45%) followed by ARDS (29%). The main risk factors associated with in-hospital death were male sex (RR 2.05, 95% CI 1.34-3.12), obesity (RR 1.62, 95% CI 1.14-2.32)-in particular morbid obesity (RR 3.38, 95%CI 1.63-7.00)-and oxygen saturation < 80% on admission (RR 4.8, 95%CI 3.26-7.31).

CONCLUSIONS

In this study we found similar in-hospital and ICU mortality, as well as risk factors for mortality, compared to previous reports. However, 45% of the patients who did not survive justified admission to ICU but did not receive IMV / ICU care due to the unavailability of ICU beds. Furthermore, mortality rate over time was mainly due to the availability of ICU beds, indirectly suggesting that overcrowding was one of the main factors that contributed to hospital mortality.

Hospital bed capacity and usage across secondary healthcare providers in England during the first wave of the COVID-19 pandemic: a descriptive analysis

OBJECTIVE

In this study, we describe the pattern of bed occupancy across England during the peak of the first wave of the COVID-19 pandemic.

DESIGN

Descriptive survey.

SETTING

All non-specialist secondary care providers in England from 27 March27to 5 June 2020.

PARTICIPANTS

Acute (non-specialist) trusts with a type 1 (ie, 24 hours/day, consultant-led) accident and emergency department (n=125), Nightingale (field) hospitals (n=7) and independent sector secondary care providers (n=195).

MAIN OUTCOME MEASURES

Two thresholds for 'safe occupancy' were used: 85% as per the Royal College of Emergency Medicine and 92% as per NHS Improvement.

RESULTS

At peak availability, there were 2711 additional beds compatible with mechanical ventilation across England, reflecting a 53% increase in capacity, and occupancy never exceeded 62%. A consequence of the repurposing of beds meant that at the trough there were 8.7% (8508) fewer general and acute beds across England, but occupancy never exceeded 72%. The closest to full occupancy of general and acute bed (surge) capacity that any trust in England reached was 99.8% . For beds compatible with mechanical ventilation there were 326 trust-days (3.7%) spent above 85% of surge capacity and 154 trust-days (1.8%) spent above 92%. 23 trusts spent a cumulative 81 days at 100% saturation of their surge ventilator bed capacity (median number of days per trust=1, range: 1-17). However, only three sustainability and transformation partnerships (aggregates of geographically co-located trusts) reached 100% saturation of their mechanical ventilation beds.

CONCLUSIONS

Throughout the first wave of the pandemic, an adequate supply of all bed types existed at a national level. However, due to an unequal distribution of bed utilisation, many trusts spent a significant period operating above 'safe-occupancy' thresholds despite substantial capacity in geographically co-located trusts, a key operational issue to address in preparing for future waves.

Limiting ICU admission from emergency services and wards

INTRODUCTION

Decisions not to admit a patient to intensive care units (ICU) as a way of limiting life support treatment (LLST) is a practice that can affect the operation of the emergency services and the way in which patients die.

METHODS

Post hoc analysis of the ADENI-UCI study. The main variable analysed was the reason for refusal of admission to the ICU as a measure of LLST. For the present post hoc analysis, the registered patients were divided into 2 groups: the patients assessed in the intensive medicine services from the emergency department and the patients assessed from the conventional hospitalization areas. Student t was used in the comparative statistics when the mean values of the patient sub-cohorts were compared. Categorical variables were compared with the χ² tests.

RESULTS

The ADENI-ICU study included 2,284 decisions not to admit to the ICU as a measure of LLST. Estimated poor quality of life (p=.0158), the presence of severe chronic disease (P=.0169) and futility of treatment (P=.0006) were percentage decisions with greater weight within the population of hospitalized patients. The percentage of disagreement between the consulting physician and the intensivist was significantly lower in patients assessed from the emergency services (P=.0021).

CONCLUSIONS

There are appreciable differences in the reasons for consultation, as well as in those for refusal of admission to an ICU between the consultations made from an emergency department and a conventional hospitalization facility.

Effectiveness of hospital emergency department regionalization and categorization policy on appropriate patient emergency care use: a nationwide observational study in Taiwan

BACKGROUND

Emergency department (ED) overcrowding is a health services issue worldwide. Modern health policy emphasizes appropriate health services utilization. However, the relationship between accessibility, capability, and appropriateness of ED use is unknown. Thus, this study aimed to examine the effect of hospital ED regionalization policy and categorization of hospital emergency capability policy (categorization policy) on patient-appropriate ED use.

METHODS

Taiwan implemented a nationwide three-tiered hospital ED regionalization and categorization of hospital emergency capability policies in 2007 and 2009, respectively. We conducted a retrospective observational study on the effect of emergency care policy intervention on patient visit. Between 2005 and 2011, the Taiwan National Health Insurance Research Database recorded 1,835,860 ED visits from 1 million random samples. ED visits were categorized using the Yang-Ming modified New York University-ED algorithm. A time series analysis was performed to examine the change in appropriate ED use rate after policy implementation.

RESULTS

From 2005 to 2011, total ED visits increased by 10.7%. After policy implementation, the average appropriate ED visit rate was 66.9%. The intervention had no significant effect on the trend of appropriate ED visit rate.

CONCLUSIONS

Although regionalization and categorization policies did increase emergency care accessibility, it had no significant effect on patient-appropriate ED use. Further research is required to improve data-driven policymaking.

Effect of emergency critical care nurses and emergency department boarding time on in-hospital mortality in critically ill patients

STUDY HYPOTHESIS

We hypothesized that establishing a program of specialized emergency critical care (ECC) nurses in the ED would improve mortality of ICU patients boarding in the ED.

METHODS

This was a retrospective before-after cohort study using electronic health record data at an academic medical center. We compared in-hospital mortality between the pre- and post-intervention periods and between non-prolonged (≤6 h) boarding time and prolonged (>6 h) boarding time. In-hospital mortality was stratified by illness severity (eccSOFA category) and adjusted using logistic regression.

RESULTS

Severity-adjusted in-hospital mortality decreased from 12.8% pre-intervention to 12.3% post-intervention (-0.5% (95% CI, -3.1% to 2.1%), which was not statistically significant. This was despite a concurrent increase in ED and hospital crowding. The proportion of ECC patients downgraded to a lower level of care while still in the ED increased from 6.4% in the pre-intervention period to 17.0% in the post-intervention period. (+10.6%, 8.2% to 13.0%, p < 0.001). Severity-adjusted mortality was 12.8% in the non-prolonged group vs. 11.3% in the prolonged group (p = 0.331).

CONCLUSIONS

During the post-intervention period, there was a significant increase in illness severity, hospital congestion, ED boarding time, and downgrades in the ED, but no significant change in mortality. These findings suggest that ECC nurses may improve the safety of boarding ICU patients in the ED. Longer ED boarding times were not associated with higher mortality in either the pre- or post-intervention periods.

Changing the Care Paradigm for Patients: Advanced Illness Beds Care Model

BACKGROUND

Over 90 million Americans suffer from advanced illness (AI) and spend their last days of life in critical care units receiving costly, unwanted, aggressive medical care.

OBJECTIVE

Evaluate the impact of a specialized care model in medical/surgical units for hospitalized geriatric patients and patients with complex care requirements where designated AI beds align care with patient's wishes/goals, minimize aggressive interventions, and influence efficient resource utilization.

DESIGN

US based multi-facility retrospective, longitudinal descriptive study of screened positive AI patients in AI Beds (N = 1,237) from 3 facilities from 2015 to 2017.

RESULTS

Patient outcomes included 60% referrals to AI beds from ICU, a decrease of 39-49% in average ICU LOS, a 23% reduction of AI bed patient expirations, 9.0% referrals to hospice, and projected cost savings of $4,361.66/patient, US dollars.

CONCLUSION

Allocating AI beds to deliver care to AI patients resulted in a decreased cost of care by reducing overall hospital LOS, mortality, and efficient use of both critical care and hospital resources.

Frequency, Causes, and Outcomes of Return Visits to the Emergency Department Within 72 Hours: A Retrospective Observational Study

Background

Emergency departments (EDs) serve as an accessible gateway to healthcare system wherein numerous patients consider it a prime choice for medical complaints. Frequency of ED revisits, causes, and its burden are necessary to assess quality of care provided to patients and identify factors that leads to revisit.

Patients and Methods

Electronic and printed medical records of all patients who revisited ED from January to May 2016 within 72 hours of initial visit were reviewed. Patients’ cause of revisit were classified to three categories: patient-, physician- and system-related factors. Common complaints that require revisits were also collected. Descriptive analysis was performed and categorical variables were represented by the frequency; percentages and continuous variables were presented as median, and range if data did not follow normal distribution.

Results

Of the 79,279 patients who visited ED during the study period, 1.3% (1000) patients revisited within 72 hours; 51.3% (n=513) were males, with a mean age of 31.5 years (SD=17.7 years) where majority (57.1%) had no comorbidity recorded. The most attributed factors for revisit were as follows: patient-related causes 635 patients (63.5%), physician-related factors 167 patients (16.7%), and system-related factors 42 patients (4.2%); 15.6% were found not related to the initial visit. Recurrence of the same complaint was the highest among patient-related factors (80.5%), inadequate management and no improvement of symptoms in 71.3% among the physician-related factors. The most common ED revisit complaint was fever 29.1% (n=291). Outcomes of the revisit were mainly patient discharge 96.7% (n=967), admission 1.2% (n=12) and death in 0.2% (n=2).

Conclusion

Recurrence of the same complaint with no symptoms improvement and suboptimal management of physicians contributed to most of the ED revisits within 72 hours. Encouraging physicians to provide clear instructions in educating patients on discharge regarding disease progression and its red flags as to when a return to ED, might help in reducing revisit rate.

Is Early Oral Antimicrobial Switch Useful for Less Critically Ill Adults with Community-Onset Bacteraemia in Emergency Departments?

To compare prognoses and adverse events between bacteraemic patients in the emergency department (ED) who received an early antimicrobial IV-to-PO switch and those treated with late or no IV-to-PO switch, an 8-year multicentre cohort consisting of adults with community-onset bacteraemia was conducted. The clinical characteristics and outcomes were compared in matched cohorts by the closest propensity score calculated based on the independent determinants of 30-day mortality identified by the multivariate regression model. Of the 6664 hospitalised patients who received no or late IV-to-PO switch, 2410 were appropriately matched with 482 patients treated with early IV-to-PO switch and discharged from the ED. There were no significant differences between the two matched groups in their baseline characteristics, including the patient demographics, severity and types of comorbidities, severity and sources of bacteraemia, and the 15- and 30-day mortality rates. Notably, in addition to the shorter lengths of intravenous antimicrobial administration and hospital stay, less phlebitis and lower antimicrobial costs were observed in patients who received an early IV-to-PO switch. Similarity was observed in the clinical failure rates between the two groups. Furthermore, the inappropriate administration of empirical antibiotics and inadequate source control were identified as the only independent determinants of the post-switch 30-day crude mortality in patients who received an early IV-to-PO switch. In conclusion, for less critically ill adults with community-onset bacteraemia who received appropriate empirical antimicrobial therapy and adequate source control, an early IV-to-PO switch might be safe and cost-effective after a short course of intravenous antimicrobial therapy.

Emergency Department Boarding of Non-Trauma Patients Adversely Affects Trauma Patient Length of Stay

Introduction Emergency Department (ED) boarding delays initiation of time-sensitive protocols for trauma patients and makes them susceptible to increased mortality and morbidity. In this study, we compared the ED boarding times of non-trauma patients and ED length of stay (LOS) of trauma patients. Methods This was a single-center retrospective cohort study in a Level 1 trauma center. The median boarding time among non-trauma patients and ED LOS among trauma patients was determined by month between the period of April 2018 to March 2019. Linear regression and Pearson correlation coefficient were used to express the magnitude and direction of the relationship between these two variables. Results During the study period, the mean number of non-trauma patients admitted in our ED per month was 1,154 and trauma patients was 89. The mean of the median boarding time per month for non-trauma patients was 76 minutes, and the mean of the median ED LOS per month for trauma patients was 198 minutes. There was a significant positive correlation between boarding time for non-trauma patients and ED LOS for trauma patients (Pearson correlation coefficient: 0.73; p = 0.007). Conclusion The long boarding times for non-trauma patients is associated with ED LOS for trauma patients, indicating that the total patient volume in the hospital contributes to the trauma patient's stay in the ED. Thus, ED LOS of trauma patients can be minimized by improving overall ED and hospital flow, including non-trauma patients.

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses

Objective

Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classification algorithms, and we use the best performing approach to identify novel risk factors of ED return visits.

Methods

We analyzed 3.2 million ED encounters with at least one diagnosis under “injury, poisoning and certain other consequences of external causes” and “external causes of morbidity.” These encounters included patients 18 years or older from across 128 emergency room facilities in the USA. For each encounter, we calculated the 72-h ED return status and retrieved 57 features from demographics, diagnoses, procedures, and medications administered during the process of administration of medical care. We implemented a mixed-effects model to assess the effects of the covariates while accounting for the hierarchical structure of the data. Additionally, we investigated the predictive accuracy of the extreme gradient boosting tree ensemble approach and compared the performance of the two methods.

Results

The mixed-effects model indicates that certain blunt force and non-blunt trauma inflates the risk of a return visit. Notably, patients with trauma to the head and patients with burns and corrosions have elevated risks. This is in addition to 11 other classes of both blunt force and non-blunt force traumas. In addition, prior healthcare resource utilization, patients who have had one or more prior return visits within the last 6 months, prior ED visits, and the number of hospitalizations within the 6 months are associated with increased risk of returning to the ED after discharge. On the one hand, the area under the receiver characteristic curve (AUROC) of the mixed-effects model was 0.710 (0.707, 0.712). On the other hand, the gradient boosting tree ensemble had a lower AUROC of 0.698 CI (0.696, 0.700) on the independent test model.

Conclusions

The proposed mixed-effects model achieved the highest known AUC and resulted in the identification of novel risk factors. The model outperformed one of the leading machine learning ensemble classifiers, the extreme gradient boosting tree in terms of model performance. The risk factors we identified can assist emergency departments to decrease the number of unplanned return visits within 72 h.

Defining and Characterizing Frequent Attenders: Systematic Literature Review and Recommendations

PURPOSE

To decrease cost and improve efficiency, health care organizations have focused on frequent attenders - patients with high health care utilization. Prior studies have investigated singular health care settings, used varying definitions of frequent attendance, and inconsistently identified factors correlated with frequent attendance. The purpose of this article is to suggest a uniform definition of frequent attenders for different health care settings and to determine factors correlated with frequent attendance.

METHODS

This systematic review of three databases identified 2761 unique articles; 174 met inclusion criteria. Studies were analyzed for their definition of frequent attenders and factors associated with frequent attendance.

RESULTS

Most studies defined frequent attenders by number of health care visits within a set time period (n=115) and top percentile cutoff (n=42). Based on averages across studies, we propose the following frequent attender definitions: for primary care, either the top 10th percentile or at least 10 visits in 12 months; for emergency room, at least 5 visits in 12 months; and for inpatient hospitalization, at least 4 admissions in 12 months. Common factors correlated with frequent attendance were mental health and chronic disease.

CONCLUSIONS

We propose definitions of frequent attenders for three common health care settings: primary care, emergency room, and inpatient. Future studies should include mental health and chronic disease, among other factors, when studying this population. Adoption of these recommendations will allow comparisons across studies such that meta-analyses may better determine interventions for more appropriate health care utilization.

Critical Care Delivery Solutions in the Emergency Department: Evolving Models in Caring for ICU Boarders

The National Academy of Medicine has identified emergency department (ED) crowding as a health care delivery problem. Because the ED is a portal of entry to the hospital, 25% of all ED encounters are related to critical illness. Crowding at both an ED and hospital level can thus lead to boarding of a number of critically ill patients in the ED. EDs are required to not only deliver immediate resuscitative and stabilizing care to critically ill patients on presentation but also provide longitudinal care while boarding for the ICU. Crowding and boarding are multifactorial and complex issues, for which different models for delivery of critical care in the ED have been described. Herein, we provide a narrative review of different models of delivery of critical care reported in the literature and highlight aspects for consideration for successful local implementation.

One-way-street revisited: Streamlined admission of critically-ill trauma patients

INTRODUCTION

Emergency department (ED) crowding is associated with increased mortality and delays in care. We developed a rapid admission pathway targeting critically-ill trauma patients in the ED. This study investigates the sustainability of the pathway, as well as its effectiveness in times of increased ED crowding.

MATERIALS & METHODS

This was a retrospective cohort study assessing the admission of critically-ill trauma patients with and without the use of a rapid admission pathway from 2013 to 2018. We accessed demographic and clinical data from trauma registry data and ED capacity logs. Statistical analyses included univariate and multivariate testing.

RESULTS

A total of 1700 patients were included. Of this cohort, 434 patients were admitted using the rapid admission pathway, whereas 1266 were admitted using the traditional pathway. In bivariate analysis, mean ED LOS was 1.54 h (95% Confidence Interval [CI]: 1.41, 1.66) with the rapid pathway, compared with 5.88 h (95% CI: 5.64, 6.12) with the traditional pathway (p < 0.01). We found no statistically significant relationship between rapid admission pathway use and survival to hospital discharge. During times of increased crowding, rapid pathway use continued to be associated with reduction in ED LOS (p < 0.01). The reduction in ED LOS was sustained when comparing initial results (2013-2014) to recent data (2015-2018).

CONCLUSION

This study found that a streamlined process to admit critically-ill trauma patients is sustainable and associated with reduction in ED LOS. As ED crowding remains pervasive, these findings support restructured care processes to limit prolonged ED boarding times for critically-ill patients.

The Impact of Bed Traffic Control and Improved Flow Process on Throughput Measures in a Metropolitan Emergency Department

INTRODUCTION

ED crowding is a complex phenomenon that presents many challenges to patients, hospitals, and staff. Using Lewin's change model, we implemented an ED improvement plan, including an innovative bed traffic control and improved flow system. We hypothesized that this plan would reduce door-to-provider time and emergency medical service-offloading time, decrease the length of stay and number of patients leaving without being seen by a physician, and increase overall patient satisfaction.

METHODS

We examined the ED improvement plan's impact on institutional throughput metrics over a 4-year period (2015-2019). Data on door-to-provider time, door-to-discharge time, patient volume, leaving without being seen by a physician, and patient satisfaction by Press Ganey were analyzed.

RESULTS

Between 2015 and 2018, the median door-to-provider time decreased 56.9% and the median door-to-discharge time decreased 29.6%. Percentage of patients who left without being seen by a physician decreased 73.8%. In 2018, the patient satisfaction rank increased by 16 points (84.2% increase). Emergency medical services-offloading time decreased significantly, prompting a change of the 30-minute cutoff to 20 minutes. In 2018, 0.84% of patients had an offloading time of more than 20 minutes. Preliminary 2019 data show maintenance of this trend for all hospital metrics.

DISCUSSION

Implementing a pod system, with flow and bed placement managed by bed traffic control, reduced door-to-provider time, door-to-discharge time, leaving without being seen by a physician, emergency medical service-offload time, and increased patient satisfaction. Our results may provide a model for other emergency departments to effectively manage the challenges of crowding.

Emergency physician-based intensive care unit for critically ill patients visiting emergency department

BACKGROUND

To provide a prompt and optimal intensive care to critically ill patients visiting our emergency department (ED), we set up and ran a specific type of emergency intensive care unit (EICU) managed by emergency physician (EP) intensivists. We investigated whether this EICU reduced the time interval from ED arrival to ICU transfer (ED-ICU interval) without altering mortality.

METHODS

This was a retrospective study conducted in a tertiary referral hospital. We collected data from ED patients who were admitted to the EICU (EICU group) and other ICUs including medical, surgical, and cardiopulmonary ICUs (other ICUs group), from August 2014 to July 2017. We compared these two groups with respect to demographic findings, including the Acute Physiology and Chronic Health Evaluation II (APACHE II) score, ED-ICU interval, ICU mortality, and hospital mortality.

RESULTS

Among the 3440 critically ill patients who visited ED, 1815 (52.8%) were admitted to the EICU during the study period. The ED-ICU interval for the EICU group was significantly shorter than that for the other ICUs group by 27.5% (5.0 ± 4.9 vs. 6.9 ± 5.4 h, p < 0.001). In multivariable analysis, the ICU mortality (odds ratio = 1.062, 95% confidence interval 0.862-1.308, p = 0.571) and hospital mortality (odds ratio = 1.093, 95% confidence interval 0.892-1.338, p = 0.391) of the EICU group were not inferior to those of the other ICUs group.

CONCLUSIONS

The EICU run by EP intensivists reduced the time interval from ED arrival to ICU transfer without altering hospital mortality.

Effect of Boarding on Mortality in ICUs

OBJECTIVES

Hospitals use a variety of strategies to maximize the availability of limited ICU beds. Boarding, which involves assigning patients to an open bed in a different subspecialty ICU, is one such practice employed when ICU occupancy levels are high, and beds in a particular unit are unavailable. Boarding disrupts the normal geographic colocation of patients and care teams, exposing patients to nursing staff with different training and expertise to those caring for nonboarders. We analyzed whether medical ICU patients boarding in alternative specialty ICUs are at increased risk of mortality.

DESIGN

Retrospective cohort study using an instrumental variable analysis to control for unmeasured confounding. A semiparametric bivariate probit estimation strategy was employed for the instrumental model. Propensity score matching and standard logistic regression (generalized linear modeling) were used as robustness checks.

SETTING

The medical ICU of a tertiary care nonprofit hospital in the United States between 2002 and 2012.

PATIENTS

All medical ICU admissions during the specified time period.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The study population consisted of 8,429 patients of whom 1,871 were boarders. The instrumental variable model demonstrated a relative risk of 1.18 (95% CI, 1.01-1.38) for ICU stay mortality for boarders. The relative risk of in-hospital mortality among boarders was 1.22 (95% CI, 1.00-1.49). GLM and propensity score matching without use of the instrument yielded similar estimates. Instrumental variable estimates are for marginal patients, whereas generalized linear modeling and propensity score matching yield population average effects.

CONCLUSIONS

Mortality increased with boarding of critically ill patients. Further research is needed to identify safer practices for managing patients during periods of high ICU occupancy.

Improving the wait time to admission by reducing bed rejections

Congestion at the emergency department (ED) is associated with increased wait times, morbidity and mortality. We have identified prolonged wait time to admission as a significant contributor to ED congestion. One of the main contributors to prolonged wait time to admission was due to rejections by ward staff for the beds allocated to newly admitted patients by the Bed Management Unit (BMU). We have identified this as a systemic issue and through this quality improvement effort, seek to reduce the incidence of bed rejections for all admitted patients by 50% from 9% to 4.5% within 6 months. We used PDSA (Plan, Do, Study, Act) cycles to implement a series of interventions, such as updating legacy categorisation of wards, instituting a 'no rejects' policy and performing ward level audits. Compared with baseline, there was reduction in rejected BMU allocation requests from 9% to 5% (p<0.01). The monthly percentage of patients with at least one rejection dropped from an average of 7% to 4% (p<0.01). With reduction in the number of rejections, the average wait time to the final request acknowledged by the ward for all admission sources decreased from 2 hours 19 min to 1 hour (p<0.01), thereby allowing the overall wait time to admission to decrease by 68 min, from 5 hours 13 min to 4 hours 5 min. Improvements in the absolute duration and variance of wait times were sustained. Although the team's initial impetus was to improve ED wait times, this hospital-wide effort improved wait times across all admission sources. There has been a resultant increase in ownership of the admissions process by both nursing and BMU staff. With the conclusion of this effort, we are looking to further reduce the wait time to admission by optimising the current bed allocation logic through another quality improvement effort.

Reasons for longer LOS at the emergency departments: Practical, patient-centred, medical, or cultural?

Emergency department (ED) overcrowding is caused by external and/or internal factors. One critical internal factor, leading to longer length of stay (LOS) at ED (eg, frequent ED users), is the physician's uncertainty in management of patients with unclear diagnosis and or complex medical history. The aim of this study was to identify whether the causes of physicians' uncertainty was practical, patient-centred, medical, or cultural. Using earlier published dimensions of uncertainty, 18 physicians were asked to reply to a template by choosing a relevant dimension that causes a delay in assessment of a known complex patient. This stage was completed by interviews through which participants had an opportunity to express their concerns and critical thoughts, if any. The data obtained from the template were collected and analysed. The interviews were recorded and transcribed verbatim. The results of the template indicated medical dimension as the main factor in delayed assessment of a complex patient. However, this finding was challenged by the results of the interviews, which indicated higher impact of personal/routines/cultural dimension (eg, being afraid of criticism, reprimand, and gossip or feelings of guilt). Although medical, patient-centred, and practical issues are important causes of longer LOS at ED, physicians' working and professional environment may have a higher impact than previously perceived. The uncertainty caused by interpersonal, organisational, and cultural issues within a clinic/hospital seems to influence the physician's ability to make decisions and thus a patient's medical outcome.

Conscious sedation and reduction of fractures in the paediatric population: an orthopaedic perspective

PURPOSE

Closed reduction under conscious sedation in the emergency department (ED) has been demonstrated to provide cost-effective, timely care. There has been little research into the efficacy of conscious sedation and reduction from an orthopaedic trauma perspective. This study describes the epidemiology and outcomes associated with fracture conscious sedation and reduction in our level I paediatric ED.

METHODS

All fracture patients presenting overnight to our level I trauma centre ED between 01 June 2016 and 30 June 2017 were identified. Patient records were reviewed to determine diagnoses, treatments and outcomes. The rate of repeat intervention after successful conscious sedation and reduction and rate of changes in management in which the orthopaedic resident's overnight management plan to provide procedural sedation was altered to surgical intervention after morning case review rounds was calculated.

RESULTS

Conscious sedation and reduction was performed on a total of 386 patients covering ten fracture types during the course of our study, with distal radius fractures (n = 167, 43.3%) comprising the majority of cases. A total of 53 cases (13.7%, 53/386) lost alignment and required repeat intervention, consisting of 33 cases (8.5%, 33/386) that required repeat surgery and 5.2% (20/386) that required cast wedging. In all, 12 patients (3.1%, 12/386) initially reduced under conscious sedation required a change in management and surgical intervention. There were five cases of growth arrest and two cases of malunion.

CONCLUSIONS

Conscious sedation and reduction provides an alternative to general anaesthesia for many paediatric trauma injuries without compromising patient outcomes.

LEVEL OF EVIDENCE

IV.

Impact of triage-to-admission time on patient outcome in European intensive care units: A prospective, multi-national study

PURPOSE

Ubiquitous bed shortages lead to delays in intensive care unit (ICU) admissions worldwide. Assessing the impact of delayed admission must account for illness severity. This study examined both the relationship between triage-to-admission time and 28-day mortality and the impact of controlling for Simplified Acute Physiology Score (SAPS) II scores on that relationship.

METHODS

Prospective cross-sectional analysis of referrals to eleven ICUs in seven European countries between 2003 and 2005. Outcomes among patients admitted within versus after 4 h were compared using a Chi-square test. Triage-to-admission time was also analyzed as a continuous variable; outcomes were assessed using a non-parametric Kruskal-Wallis test.

RESULTS

Among 3175 patients analyzed, triage-to-admission time was 2.1 ± 3.9 h. Patients admitted within 4 h had higher SAPS II scores (33.6 versus 30.6, Pearson correlation coefficient -0.07, p < 0.0001). 28-day mortality was surprisingly higher among patients admitted earlier (29.6 vs 25.2%, OR 1.25, 95% CI 0.99-1.58, p = 0.06). Even after adjusting for SAPS II scores, delayed admission was not associated with higher mortality (OR 1.08, CI 0.83-1.41, p = 0.58).

CONCLUSIONS

Even after accounting for quantifiable parameters of illness severity, delayed admission did not negatively impact outcome. Triage practices likely influence outcomes. Severity scores may not fully reflect illness acuity or trajectory.

The effect of emergency department crowding on lung-protective ventilation utilization for critically ill patients

OBJECTIVE

To measure effects of ED crowding on lung-protective ventilation (LPV) utilization in critically ill ED patients.

METHODS

This is a retrospective cohort study of adult mechanically ventilated ED patients admitted to the medical intensive care unit (MICU), over a 3.5-year period at a single academic tertiary care hospital. Clinical data, including reason for intubation, severity of illness (MPM₀-III), acute respiratory distress syndrome (ARDS) risk score (EDLIPS), and ventilator settings were extracted via electronic query of electronic health record and standardized chart abstraction. Crowding metrics were obtained at 5-min intervals and averaged over the ED stay, stratified by acuity and disposition. Multivariate logistic regression was used to predict likelihood of LPV prior to ED departure.

RESULTS

Mechanical ventilation was used in 446 patients for a median ED duration of 3.7 h (interquartile ratio, IQR, 2.3, 5.6). Mean MPM₀-III score was 32.5 ± 22.7, with high risk for ARDS (EDLIPS ≥5) seen in 373 (82%) patients. Initial and final ED ventilator settings differed in 134 (30.0%) patients, of which only 47 (35.1%) involved tidal volume changes. Higher percentages of active ED patients (workup in-progress) and those requiring eventual admission were associated with lower odds of LPV utilization by ED departure (OR 0.97, 95%CI 0.94-1.00; OR 0.97, 95%CI 0.94-1.00, respectively). In periods of high volume, ventilator adjustments to settings other than the tidal volume were associated with higher odds of LPV utilization. Reason for intubation, MPM₀-III, and EDLIPS were not associated with LPV utilization, with no interactions detected in times of crowding.

CONCLUSIONS

ED patients remain on suboptimal tidal volume settings with infrequent ventilator adjustments during the ED stay. Hospitals should focus on both systemic factors and bedside physician and/or respiratory therapist interventions to increase LPV utilization in times of ED boarding and crowding for all patients.

Recurrent Emergency Department Users: Two Categories with Different Risk Profiles

Recurrent emergency department (ED) visits are responsible for an increasing proportion of overcrowding. Therefore, our aim was to investigate the characteristics and prevalence of recurrent ED visitors as well as to determine risk factors associated with multiple ED visits. ED patients visiting the ED of a tertiary care hospital at least four times consecutively in 2015 were enrolled. Of 33,335 primary ED visits, 1921 ED visits (5.8%) were performed by 372 ED patients who presented in the ED at least four times within the one-year period. Two different categories of recurrent ED patients were identified: repeated ED users presenting always with the same symptoms and frequent ED visitors who were suffering from different symptoms on each ED visit. Repeated ED users had more ED visits (p < 0.001) and needed more hospital admissions (p < 0.010) compared to frequent ED users. Repeated ED users visited the ED more likely due to symptoms from chronic obstructive pulmonary diseases (p < 0.001) and mental disorders (p < 0.001). In contrast, frequent ED patients showed to be at risk for multiple ED visits when being disabled (p = 0.001), had an increased Charlson co-morbidity index (p = 0.004) or suffering from rheumatic diseases (p < 0.001). A small number of recurrent ED visitors determines a relevant number of ED visits with a relevance for and impact on patient centred care and emergency services. There are two categories of recurrent ED users with different risk factors for multiple ED visits: repeated and frequent. Therefore, multi-professional follow-up care models for recurrent ED patients are needed to improve patients' needs, quality of life as well as emergency services.