Emergency department crowding predicts admission length-of-stay but not mortality in a large health system

A literature-based approach to predict continuous hospital length of stay in adult acute care patients using admission variables: A single university center experience

PURPOSE

To review the existing literature on predicting length of stay (LOS) and to apply the findings on a Real World Data example in a single hospital.

METHODS

Performing a literature review on PubMed and Embase, focusing on adults, acute conditions, and hospital-wide prediction of LOS, summarizing all the variables and statistical methods used to predict LOS. Then, we use this set of variables on a single university hospital and run an XGBoost model with Survival Cox regression on the LOS, as well as a logistic regression on binary LOS (cut-off at 4 days). Model metrics are the concordance index (c-index) and area under the curve (AUC).

RESULTS

After applying the search strategy and exclusion criteria, 57 articles are included in the study. The list of variables is long, but mostly non-clinical data are used in the existing literature. A wide range of statistical methods are used, with a recent trend toward machine learning models. The XGBoost model results for the Cox regression in a C-index of 0.87, and the logistic regression on binary LOS has an AUC of 0.94.

CONCLUSIONS

Many variables identified in the literature are not available at the time of admission, yet they are still used in models for predicting LOS. Machine learning has become the preferred statistical approach in recent studies, though mainly for binary LOS predictions. Based on the current literature, it remains challenging to derive a practical and high performing model for continuous LOS prediction.

Measurement of Cost of Boarding in the Emergency Department Using Time-Driven Activity-Based Costing

STUDY OBJECTIVE

Boarding admitted patients in emergency departments (EDs) is a national crisis that is worsening despite potential financial disadvantages. The objective of this study was to assess costs associated with boarding.

METHODS

We conducted a prospective, observational investigation of patients admitted through an ED for management of acute stroke at a large, urban, academic, comprehensive stroke center hospital. We employed time-driven activity-based costing methodology to estimate cost for patient care activities during admission and aggregated results to estimate the total cost of boarding versus inpatient care. Primary outcomes were total daily costs per patient for medical-surgical (med/surg) boarding, med/surg inpatient care, ICU boarding, and ICU inpatient care.

RESULTS

The total daily cost per patient with acute stroke was US$1856, for med/surg boarding versus US$993 for med/surg inpatient care and US$2267, for ICU boarding versus US$2165, for ICU inpatient care. These differences were even greater when accounting for costs associated with traveler nurses. ED nurses spent 293 min/d (mean) caring for each med/surg boarder; inpatient nurses spent 313 min/d for each med/surg inpatient. ED nurses spent 419 min/d caring for each ICU boarder; inpatient nurses spent 787 min/d for each ICU inpatient. Neurology attendings and residents spent 25 and 52 min/d caring for each med/surg boarder versus 62 minutes and 90 minutes for each med/surg inpatient, respectively.

CONCLUSION

Using advanced cost-accounting methods, our investigation provides novel evidence that boarding of admitted patients is financially costly, adding greater urgency for elimination of this practice.

Impact of emergency department length of stay on in-hospital mortality: a retrospective cohort study

BACKGROUND AND IMPORTANCE

Emergency Department (ED) workload may lead to ED crowding and increased ED length of stay (LOS). ED crowding has been shown to be associated with adverse events and increasing mortality. We hypothesised that ED-LOS is associated with mortality.

OBJECTIVE

To study the relationship between ED-LOS and in-hospital mortality.

DESIGN

Observational retrospective cohort study.

SETTINGS AND PARTICIPANTS

From 1 January 2015 to 30 September 2018, all visits by patients aged 15 or older to one of the two ED at Toulouse University Hospital were screened. Patients admitted to the hospital after ED visits were included. Visits followed by ED discharge, in-ED death or transfer to ICU or another hospital were not included.

OUTCOME MEASURE AND ANALYSIS

The primary outcome was 30-day in-hospital mortality. ED-LOS was defined as time from ED registration to inpatient admission. ED-LOS was categorised according to quartiles [<303 min (Q1), between 303 and 433 minutes (Q2), between 434 and 612 minutes (Q3) and >612 min (Q4)]. A multivariable logistic regression tested the association between ED-LOS and in-hospital mortality.

MAIN RESULTS

A total of 49 913 patients were admitted to our hospital after ED visits and included in the study. ED-LOS was not independently associated with in-hospital mortality. Compared to ED-LOS < 303 min (Q1, reference), odd-ratios (OR) [95% CI] of in-hospital mortality for Q2, Q3, and Q4 were respectively 0.872 [0.747-1.017], 0.906 [0.777-1.056], and 1.137 [0.985-1.312]. Factors associated to in-hospital mortality were: aged over 75 years (OR [95% CI] = 4.3 [3.8-4.9]), Charlson Comorbidity Index score > 1 (OR [95% CI] = 1.3 [1.1-1.5], and 2.2 [1.9-2.5] for scores 2 and ≥ 3 respectively), high acuity at triage (OR [95% CI] = 3.9 [3.5-4.4]), ED visit at Hospital 1 (OR [95% CI] = 1.6 [1.4-1.7]), and illness diagnosis compared to trauma (OR [95% CI] = 2.1 [1.7-2.6]). Night-time arrival was associated with decreased in-hospital mortality (OR [95% CI] = 0.852 [0.767-0.947]).

CONCLUSION

In this retrospective cohort study, there was no independent association between ED-LOS before admission to general non-ICU wards and in-patient mortality.

Emergency department crowding increases 10-day mortality for non-critical patients: a retrospective observational study

The current evidence suggests that higher levels of crowding in the Emergency Department (ED) have a negative impact on patient outcomes, including mortality. However, only limited data are available about the association between crowding and mortality, especially for patients discharged from the ED. The primary objective of this study was to establish the association between ED crowding and overall 10-day mortality for non-critical patients. The secondary objective was to perform a subgroup analysis of mortality risk separately for both admitted and discharged patients. An observational single-centre retrospective study was conducted in the Tampere University Hospital ED from January 2018 to February 2020. The ED Occupancy Ratio (EDOR) was used to describe the level of crowding and it was calculated both at patient's arrival and at the maximum point during the stay in the ED. Age, gender, Emergency Medical Service transport, triage acuity, and shift were considered as confounding factors in the analyses. A total of 103,196 ED visits were included. The overall 10-day mortality rate was 1.0% (n = 1022). After controlling for confounding factors, the highest quartile of crowding was identified as an independent risk factor for 10-day mortality. The results were essentially similar whether using the EDOR at arrival (OR 1.31, 95% CI 1.07-1.61, p = 0.009) or the maximum EDOR (OR 1.27, 95% CI 1.04-1.56, p = 0.020). A more precise, mortality-associated threshold of crowding was identified at EDOR 0.9. The subgroup analysis did not yield any statistically significant findings. The risk for 10-day mortality increased among non-critical ED patients treated during the highest EDOR quartile.

Association Between the Emergency Department Length of Stay and in-Hospital Mortality: A Retrospective Cohort Study

Purpose

The number of emergency department (ED) visits and prolonged ED length of stay (LOS) are increasing worldwide. Prolonged ED LOS may be associated with a higher risk of in-hospital mortality. Here, we analysed the association between of ED LOS and the risk of in-hospital mortality in a hospital in Jakarta, Indonesia.

Patients and methods

This was a single-centre retrospective cohort study performed in a referral academic hospital in Jakarta, Indonesia. Data on ED visits in 2019 were obtained from the electronic medical records. ED patient was used as the unit of the analysis. The dependent variable was all-cause in-hospital mortality during one's visit. The main independent variable was ED LOS with respect to approval (<8 h) and prolonged (≥8 h). Potential confounders were sex, age, triage categories, trauma-related case, malignancy-related case, labour-related case, and referral patients from other healthcare facilities. Multivariate logistic regression analysis was performed to evaluate the association of ED LOS and in-hospital mortality after adjusting for other confounders.

Results

There were 18,553 participants included in the analysis. The in-hospital mortality was 13.5% among all participants, and 63.5% participants had an ED LOS ≥8 h. Multivariate analysis showed that a prolonged ED LOS was associated with an increased risk of in-hospital mortality (adjusted relative risk, 2.69; 95% confidence interval, 2.40-3.03; P<0.001).

Conclusion

Prolonged ED LOS was associated with risk an increased of in-hospital mortality after adjusting for several confounders. In future, hospital service plans should aim to reduce ED LOS and increase patient flow from the ED to in-patient wards.

Association of emergency department crowding with inpatient outcomes

OBJECTIVE

To examine the association of higher emergency department (ED) census with inpatient outcomes on the day of discharge (inpatient length of stay, in-hospital mortality, ED revisits, and readmissions).

DATA SOURCES AND STUDY SETTING

All-payer ED and inpatient discharge data and hospital characteristics data from all non-federal, general, and acute care hospitals in the state of California from October 1, 2015 to December 31, 2017.

STUDY DESIGN

In retrospective data analysis, we examined whether ED census was associated with inpatient outcomes for all inpatients, including those not admitted through the ED. The main predictor variable was ED census on day of discharge, categorized based on hospital year and day of week. Separate linear regression models with robust SEs and hospital fixed effects examined the association of ED census on inpatient outcomes (length of stay, 3-day ED revisit, 30-day all-cause readmission, in-hospital mortality), controlling for patient and visit-level factors. We stratified analyses by whether admission was elective or unscheduled.

EXTRACTION METHODS

Inpatient discharges in non-federal, general medical hospitals with EDs.

PRINCIPAL FINDINGS

We examined 5,784,253 discharges. The adjusted model showed that, compared to when the ED was below the median, higher ED census on the day of discharge was associated with longer inpatient length of stay, lower readmissions, and higher in-hospital mortality (90th percentile for length of stay: +0.8% [95% confidence interval, CI: +0.6% to +1.1%]; readmissions: -0.59 percentage points [or -5.6%] [95% CI: -0.0071 to -0.0048]; mortality: +0.14 percentage points [or +5.4%] [95% CI: +0.0009 to +0.0018]). [Correction added on 18 November 2022, after first online publication: '[odds rato, OR -5.6%]' and '[OR +5.4%]' of the preceding sentence have been corrected to '[or -5.6%]' and '[or +5.4%]', respectively, in this version.] Results for length of stay were primarily driven by patients with elective admissions, while results for readmissions and in-hospital mortality were primarily driven by patients with unscheduled admissions.

CONCLUSIONS

This study suggests that ED crowding may affect inpatients throughout the hospital, even patients who are already admitted to the hospital.

Emergency department crowding and mortality: an observational multicenter study in Sweden

Background

Emergency department (ED) crowding is a serious problem worldwide causing decreased quality of care. It is reasonable to assume that the negative effects of crowding are at least partially due to high staff workload, but previous crowding metrics based on high workload have not been generalisable to Swedish EDs and have not been associated with increased mortality, in contrast to, e.g., occupancy rate. We recently derived and validated the modified Skåne Emergency Department Assessment of Patient Load model (mSEAL) that measures crowding based on staff workload in Swedish EDs, but its ability to identify situations with increased mortality is unclear. In this study, we aimed to investigate the association between ED crowding measured by mSEAL model, or occupancy rate, and mortality.

Methods

All ED patients from 2017-01-01 to 2017-06-30 from two regional healthcare systems (Skåne and Östergötland Counties with a combined population of approximately 1.8 million) in Sweden were included. Exposure was ED- and hour-adjusted mSEAL or occupancy rate. Primary outcome was mortality within 7 days of ED arrival, with one-day and 30-day mortality as secondary outcomes. We used Cox regression hazard ratio (HR) adjusted for age, sex, arrival by ambulance, hospital admission and chief complaint.

Results

We included a total of 122,893 patients with 168,900 visits to the six participating EDs. Arriving at an hour with a mSEAL score above the 95th percentile for that ED and hour of day was associated with an non-significant HR for death at 7 days of 1.04 (95% CI 0.96-1.13). For one- and 30-day mortality the HR was non-significant at 1.03 (95% CI 0.9-1.18) and 1.03 (95% CI 0.97-1.09). Similarly, occupancy rate above the 95th percentile with a HR of 1.04 (95% CI 0.9-1.19), 1.03 (95%CI 0.95-1.13) and 1.04 (95% CI 0.98-1.11) for one-, 7- and 30-day mortality, respectively.

Conclusion

In this multicenter study in Sweden, ED crowding measured by mSEAL or occupancy rate was not associated with a significant increase in short-term mortality.

Patterns in Patient Encounters and Emergency Department Capacity in California, 2011-2021

Importance

The health care system has undergone major changes in the past decade, and emergency department (ED) crowding has worsened over time; however, the most recent patterns in ED capacity and use in California have yet to be studied.

Objective

To analyze patterns in ED capacity and utilization in California hospitals from 2011 to 2021.

Design, Setting, and Participants

This retrospective cohort study used data from the California Department of Health Care Access and Information and the US Census Bureau to analyze ED facility characteristics from more than 400 general acute care hospitals with more than 320 EDs in California as well as patients who presented to those EDs between January 1, 2011, and December 31, 2021.

Main Outcomes and Measures

Linear patterns (measured by percentage change) in total annual ED capacity (volume of hospital beds, EDs, ED treatment stations, and trauma centers) and ED use (ED visits by disposition and acuity) were assessed as primary outcomes. Patterns in ambulance diversion hours and the number of patients who left the ED without being seen were also examined as secondary outcomes. Visit acuity was categorized into 5 levels by increasing severity (minor, low to moderate, moderate, severe without threat, and severe with threat) based on California Department of Health Care Access and Information descriptions corresponding to Current Procedural Terminology codes.

Results

In the prepandemic period (2011-2019), the total population of California increased from 37 638 369 to 39 512 223 (5.0%; 95% CI, 4.1%-5.8%), then decreased to 39 237 836 in 2021 (0.7%; 95% CI, -3.9% to 2.5%). Over the entire study period (2011-2021), the total California population increased by 4.2% (95% CI, 3.3%-5.2%). From 2011 to 2019, the annual number of ED visits increased from 12 054 885 to 14 876 653 (23.4%; 95% CI, 20.0%-26.8%) before decreasing to 12 944 692 in 2021 (-13.0%; 95% CI, -33.1% to 7.1%); from 2011 to 2021, total ED visits increased by 7.4% (95% CI, 5.6%-9.1%). From 2011 to 2021, the total number of EDs decreased from 339 to 326 (-3.8%; 95% CI, -4.4% to -3.2%) and the total number of hospital beds decreased from 75 940 to 74 052 (-2.5%; 95% CI, -3.3% to -1.6%), while the number of ED treatment stations in these fewer EDs increased from 7159 to 8667 (21.1%; 95% CI, 19.7%-22.4%). The number of visits rated as severe with threat also increased, from 2 011 637 in 2011 to 3 375 539 in 2021 (67.8%; 95% CI, 59.7%-75.9%), while visits rated as minor decreased from 913 712 to 336 071 (-63.2%; 95% CI, -75.2% to -51.2%) over the same period.

Conclusions and Relevance

In this cohort study, multiple measures of ED capacity did not proportionally increase with the increasing demand for services; however, the COVID-19 pandemic appears to have substantially affected some of these patterns. These findings may be helpful to policy makers and health care stakeholders when planning resource allocation of limited health care resources.

Operations Factors Associated with Emergency Department Length of Stay: Analysis of a National Operations Database

Introduction: Prolonged emergency department (ED) length of stay (LOS) has been shown to adversely affect patient care. We sought to determine factors associated with ED LOS via analysis of a large, national, ED operations database. Methods: We performed retrospective, multivariable, linear regression modeling using the 2019 Emergency Department Benchmarking Alliance survey results to identify associated factors of ED LOS for admitted and discharged patients. Results: A total of 1,052 general and adult-only EDs responded to the survey. Median annual volume was 40,946. The median admit and discharge LOS were 289 minutes and 147 minutes, respectively. R-squared values for the admit and discharge models were 0.63 and 0.56 with out-of-sample R-squared values of 0.54 and 0.59, respectively. Both admit and discharge LOS were associated with academic designation, trauma level designation, annual volume, proportion of ED arrivals occurring via emergency medical services, median boarding, and use of a fast track. Additionally, admit LOS was associated with transfer-out percentage, and discharge LOS was associated with percentage of high Current Procedural Terminology, percentage of patients <18 years old, use of radiographs and computed tomography, and use of an intake physician. Conclusion: Models derived from a large, nationally representative cohort identified diverse associated factors of ED length of stay, several of which were not previously reported. Dominant within the LOS modeling were patient population characteristics and other factors extrinsic to ED operations, including boarding of admitted patients, which was associated with both admitted and discharged LOS. The results of the modeling have significant implications for ED process improvement and appropriate benchmarking.

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

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

Emergency Department Overcrowding: Understanding the Factors to Find Corresponding Solutions

It is certain and established that overcrowding represents one of the main problems that has been affecting global health and the functioning of the healthcare system in the last decades, and this is especially true for the emergency department (ED). Since 1980, overcrowding has been identified as one of the main factors limiting correct, timely, and efficient hospital care. The more recent COVID-19 pandemic contributed to the accentuation of this phenomenon, which was already well known and of international interest. Considering what would appear to be a trivial definition of overcrowding, it may seem simple for the reader to hypothesize solutions for what seems to be one of the most avoidable problems affecting the hospital system. However, proposing solutions to overcrowding, as well as their implementation, cannot be separated from a correct and precise definition of the issue, which must consider the main causes and aggravating factors. In light of the need of finding solutions that can put an end to hospital overcrowding, this review aims, through a review of the literature, to summarize the triggering factors, as well as the possible solutions that can be proposed.

Measures of Emergency Department Crowding, a Systematic Review. How to Make Sense of a Long List

Emergency department (ED) crowding, a common and serious phenomenon in many countries, lacks standardized definition and measurement methods. This systematic review critically analyzes the most commonly studied ED crowding measures. We followed the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. We searched PubMed/Medline Database for all studies published in English from January 1st, 1990, until December 1st, 2020. We used the National Institute of Health (NIH) Quality Assessment Tool to grade the included studies. The initial search yielded 2293 titles and abstracts, of whom we thoroughly reviewed 109 studies, then, after adding seven additional, included 90 in the final analysis. We excluded simple surveys, reviews, opinions, case reports, and letters to the editors. We included relevant papers published in English from 1990 to 2020. We did not grade any study as poor and graded 18 as fair and 72 as good. Most studies were conducted in the USA. The most studied crowding measures were the ED occupancy, the ED length of stay, and the ED volume. The most heterogeneous crowding measures were the boarding time and number of boarders. Except for the National ED Overcrowding Scale (NEDOCS) and the Emergency Department Work Index (EDWIN) scores, the studied measures are easy to calculate and communicate. Quality of care was the most studied outcome. The EDWIN and NEDOCS had no studies with the outcome mortality. The ED length of stay had no studies with the outcome perception of care. ED crowding was often associated with worse outcomes: higher mortality in 45% of the studies, worse quality of care in 75%, and a worse perception of care in 100%. The ED occupancy, ED volume, and ED length of stay are easy to measure, calculate and communicate, are homogenous in their definition, and were the most studied measures.

Association between emergency department length of stay and patient outcomes: A systematic review

In this review, we investigate associations between time spent in the emergency department (ED) and patient reported outcomes. ED staff provide initial assessment, treatment and referral to patients presenting with an acute status to the hospital 24 h a day. ED length of stay, including ED boarding, and treatment received in the ED may affect patient outcomes. In this review we considered published studies that explored the association of ED length of stay of individuals of any age with their subsequent outcomes, including mortality and inpatient length of stay (IPLOS). Joanna Briggs Institute methods for systematic reviews of association were followed. Search strategies were developed to identify studies published in English since 2000 for inclusion. Two reviewers assessed the studies for inclusion and methodological quality and extracted data independently. In total, 34 studies were included in the review, including one case-control, one analytical cross-sectional, and 32 retrospective cohort studies, with a total sample size of 2,308,840 patients. Overall, there were variable associations of time spent in the ED and mortality, IPLOS, time-to-treatment and adverse events. However, findings indicated that older people are at risk for longer ED stays. They may also experience higher mortality. Specific focus should be placed upon elderly people in the ED, to reduce their exposure to the ED environment where possible and to implement focused initiatives that address their specific and complex treatment needs. We conclude that the diversity of individual settings and health systems will require locally defined and relevant solutions to locally identified issues.

The prediction of hospital length of stay using unstructured data

Objective

This study aimed to assess the performance improvement for machine learning-based hospital length of stay (LOS) predictions when clinical signs written in text are accounted for and compared to the traditional approach of solely considering structured information such as age, gender and major ICD diagnosis.

Methods

This study was an observational retrospective cohort study and analyzed patient stays admitted between 1 January to 24 September 2019. For each stay, a patient was admitted through the Emergency Department (ED) and stayed for more than two days in the subsequent service. LOS was predicted using two random forest models. The first included unstructured text extracted from electronic health records (EHRs). A word-embedding algorithm based on UMLS terminology with exact matching restricted to patient-centric affirmation sentences was used to assess the EHR data. The second model was primarily based on structured data in the form of diagnoses coded from the International Classification of Disease 10th Edition (ICD-10) and triage codes (CCMU/GEMSA classifications). Variables common to both models were: age, gender, zip/postal code, LOS in the ED, recent visit flag, assigned patient ward after the ED stay and short-term ED activity. Models were trained on 80% of data and performance was evaluated by accuracy on the remaining 20% test data.

Results

The model using unstructured data had a 75.0% accuracy compared to 74.1% for the model containing structured data. The two models produced a similar prediction in 86.6% of cases. In a secondary analysis restricted to intensive care patients, the accuracy of both models was also similar (76.3% vs 75.0%).

Conclusions

LOS prediction using unstructured data had similar accuracy to using structured data and can be considered of use to accurately model LOS.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12911-021-01722-4.

Mixed effect of increasing outflow of medical patients from an emergency department

Background and aim

Since 2014, the annual number of patients entering our emergency department (ED) has increased significantly. These were primarily Internal Medicine (IM) patients, and of these, 25–30% were admitted. The present governmental policy presents a deterrent to adding IM beds for these patients, and Emergency and IM departments cope with ever-increasing number of IM patients. We describe a quality improvement intervention to increase outflow of IM patients from the ED to the IM departments.

Methods

We conducted a quality improvement intervention at the Shaare Zedek Medical Center from 2014 to 2018. The first stage consisted of an effort to increase morning discharges from the IM departments. The second stage consisted of establishing a process to increase the number of admissions to the IM departments from the ED.

Results

Implementation of the first stage led to an increased morning discharge rate from a baseline of 2–4 to 18%. The second stage led to an immediate mean (± SD) morning transfer of 35 ± 7 patients to the medical departments (8–12 per department), providing significant relief for the ED. However, the additional workload for the IM departments’ medical and nursing staff led to a rapid decrease in morning discharges, returning to pre-intervention rates. Throughout the period of the new throughput intervention, morning admissions increased from 30 to > 70%, and were sustained. The number of patients in each department increased from 36 to 38 to a new steady state of 42–44, included constant hallway housing, and often midday peaks of 48–50 patients. Mean length of stay did not change. IM physician and nurse dissatisfaction led to increased number of patients being admitted during the evening and night hours and fewer during the morning.

Conclusion

We describe a quality improvement intervention to improve outflow of medical patients from the ED in the morning hours. The new ED practices had mixed effects. They led to less ED crowding in the morning hours but increased dissatisfaction among the IM department medical and nursing staff due to an increased number of admissions in a limited number of hours. The present governmental reimbursement policy needs to address hospital overcrowding as it relates to limited community healthcare beds and an aging population.

The Association of Workload and Outcomes in the Pediatric Cardiac ICU

OBJECTIVES

Healthcare workload has emerged as an important metric associated with poor outcomes. To measure workload, studies have used bed occupancy as a surrogate. However, few studies have examined frontline provider (fellows, nurse practitioners, physician assistants) workload and outcomes. We hypothesize frontline provider workload, measured by bed occupancy and staffing, is associated with poor outcomes and unnecessary testing.

DESIGN

A retrospective single-center, time-stamped orders, ordering provider identifiers, and patient data were collected. Regression was performed to study the influence of occupancy on orders, length of stay, and mortality, controlling for age, weight, admission type, Society of Thoracic Surgery-European Association for Cardio-Thoracic Surgery Congenital Heart Surgery Mortality score, diagnosis, number of surgeries, orders, provider staffing, attending experience, and time fixed effects.

SETTING

Twenty-seven bed tertiary cardiac ICU in a free-standing children's hospital.

PATIENTS

Patients (0-18 yr) admitted to the pediatric cardiac ICU, January 2018 to December 2019.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

There were 16,500 imaging and 73,113 laboratory orders among 1,468 patient admissions. Median age 6 months (12 d to 5 yr), weight 6.2 kg (3.7-16.2 kg); 840 (57.2%) surgical and 628 (42.8%) medical patients. ICU teams consisted of 16 attendings and 31 frontline providers. Mortality 4.4%, median stay 5 days (2-11 d), and median bed occupancy 89% (78-93%). Every 10% increase in bed occupancy had 7.2% increase in imaging orders per patient (p < 0.01), 3% longer laboratory turn-around time (p = 0.015), and 3 additional days (p < 0.01). Higher staffing (> 3 providers) was associated with 6% less imaging (p = 0.03) and 3% less laboratory orders (p = 0.04). The number of "busy days" (bed occupancy > 89%) was associated with longer stays (p < 0.01), and increased mortality (p < 0.01).

CONCLUSIONS

Increased bed occupancy and lower staffing were associated with increased mortality, length of stay, imaging orders, and laboratory turn-around time. The data demonstrate performance of the cardiac ICU system is exacerbated during high occupancy and low staffing.

Analysis of Factors Associated With Length of Stay of Opioid-Related Emergency Department Visits

Introduction and Objective: Emergency department (ED) length of stay (LOS) is an important indicator of the quality of care in ED and is associated with patients’ outcomes and healthcare costs. However, there is limited data on how the patient characteristics affect the ED LOS of opioid-related visits. This study aims to identify and quantify the effect of patient-related characteristics on LOS of opioid-related ED visits.

Methods: This is a retrospective analysis of electronic health records (EHR) of patients with diagnoses of opioid abuse. The study included patients with a diagnosis of opioid abuse who visited the ED at Christiana Care Hospital from January 1, 2017, to December 31, 2018 (N=5,661). The opioid-related visits were identified using ICD-10 diagnosis codes. We used accelerated failure time (AFT) models, a time-to-event analysis approach to evaluate the relationships of different patient characteristics with ED LOS.

Results: The mean age of the study population was 39 years. The study population had 40% female, 20% Black/African American, and 5% Hispanic or Latino. The prevalence of co-use of cocaine and co-use of alcohol was 11%, and 9%, respectively. Also, 58% had mental health comorbidity, and 1% were homeless. The distribution of ED LOS was right-skewed with a median of 4.3 (IQR: 2.6, 6.8). Co-use of alcohol (time ratio, TR: 1.31, CI: 1.23-1.40), co-use of cocaine (TR: 1.18, CI: 1.11-1.25), the presence of mental health comorbidity (TR: 1.05, CI 1.01-1.09), and homelessness (TR: 1.57, CI: 1.32-1.86) were associated with increased ED LOS.

Conclusions: Co-use of alcohol, co-use of cocaine, homelessness, and mental health comorbidity are associated with the longer LOS of opioid-related ED visits.

Performance evaluation of Emergency Department patient arrivals forecasting models by including meteorological and calendar information: A comparative study

The volume of daily patient arrivals at Emergency Departments (EDs) is unpredictable and is a significant reason of ED crowding in hospitals worldwide. Timely forecast of patients arriving at ED can help the hospital management in early planning and avoiding of overcrowding. Many different ED patient arrivals forecasting models have previously been proposed by using time series analysis methods. Even though the time series methods such as Linear and Logistic Regression, Autoregressive Integrated Moving Average (ARIMA), Seasonal ARIMA (SARIMA), Exponential Smoothing (ES), and Artificial Neural Network (ANN) have been explored extensively for the ED forecasting model development, the few significant limitations of these methods associated in the analysis of time series data make the models inadequate in many practical situations. Therefore, in this paper, Machine Learning (ML)-based Random Forest (RF) regressor, and Deep Neural Network (DNN)-based Long Short-Term Memory (LSTM) and Convolutional Neural network (CNN) methods, which have not been explored to the same extent as the other time series techniques, are implemented by incorporating meteorological and calendar parameters for the development of forecasting models. The performances of the developed three models in forecasting ED patient arrivals are evaluated. Among the three models, CNN outperformed for short-term (3 days in advance) patient arrivals prediction with Mean Absolute Percentage Error (MAPE) of 9.24% and LSTM performed better for moderate-term (7 days in advance) patient arrivals prediction with MAPE of 8.91% using weather forecast information. Whereas, LSTM model outperformed with MAPE of 8.04% compared to 9.53% by CNN and 10.10% by RF model for current day prediction of patient arrivals using 3 days past weather information. Thus, for short-term ED patient arrivals forecasting, DNN-based model performed better compared to RF regressor ML-based model.

The 4-hour target in the emergency department, in-hospital mortality, and length of hospitalization: A single center-retrospective study

BACKGROUND

The four-hour (4 h') rule in the emergency department (ED) is a performance-based measure introduced with the objective to improve the quality of care. We evaluated the association between time in the ED with in-hospital mortality and hospital length of stay (LOS).

METHODS

This was a retrospective study performed in one public hospital with over 100,000 ED referrals per year. Hospitalizations from the ED during 2017 were analyzed. We defined time in the ED as either: until a decision was made (DED); or total time in the ED (TED). In-hospital mortality and LOS were evaluated for patients with DED or TED within and beyond 4 h'.

RESULTS

Compared to patients with TED or DED within 4 h', in-hospital mortality did not increase in patients with TED beyond 4 h' (2.8% vs. 3.1%, non-significant), or DED beyond 4 h' (2.1% vs. 3.2%, p < 0.001). LOS did increase in patients with either DED or TED beyond 4 h' (p < 0.001). In-hospital mortality increased with increasing DED-TED intervals for patients hospitalized in the internal medicine departments: 3.7% (0-1 h'), 5.1% (1-2 h'), 5.7% (2-3 h'), and 7.1% (>3 h') (p < 0.001).

CONCLUSIONS

In-hospital mortality was not associated with time in the ED beyond 4 h'. LOS, however, was increased in this group of patients. Decreased LOS observed in patients with time in the ED within 4 h', does not support patients' risk as a contributing factor leading to higher trends in mortality observed in this patient group. In-hospital mortality was associated with an increase in DED-TED intervals in patients hospitalized in the internal medicine departments.

Delays in antibiotic redosing: Association with inpatient mortality and risk factors for delay

OBJECTIVE

Although timely administration of antibiotics has an established benefit in serious bacterial infection, the majority of studies evaluating antibiotic delay focus only on the first dose. Recent evidence suggests that delays in redosing may also be associated with worse clinical outcome. In light of the increasing burden of boarding in Emergency Departments (ED) and subsequent need to redose antibiotic in the ED, we examined the association between delayed second antibiotic dose administration and mortality among patients admitted from the ED with a broad array of infections and characterized risk factors associated with delayed second dose administration.

METHODS

We performed a retrospective cohort study of patients admitted through five EDs in a single healthcare system from 1/2018 through 12/2018. Our study included all patients, aged 18 years or older, who received two intravenous antibiotic doses within a 30-h period, with the first dose administered in the ED. Patients with end stage renal disease, cirrhosis and extremes of weight were excluded due to a lack of consensus on antibiotic dosing intervals for these populations. Delay was defined as administration of the second dose at a time-point greater than 125% of the recommended interval. The primary outcome was in-hospital mortality.

RESULTS

A total of 5605 second antibiotic doses, occurring during 4904 visits, met study criteria. Delayed administration of the second dose occurred during 21.1% of visits. After adjustment for patient characteristics, delayed second dose administration was associated with increased odds of in-hospital mortality (OR 1.50, 95%CI 1.05-2.13). Regarding risk factors for delay, every one-hour increase in allowable compliance time was associated with a 18% decrease in odds of delay (OR 0.82 95%CI 0.75-0.88). Other risk factors for delay included ED boarding more than 4 h (OR 1.47, 95%CI 1.27-1.71) or a high acuity presentation as defined by emergency severity index (ESI) (OR 1.54, 95%CI 1.30-1.81 for ESI 1-2 versus 3-5).

CONCLUSIONS

Delays in second antibiotic dose administration were frequent in the ED and early hospital course, and were associated with increased odds of in-hospital mortality. Several risk factors associated with delays in second dose administration, including ED boarding, were identified.

Two-step predictive model for early detection of emergency department patients with prolonged stay and its management implications

OBJECTIVE

To develop a novel model for predicting Emergency Department (ED) prolonged length of stay (LOS) patients upon triage completion, and further investigate the benefit of a targeted intervention for patients with prolonged ED LOS.

MATERIALS AND METHODS

A two-step model to predict patients with prolonged ED LOS (>16 h) was constructed. This model was initially used to predict ED resource usage and was subsequently adapted to predict patient ED LOS based on the number of ED resources using binary logistic regressions and was validated internally with accuracy. Finally, a discrete event simulation was used to move patients with predicted prolonged ED LOS directly to a virtual Clinical Decision Unit (CDU). The changes of ED crowding status (Overcrowding, Crowding, and Not-Crowding) and savings of ED bed-hour equivalents were estimated as the measures of the efficacy of this intervention.

RESULTS

We screened a total of 123,975 patient visits with final enrollment of 110,471 patient visits. The overall accuracy of the final model predicting prolonged patient LOS was 67.8%. The C-index of this model ranges from 0.72 to 0.82. By implementing the proposed intervention, the simulation showed a 12% (1044/8760) reduction of ED overcrowded status - an equivalent savings of 129.3 ED bed-hours per day.

CONCLUSIONS

Early prediction of prolonged ED LOS patients and subsequent (simulated) early CDU transfer could lead to more efficiently utilization of ED resources and improved efficacy of ED operations. This study provides evidence to support the implementation of this novel intervention into real healthcare practice.

Impact of COVID-19 Pandemic on the Overall Diagnostic and Therapeutic Process for Patients of Emergency Department and Those with Acute Cerebrovascular Disease

(1) Background: During a pandemic, patients and processes in the emergency department (ED) change. These circumstances affect the length of stay (LOS) or degree of crowding in the ED. The processes for patients with acute critical illness, such as cerebrovascular disease (CVD), can be also delayed. Using the process mining (PM) method, this study aimed to evaluate LOS, ED processes for CVD, and delayed processes during the coronavirus disease 2019 (COVID-19) pandemic. (2) Methods: Data were collected from the Clinical Data Warehouse of a medical center. Phase 1 included patients who visited the ED before the COVID-19 outbreak. In Phase 2, post-COVID-19 ED patients were divided into the COVID-19 tested group (CTG) and COVID-19 not tested group (CNTG) according to whether polymerase chain reaction test was performed. We analyzed patients' ED processes before and after COVID-19 using the PM method. We analyzed patients with acute CVD separately to determine whether the process and LOS of patients with acute critical illness were changed or delayed. (3) Results: After the COVID-19 outbreak, the overall LOS was delayed and all processes in CTG patients were delayed. Registration to triage and triage were delayed in both CTG and CNTG patients. The brain imaging process for CTG patients with acute CVD was also delayed. (4) Conclusion: After a pandemic, some processes were changed, new processes were developed, and processes for patients with acute CVD who needed proper time management were not exempted.

Managing and Measuring Emergency Department Care: Results of the Fourth Emergency Department Benchmarking Definitions Summit

BACKGROUND

A shared language and vocabulary are essential for managing emergency department (ED) operations. This Fourth Emergency Department Benchmarking Alliance (EDBA) Summit brought together experts in the field to review, update, and add to key definitions and metrics of ED operations.

OBJECTIVE

Summit objectives were to review and revise existing definitions, define and characterize new practices related to ED operations, and introduce financial and regulatory definitions affecting ED reimbursement.

METHODS

Forty-six ED operations, data management, and benchmarking experts were invited to participate in the EDBA summit. Before arrival, experts were provided with documents from the three prior summits and assigned to update the terminology. Materials and publications related to standards of ED operations were considered and discussed. Each group submitted a revised set of definitions prior to the summit. Significantly revised, topical, or controversial recommendations were discussed among all summit participants. The goal of the in-person discussion was to reach consensus on definitions. Work group leaders made changes to reflect the discussion, which was revised with public and stakeholder feedback.

RESULTS

The entire EDBA dictionary was updated and expanded. This article focuses on an update and discussion of definitions related to specific topics that changed since the last summit, specifically ED intake, boarding, diversion, and observation care. In addition, an extensive new glossary of financial and regulatory terminology germane to the practice of emergency medicine is included.

CONCLUSIONS

A complete and precise set of operational definitions, time intervals, and utilization measures is necessary for timely and effective ED care. A common language of financial and regulatory definitions that affect ED operations is included for the first time. This article and its companion dictionary should serve as a resource to ED leadership, researchers, informatics and health policy leaders, and regulatory bodies.

Factors Affecting Emergency Department Crowding

Emergency department crowding is a multifactorial issue with causes intrinsic to the emergency department and to the health care system. Understanding that the causes of emergency department crowding span this continuum allows for a more accurate analysis of its effects and a more global consideration of potential solutions. Within the emergency department, boarding of inpatients is the most appreciable effect of hospital-wide crowding, and leads to further emergency department crowding. We explore the concept of emergency department crowding, and its causes, effects, and potential strategies to overcome this problem.

Analyzing Main and Interaction Effects of Length of Stay Determinants in Emergency Departments

BACKGROUND

Measuring and understanding main determinants of length of stay (LOS) in emergency departments (EDs) is critical from an operations perspective, since LOS is one of the main performance indicators of ED operations. Therefore, this study analyzes both the main and interaction effects of four widely-used independent determinants of ED-LOS.

METHODS

The analysis was conducted using secondary data from an ED of a large urban hospital in Izmir, Turkey. Between-subject factorial analysis of variance (ANOVA) was used to test the main and interaction effects of the corresponding factors. P values <.05 were considered statistically significant.

RESULTS

While the main effect of gender was insignificant, age, mode of arrival, and clinical acuity had significant effects, whereby ED-LOS was significantly higher for the elderly, those arriving by ambulance, and clinically-categorized high-acuity patients. Additionally, there was an interaction between the age and clinical acuity in that, while ED-LOS increased with age for high acuity patients, the opposite trend occurred for low acuity patients. When ED-LOS was modeled using gender, age, and mode of arrival, there was a significant interaction between age and mode of arrival. However, this interaction was not significant when the model included age, mode of arrival, and clinical acuity.

CONCLUSION

Significant interactions exist between commonly used ED-LOS determinants. Therefore, interaction effects should be considered in analyzing and modelling ED-LOS.

Liu S, A. Camargo C, Aburawi E, Moeckel M, Slagman A, Christ M, Singer A, Tazarourte K, Rathlev NK, A. Grossman S, Bellou A. Association between boarding in the emergency department and in-hospital mortality: A systematic review

IMPORTANCE

Boarding in the emergency department (ED) is a critical indicator of quality of care for hospitals. It is defined as the time between the admission decision and departure from the ED. As a result of boarding, patients stay in the ED until inpatient beds are available; moreover, boarding is associated with various adverse events.

STUDY OBJECTIVE

The objective of our systematic review was to determine whether ED boarding (EDB) time is associated with in-hospital mortality (IHM).

METHODS

A systematic search was conducted in academic databases to identify relevant studies. Medline, PubMed, Scopus, Embase, Cochrane, Web of Science, Cochrane, CINAHL and PsychInfo were searched. We included all peer-reviewed published studies from all previous years until November 2018. Studies performed in the ED and focused on the association between EDB and IHM as the primary objective were included. Extracted data included study characteristics, prognostic factors, outcomes, and IHM. A search update in PubMed was performed in May 2019 to ensure the inclusion of recent studies before publishing.

RESULTS

From the initial 4,321 references found through the systematic search, the manual screening of reference lists and the updated search in PubMed, a total of 12 studies were identified as eligible for a descriptive analysis. Overall, six studies found an association between EDB and IHM, while five studies showed no association. The last remaining study included both ICU and non-ICU subgroups and showed conflicting results, with a positive association for non-ICU patients but no association for ICU patients. Overall, a tendency toward an association between EDB and IHM using the pool random effect was observed.

CONCLUSION

Our systematic review did not find a strong evidence for the association between ED boarding and IHM but there is a tendency toward this association. Further well-controlled, international multicenter studies are needed to demonstrate whether this association exists and whether there is a specific EDB time cut-off that results in increased IHM.

The effect of emergency department delays on 30-day mortality in Central Norway

OBJECTIVE

To assess whether prolonged length of stay in the emergency department was associated with risk of death.

METHODS

We analysed data from 165,183 arrivals at St. Olav's University Hospital's emergency department from 2011 to 2018, using an instrumental variable method. As instruments for prolonged length of emergency department stay, we used indicators measured before arrival of the patient. These indicators were used to study the association between prolonged length of emergency department stay and risk of death, being discharged from the emergency department and length of hospitalisation for those who were hospitalised.

RESULTS

Mean length of stay in the emergency department was 2.9 hours, and 30-day risk of death was 3.4%. Per hour prolonged length of stay in the emergency department, the overall change in risk of death was close to zero, with a narrow 95% confidence interval of -0.5 to 0.7 percentage points. Prolonged emergency department stay was associated with a higher probability of being discharged from the emergency department without admission to the hospital. We found no substantial differences in length of hospitalisation for patients who were admitted.

CONCLUSION

In this study, prolonged emergency department stay was not associated with increased risk of death.

Challenges, consequences, and lessons for way-outs to emergencies at hospitals: a systematic review study

Background

Emergency Department (ED) overcrowding adversely affects patients’ health, accessibility, and quality of healthcare systems for communities. Several studies have addressed this issue. This study aimed to conduct a systematic review study concerning challenges, lessons and way outs of clinical emergencies at hospitals.

Methods

Original research articles on crowding of emergencies at hospitals published from 1st January 2007, and 1st August 2018 were utilized. Relevant studies from the PubMed and EMBASE databases were assessed using suitable keywords. Two reviewers independently screened the titles, abstracts and the methodological validity of the records using data extraction format before their inclusion in the final review. Discussions with the senior faculty member were used to resolve any disagreements among the reviewers during the assessment phase.

Results

Out of the total 117 articles in the final record, we excluded 11 of them because of poor quality. Thus, this systematic review synthesized the reports of 106 original articles. Overall 14, 55 and 29 of the reviewed refer to causes, effects, and solutions of ED crowding, respectively. The review also included four articles on both causes and effects and another four on causes and solutions. Multiple individual patients and healthcare system related challenges, experiences and responses to crowding and its consequences are comprehensively synthesized.

Conclusion

ED overcrowding is a multi-facet issue which affects by patient-related factors and emergency service delivery. Crowding of the EDs adversely affected individual patients, healthcare delivery systems and communities. The identified issues concern organizational managers, leadership, and operational level actions to reduce crowding and improve emergency healthcare outcomes efficiently.

Outcomes of Crowding in Emergency Departments; a Systematic Review

INTRODUCTION

Emergency Department (ED) crowding is a global public health phenomenon affecting access and quality of care. In this study, we seek to conduct a systematic review concerning the challenges and outcomes of ED crowding.

METHODS

This systematic review utilized original research articles published from 1st January 2007, to 1st January 2019. Relevant articles from the PubMed (MEDLINE), EMBASE, and Google scholar databases were extracted using predesigned keywords. Following the PRISMA guidelines, two reviewers independently evaluated the quality of the studies using Critical Appraisal Skills Programme for cohort studies and qualitative studies, and Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument for studies.

RESULTS

Out of the total of 73 articles in the final record, we excluded 15 of them because of poor quality. This systematic review synthesized the reports of 58 original articles. The outcomes of multiple individual patients and healthcare-related challenges are comprehensively assessed.

CONCLUSIONS

ED crowding affects individual patients, healthcare systems and communities at large. The negative influences of crowding on healthcare service delivery result in delayed service delivery, poor quality care, and inefficiency; all negatively affecting the emergency patients' healthcare outcomes, in turn.

Emergency Medicine Resident Efficiency and Emergency Department Crowding

OBJECTIVES

Provider efficiency has been reported in the literature but there is a lack of efficiency analysis among emergency medicine (EM) residents. We aim to compare efficiency of EM residents of different training levels and determine if EM resident efficiency is affected by emergency department (ED) crowding.

METHODS

We conducted a single-center retrospective observation study from July 1, 2014, to June 30, 2017. The number of new patients per resident per hour and provider-to-disposition (PTD) time of each patient were used as resident efficiency markers. A crowding score was assigned to each patient upon the patient's arrival to the ED. We compared efficiency among EM residents of different training levels under different ED crowding statuses. Dynamic efficiency changes were compared monthly through the entire academic year (July to next June).

RESULTS

The study enrolled a total of 150,920 patients. A mean of 1.9 patients/hour was seen by PGY-1 EM residents in comparison to 2.6 patients/hour by PGY-2 and -3 EM residents. Median PTD was 2.8 hours in PGY-1 EM residents versus 2.6 hours in PGY-2 and -3 EM residents. There were no significant differences in acuity across all patients seen by EM residents. When crowded conditions existed, residency efficiency increased, but such changes were minimized when the ED became overcrowded. A linear increase of resident efficiency was observed only in PGY-1 EM residents throughout the entire academic year.

CONCLUSION

Resident efficiency improved significantly only during their first year of EM training. This efficiency can be affected by ED crowding.

Evaluating the impact of emergency department crowding on disposition patterns and outcomes of discharged patients

BACKGROUND

Crowding is a major challenge faced by EDs and is associated with poor outcomes.

OBJECTIVES

Determine the effect of high ED occupancy on disposition decisions, return ED visits, and hospitalizations.

METHODS

We conducted a retrospective analysis of electronic health records of patients evaluated at an adult, urban, and academic ED over 20 months between the years 2012 and 2014. Using a logistic regression model predicting admission, we obtained estimates of the effect of high occupancy on admission disposition, adjusted for key covariates. We then stratified the analysis based on the presence or absence of high boarder patient counts.

RESULTS

Disposition decisions during a high occupancy hour decreased the odds of admission (OR = 0.93, 95% CI: [0.89, 0.98]). Among those who were not admitted, high occupancy was not associated with increased odds of return in the combined (OR = 0.94, 95% CI: [0.87, 1.02]), with-boarders (OR = 0.96, 95% CI: [0.86, 1.09]), and no-boarders samples (OR = 0.93, 95% CI: [0.83, 1.04]). Among those who were not admitted and who did return within 14 days, disposition during a high occupancy hour on the initial ED visit was not associated with a significant increased odds of hospitalization in the combined (OR = 1.04, 95% CI: [0.87, 1.24]), the with-boarders (OR = 1.12, 95% CI: [0.87, 1.44]), and the no-boarders samples (OR = 0.98, 95% CI: [0.77, 1.24]).

CONCLUSION

ED crowding was associated with reduced likelihood of hospitalization without increased likelihood of 2-week return ED visit or hospitalization. Furthermore, high occupancy disposition hours with high boarder patient counts were associated with decreased likelihood of hospitalization.

Mortality Associated With Emergency Department Boarding Exposure: Are There Differences Between Patients Admitted to ICU and Non-ICU Settings?

BACKGROUND

Emergency Department (ED) boarding threatens patient safety. It is unclear whether boarding differentially affects patients admitted to intensive care units (ICUs) versus non-ICU settings.

RESEARCH DESIGN AND SUBJECTS

We performed a 2-hospital, 18-month, cross-sectional, observational, descriptive study of adult patients admitted from the ED. We used Kaplan-Meier estimation and Cox Proportional Hazards regression to describe differences in boarding time among patients who died during hospitalization versus those who survived, controlling for covariates that could affect mortality risk or boarding exposure, and separately evaluating patients admitted to ICUs versus non-ICU settings.

MEASURES

We extracted age, race, sex, time variables, admission unit, hospital disposition, and Elixhauser comorbidity measures and calculated boarding time for each admitted patient.

RESULTS

Among 39,781 admissions from the EDs (21.3% to ICUs), non-ICU patients who died in-hospital had a 1.2-fold risk (95% confidence interval, 1.03-1.36; P=0.016) of having experienced longer boarding times than survivors, accounting for covariates. We did not observe a difference among patients admitted to ICUs.

CONCLUSIONS

Among non-ICU patients, those who died during hospitalization were more likely to have had incrementally longer boarding exposure than those who survived. This difference was not observed for ICU patients. Boarding risk mitigation strategies focused on ICU patients may have accounted for this difference, but we caution against interpreting that boarding can be safe. Segmentation by patients admitted to ICU versus non-ICU settings in boarding research may be valuable in ensuring that the safety of both groups is considered in hospital flow and boarding care improvements.

Use of Systems Engineering to Design a Hospital Command Center

BACKGROUND

In hospitals and health systems across the country, patient flow bottlenecks delay care delivery-emergency department boarding and operating room exit holds are familiar examples. In other industries, such as oil, gas, and air traffic control, command centers proactively manage flow through complex systems.

METHODS

A systems engineering approach was used to analyze and maximize existing capacity in one health system, which led to the creation of the Judy Reitz Capacity Command Center. This article describes the key elements of this novel health system command center, which include strategic colocation of teams, automated visual displays of real-time data providing a global view, predictive analytics, standard work and rules-based protocols, and a clear chain of command and guiding tenets. Preliminary data are also shared.

RESULTS

With proactive capacity management, subcycle times decreased and allowed the health system's flagship hospital to increase occupancy from 85% to 92% while decreasing patient delays.

CONCLUSION

The command center was built with three primary goals-reducing emergency department boarding, eliminating operating room holds, and facilitating transfers in from outside facilities-but the command center infrastructure has the potential to improve hospital operations in many other areas.

The impact of Australian healthcare reforms on emergency department time-based process outcomes: An interrupted time series study

Background

In 2011, the Australian government introduced national healthcare reforms aimed at increasing the timeliness and quality of hospital care. The healthcare reforms included, but were not limited to, emergency department (ED) time-based targets, financial incentives, and public performance reporting of hospital data. We sought to evaluate the impact of the national healthcare reforms on ED time-based process outcomes.

Methods

A quasi-experimental study of ED presentations from 2006 to 2016 in the state of Victoria, Australia. Uncontrolled, interrupted time-series analyses were used to evaluate, by hospital peer groups, the effect of national healthcare reforms on: patient wait times for treatment; treatment within recommended time; and patient departure within four hours of arrival in ED.

Results

There were small improvements in ED time-based process outcomes following the introduction of the national healthcare reforms. These occurred in most hospital peer groups immediately and over the longer term, across the various triage categories. The largest improvements occurred in small hospitals and smallest improvements in medium sized hospitals. ED time-based targets, now abolished by the Australian government, were not achieved in any hospital peer groups.

Conclusions

Our findings suggest that national healthcare reforms had the potential to prompt fundamental changes in ED processes leading to significant improvements in ED performances across most hospital peer groups but were generally unable to reach the ED targets imposed nationally. ED performances also varied by hospital peer groups. Attention to ED time-based process outcomes within hospital peer groups may provide insights into hospital practices that could improve the quality and efficiency of ED care.

An exhaustive review and analysis on applications of statistical forecasting in hospital emergency departments

Emergency departments (EDs) provide medical treatment for a broad spectrum of illnesses and injuries to patients who arrive at all hours of the day. The quality and efficient delivery of health care in EDs are associated with a number of factors, such as patient overall length of stay (LOS) and admission, prompt ambulance diversion, quick and accurate triage, nurse and physician assessment, diagnostic and laboratory services, consultations and treatment. One of the most important ways to plan the healthcare delivery efficiently is to make forecasts of ED processes. The aim this study is thus to provide an exhaustive review for ED stakeholders interested in applying forecasting methods to their ED processes. A categorisation, analysis and interpretation of 102 papers is performed for review. This exhaustive review provides an insight for researchers and practitioners about forecasting in EDs in terms of showing current state and potential areas for future attempts.

Should I be more concerned about patient care or the four-hour target?

UK emergency departments (EDs) are high-pressure environments focused on delivering care in the most efficient way to patients with a range of health problems. For many people EDs are the front door of the NHS and are a focus of significant media and political interest. People who attend EDs are often anxious and a main element of their concern is waiting time for treatment. In UK EDs the four-hour target is a main NHS target and a cornerstone of evaluating ED performance. There is ongoing debate about whether spending additional time in EDs affects patient care and outcomes, with some research showing increased mortality associated with longer stays and some showing no effect on mortality. Evidence suggests that patients are spending longer in UK EDs and it is possible that those who remain longer than four hours could have worse outcomes. This article identifies the effects of prolonged ED length of stay through a systematic literature review of data published since implementation of the four-hour target to measure the relationship between breaching the target and morbidity and mortality.

Investigating the referral of patients with non-urgent conditions to a regional Australian emergency department: a study protocol

Background

Australia’s only island state, Tasmania, experiences one of the nation’s highest incidences of non-urgent emergency department (ED) presentations in a healthcare system regularly faced with service demands that exceed resource availability. Service-demand mismatches are acknowledged to contribute to ED crowding which in turn, has been documented to have a correlation with poorer patient outcomes. Crowding within EDs is complex, non-urgent presentations alone are not the primary cause, but have been reported to be a contributing factor. In 2015–16 Tasmania recorded over 153,000 ED attendances, 55% of these fell into the two least urgent triage categories. Recent research in the State’s North established that 29% of non-urgent presentations were referred, formally or informally, from primary healthcare providers and that, for many patients (39%), the ED was not their first choice of service provider. This study aims to identify the service needs of patients referred to a regional Australian ED and subsequently triaged as non-urgent.

Method

In order to achieve this aim, three objectives have been identified. The first two objectives use an explanatory sequential mixed-method approach while the third objective will incorporate an implementation science approach. These three objectives are: first, a retrospective analysis of seven years of routinely collected hospital data to identify trends in referral of patients with non-urgent conditions; second, focus group interviews with patients and primary care providers to further understand perceived need and service requirements of those referred to the ED, and third, translation of findings into local health service recommendations.

Discussion

Identification of the needs of patients referred to the ED with non-urgent conditions will inform future service planning aiming to facilitate access to the right service at the right time and in the right place.

Factors associated with prolonged length of stay in the psychiatric emergency service

OBJECTIVE

Dedicated regional psychiatric emergency services (PES) were proposed as a better care model for psychiatric emergencies and a possible solution to boarding of psychiatric patients in the emergency department. However, there are limited data on factors associated with prolonged length of stay (LOS) in the PES. The objective of this study was finding factors associated with prolonged LOS in the PES and moving towards a solution to this problem.

METHODS

The study sample comprised 200 PES visits randomly chosen from January 2011 to December 2015 in a psychiatric hospital in Taiwan. Relevant data were collected comprehensively through the health information system and by reviewing medical records. The primary outcome was LOS longer than 24 hours while LOS longer than 48 hours was used as the secondary outcome.

RESULTS

Mean LOS was 17.6±23.2 hours, with 53 (26.5%) visits lasting more than 24 hours and 15 (7.5%) visits lasting more than 48 hours. After adjusting for related confounders, LOS longer than 24 hours was associated with use of restraints in the PES (adjusted odds ratio (aOR) = 3.13, 95% CI = 1.59-6.15) and history of illicit substance use (aOR = 2.46, 95% CI = 1.11-5.44). LOS longer than 48 hours was associated with use of restraints in the PES (aOR = 4.11, 95% CI = 1.2-14.14), history of illicit substance use (aOR = 6.16, 95% CI = 1.37-27.62) and first time visit to the hospital (aOR = 8.54, 95% CI = 2.03-35.96). Neither outcome was associated with transfer to an inpatient unit.

CONCLUSION

Prolonged LOS was common in the study sample. Discharged patients had an equally high rate of prolonged LOS as admitted patients. Therefore measures should be taken to facilitate timely discharge. Use of restraints and history of illicit substance use were common among patients with prolonged LOS.

Code Help: Can This Unique State Regulatory Intervention Improve Emergency Department Crowding?

Introduction

Emergency department (ED) crowding adversely affects multiple facets of high-quality care. The Commonwealth of Massachusetts mandates specific, hospital action plans to reduce ED boarding via a mechanism termed "Code Help." Because implementation appears inconsistent even when hospital conditions should have triggered its activation, we hypothesized that compliance with the Code Help policy would be associated with reduction in ED boarding time and total ED length of stay (LOS) for admitted patients, compared to patients seen when the Code Help policy was not followed.

Methods

This was a retrospective analysis of data collected from electronic, patient-care, timestamp events and from a prospective Code Help registry for consecutive adult patients admitted from the ED at a single academic center during a 15-month period. For each patient, we determined whether the concurrent hospital status complied with the Code Help policy or violated it at the time of admission decision. We then compared ED boarding time and overall ED LOS for patients cared for during periods of Code Help policy compliance and during periods of Code Help policy violation, both with reference to patients cared for during normal operations.

Results

Of 89,587 adult patients who presented to the ED during the study period, 24,017 (26.8%) were admitted to an acute care or critical care bed. Boarding time ranged from zero to 67 hours 30 minutes (median 4 hours 31 minutes). Total ED LOS for admitted patients ranged from 11 minutes to 85 hours 25 minutes (median nine hours). Patients admitted during periods of Code Help policy violation experienced significantly longer boarding times (median 20 minutes longer) and total ED LOS (median 46 minutes longer), compared to patients admitted under normal operations. However, patients admitted during Code Help policy compliance did not experience a significant increase in either metric, compared to normal operations.

Conclusion

In this single-center experience, implementation of the Massachusetts Code Help regulation was associated with reduced ED boarding time and ED LOS when the policy was consistently followed, but there were adverse effects on both metrics during violations of the policy.

Emergency department length of stay for ethanol intoxication encounters

BACKGROUND

Emergency Department (ED) encounters for ethanol intoxication are becoming increasingly common. The purpose of this study was to explore factors associated with ED length of stay (LOS) for ethanol intoxication encounters.

METHODS

This was a multi-center, retrospective, observational study of patients presenting to the ED for ethanol intoxication. Data were abstracted from the electronic medical record. To explore factors associated with ED LOS, we created a mixed-effects generalized linear model.

RESULTS

We identified 18,664 eligible patients from 6 different EDs during the study period (2012-2016). The median age was 37years, 69% were male, and the median ethanol concentration was 213mg/dL. Median LOS was 348min (range 43-1658). Using a mixed-effects generalized linear model, independent variables associated with a significant increase in ED LOS included use of parenteral sedation (beta=0.30, increase in LOS=34%), laboratory testing (beta=0.21, increase in LOS=23%), as well as the hour of arrival to the ED, such that patients arriving to the ED during evening hours (between 18:00 and midnight) had up to an 86% increase in LOS. Variables not significantly associated with an increase in LOS included age, gender, ethanol concentration, psychiatric disposition, using the ED frequently for ethanol intoxication, CT use, and daily ED volume.

CONCLUSION

Variables such as diagnostic testing, treatments, and hour of arrival may influence ED LOS in patients with acute ethanol intoxication. Identification and further exploration of these factors may assist in developing hospital and community based improvements to modify LOS in this population.

Effect of crowding on length of stay for common chief complaints in the emergency department: A STROBE cohort study

Crowding in emergency departments (EDs) is associated with long lengths of stay (LOS); however, it is not known whether the effect is equal across different chief complaints.The aim of the study was to compare the effect of crowding on LOS in the 10 most common medical or surgical chief complaints in the ED.All adult visits to a university hospital ED on weekdays between 8 AM and 9 PM in 2012 (n = 19,200) were stratified based on chief complaint and triage priority. The ED bed occupancy rate was measured and crowding was defined as an occupancy rate over one. The impact of crowding on LOS was calculated for the different groups.During crowding, LOS was longer among all chief complaints (P ≤.01) (except for high-acuity patients with wounds, where the study group was very small). During crowding, LOS increased the most among patients with extremity pain/swelling (145% among high-acuity patients, 125% among low-acuity patients) and flank pain (87% among high-acuity patients, 117% among low-acuity patients) and the least among patients with chest pain (32% among high-acuity patients, 45% among low-acuity patients) or arrhythmia (37% among high-acuity patients, 52% among low-acuity patients).The effect of ED crowding on LOS is unequal across different chief complaints. These findings could be used to improve the processing of specific chief complaints in the ED.

Deconstructing the 4-h rule for access to emergency care and putting patients first

Evidence suggests improved outcomes for patients requiring emergency admission to hospital are associated with improved emergency department (ED) efficiency and lower transit times. Factors preventing timely transfers of emergency patients to in-patient beds across the ED-in-patient interface are major causes for ED crowding, for which several remedial strategies are possible, including parallel processing of probable admissions, direct-to-ward admissions and single-point medical registrars for receiving and processing all referrals directed at specific speciality units. Dynamic measures of ED overcrowding that focus on boarding time are more indicative of EDs with exit block involving the ED-in-patient interface than static proxy measures such as hospital bed occupancy and numbers of ED presentations. The ideal 4-h compliance rate for all ED presentations is around 80%, based on a large retrospective study of more than 18million presentations to EDs of 59 Australian hospitals over 4 years, which demonstrated a highly significant linear reduction in risk-adjusted in-patient mortality for admitted patients as the compliance rate for all patients rose to 83%, but was not confirmed beyond this rate. Closely monitoring patient outcomes for emergency admissions in addition to compliance with time-based access targets is strongly recommended in ensuring reforms aimed at decongesting EDs do not compromise the quality and safety of patient care.

Determinants of Pediatric Psychiatry Length of Stay in 2 Urban Emergency Departments

OBJECTIVES

Pediatric mental illness poses a significant burden with an overall prevalence of approximately 10%. Increasingly, children with mental disorders seek care in the emergency department (ED). However, the ED is not an ideal setting. Pediatric mental health patients receive limited treatment and experience significantly longer length of stay (LOS) than other patients seen in the ED. This study examines patient and hospital factors associated with LOS and prolonged LOS (PLOS).

METHODS

This is a retrospective chart review of patients between the ages of 3 and 17 presenting at 2 participating urban EDs with a psychiatric diagnosis from May 2010 to May 2012.

RESULTS

This study includes 939 patients with an average age of 14.1 years and a median LOS of 295 minutes. The diagnosis was the strongest predictor of LOS and PLOS. Patients with a psychotic disorder or suicide attempt or ideation experienced a longer LOS, 35% and 55% increases, respectively, and an increased odds of PLOS (odds ratio, 3.07 and 8.36, respectively). Patient sex, previous history of self-harm, and the daily census were associated with both a longer LOS and PLOS. Ethnicity, site of admission, and year of admission were only associated with LOS.

CONCLUSIONS

Diagnosis-specific management factors are the primary determinant of LOS. However, some patient characteristics and hospital operational factors are also associated with LOS. Organizational reforms and an evaluation of the required human and material resources are necessary to improve access to and availability of pediatric mental health care.

The Association Between Hospital Capacity Strain and Inpatient Outcomes in Highly Developed Countries: A Systematic Review

BACKGROUND

Increases in patient needs can strain hospital resources, which may worsen care quality and outcomes. This systematic literature review sought to understand whether hospital capacity strain is associated with worse health outcomes for hospitalized patients and to evaluate benefits and harms of health system interventions to improve care quality during times of hospital capacity strain.

METHODS

Parallel searches were conducted in MEDLINE, CINAHL, the Cochrane Library, and reference lists from 1999-2015. Two reviewers assessed study eligibility. We included English-language studies describing the association between capacity strain (high census, acuity, turnover, or an indirect measure of strain such as delayed admission) and health outcomes or intermediate outcomes for children and adults hospitalized in highly developed countries. We also included studies of health system interventions to improve care during times of capacity strain. Two reviewers extracted data and assessed risk of bias using the Newcastle-Ottawa Score for observational studies and the Cochrane Collaboration Risk of Bias Assessment Tool for experimental studies.

RESULTS

Of 5,702 potentially relevant studies, we included 44 observational and 8 experimental studies. There was marked heterogeneity in the metrics used to define capacity strain, hospital settings, and overall study quality. Mortality increased during times of capacity strain in 18 of 30 studies and in 9 of 12 studies in intensive care unit settings. No experimental studies were randomized, and none demonstrated an improvement in health outcomes after implementing the intervention. The pediatric literature is very limited; only six observational studies included children. There was insufficient study homogeneity to perform meta-analyses.

DISCUSSION

In highly developed countries, hospital capacity strain is associated with increased mortality and worsened health outcomes. Evidence-based solutions to improve outcomes during times of capacity strain are needed.

Associations of Emergency Department Length of Stay With Publicly Reported Quality-of-care Measures

OBJECTIVE

The Institute of Medicine identified emergency department (ED) crowding as a critical threat to patient safety. We assess the association between changes in publicly reported ED length of stay (LOS) and changes in quality-of-care measures in a national cohort of hospitals.

METHODS

Longitudinal analysis of 2012 and 2013 data from the American Hospital Association (AHA) Survey, Center for Medicare and Medicaid Services (CMS) Cost Reports, and CMS Hospital Compare. We included hospitals reporting Hospital Compare timeliness measure of LOS for admitted patients. We used AHA and CMS data to incorporate hospital predictors of interest. We used the method of first differences to test for relationships in the change over time between timeliness measures and six hospital-level measures.

RESULTS

The cohort consisted of 2,619 hospitals. Each additional hour of ED LOS was associated with a 0.7% decrease in proportion of patients giving a top satisfaction rating, a 0.7% decrease in proportion of patients who would "definitely recommend" the hospital, and a 6-minute increase in time to pain management for long bone fracture (p < 0.01 for all). A 1-hour increase in ED LOS is associated with a 44% increase in the odds of having an increase in left without being seen (95% confidence interval = 25% to 68%). ED LOS was not associated with hospital readmissions (p = 0.14) or time to percutaneous coronary intervention (p = 0.14).

CONCLUSION

In this longitudinal study of hospitals across the United States, improvements in ED timeliness measures are associated with improvements in the patient experience.

Predictors for Delayed Emergency Department Care in Medical Patients with Acute Infections - An International Prospective Observational Study

Introduction

In overcrowded emergency department (ED) care, short time to start effective antibiotic treatment has been evidenced to improve infection-related clinical outcomes. Our objective was to study factors associated with delays in initial ED care within an international prospective medical ED patient population presenting with acute infections.

Methods

We report data from an international prospective observational cohort study including patients with a main diagnosis of infection from three tertiary care hospitals in Switzerland, France and the United States (US). We studied predictors for delays in starting antibiotic treatment by using multivariate regression analyses.

Results

Overall, 544 medical ED patients with a main diagnosis of acute infection and antibiotic treatment were included, mainly pneumonia (n = 218; 40.1%), urinary tract (n = 141; 25.9%), and gastrointestinal infections (n = 58; 10.7%). The overall median time to start antibiotic therapy was 214 minutes (95% CI: 199, 228), with a median length of ED stay (ED LOS) of 322 minutes (95% CI: 308, 335). We found large variations of time to start antibiotic treatment depending on hospital centre and type of infection. The diagnosis of a gastrointestinal infection was the most significant predictor for delay in antibiotic treatment (+119 minutes compared to patients with pneumonia; 95% CI: 58, 181; p<0.001).

Conclusions

We found high variations in hospital ED performance in regard to start antibiotic treatment. The implementation of measures to reduce treatment times has the potential to improve patient care.