Emergency department conditions associated with the number of patients who leave a pediatric emergency department before physician assessment

Maximizing efficiency in emergency care: triple interventions to minimize left without being seen: An observational study

Left without being seen (LWBS) is a quality care metric associated with patient-centered outcomes. The risks affecting LWBS are complex and interventions targeting certain risks have diverse effects. We aimed to use different artificial intelligence and machine learning (AI/ML) algorithms to identify the risks affecting LWBS, implement triple interventions specifically targeted at such risks, and compare daily LWBS rate changes before and after the intervention. This is a retrospective observational study. Single urban Emergency Department (ED) daily throughput data from March 1, 2019, to February 28, 2023, were used for AI/ML model prediction. Model performance including accuracy, recall, precision, F1 score, and area under the receiver operating characteristics (AUC) were reported. The top risks affecting the LWBS were identified using the important function of the AI/ML feature. Triple interventions were implemented. The average daily LWBS rate was compared before (March 1, 2019, to February 28, 2023) and after (June 1, 2023, to May 31, 2024). A total of 1919 daily throughput metrics were analyzed, including 1461 daily metrics before the intervention, 92 daily metrics during the wash period, and 366 daily metrics after the intervention. Using data before the intervention, the Extreme Gradient Boosting (XGBoost) and Random Forest AI/ML algorithms predicted LWBS with a similar favorable performance. The 3 common factors influencing the increased daily LWBS rate were triage-to-bed (wait time), boarding time, and door-to-triage in the ED. Rapid triage, direct bedding, and boarding reduction (triple intervention) were implemented on March 1, 2023. We found 4.82% of daily LWBS before the triple intervention compared to 1.93% of daily LWBS after the triple intervention (P < .001). AI/ML approaches can identify common factors that are highly related to LWBS with favorable performance. Triple interventions targeting these factors can reduce the daily LWBS rate by approximately 60%, indicating the efficiency of the ED operational management.

Racial and Ethnic Disparities in Emergency Department Wait Times for Headache

Headache is a common complaint of individuals seeking treatment in the emergency department (ED). Because pain is subjective, medical evaluation is susceptible to implicit bias that can lead to disparities in wait times. The aim of this study was to determine whether there are racial and ethnic disparities in ED wait times for headache. Our study used the 2015-2018 National Hospital Ambulatory Care Surveys (NHAMCS), a nationally representative sample of ambulatory care visits to EDs. Our sample consisted of visits made by adults for headaches, which were identified using ICD-10 diagnosis codes and NHAMCS reason for visit codes. There were 12,301,655 ED visits for headache represented by our sample. The mean wait time for headache visits was 38.1 min (95%CI: 31.1, 45.0). The mean wait time for Non-Hispanic White patients, non-Hispanic Black patients, Hispanic patients, and the other race and ethnicity groups were 34.7 min (95%CI: 27.5, 42.0), 46.4 min (95%CI: 26.5, 66.4), 37.9 min (95%CI: 19.4, 56.3), and 21.0 min (95%CI: 6.3, 35.7) respectively. After controlling for patient- and hospital-level covariates, visits by non-Hispanic Black patients had 40% (95%CI: -0.01, 0.81, p = 0.056) longer wait times and visits by Hispanic patients had 39% (95%CI: -0.03, 0.80, p = 0.068) longer wait times than visits by non-Hispanic White patients. While our findings suggest that there may be longer wait times for visits by non-Hispanic Black and Hispanic patients compared to visits by non-Hispanic White patients, further research is needed to confirm these findings and determine causes of wait times disparities in the ED.

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.

Leaving Without Being Seen From the Pediatric Emergency Department: A New Baseline

BACKGROUND

Left without being seen (LWBS) rates are an important quality metric for pediatric emergency departments (EDs), with high-acuity LWBS children representing a patient safety risk. Since July 2021, our ED experienced a surge in LWBS after the most stringent COVID-19 quarantine restrictions ended.

OBJECTIVE

We assessed changes in LWBS rates and examined associations of system factors and patient characteristics with LWBS.

METHODS

We performed a retrospective study in a large, urban pediatric ED for all arriving patients, comparing the following three time-periods: before COVID-19 (PRE, January 2018-February 2020), during early COVID-19 (COVID, March 2020-June 2021), and after the emergence of COVID-19 variants and re-emergence of seasonal viruses (POST, July 2021-December 2021). We compared descriptive statistics of daily LWBS rates, patient demographic characteristics, and system characteristics. Negative binomial (system factors) and logistic regression (patient characteristics) models were developed to evaluate the associations between system factors and LWBS, and patient characteristics and LWBS, respectively.

RESULTS

Mean daily LWBS rates changed from 1.8% PRE to 1.4% COVID to 10.7% during POST. Rates increased across every patient demographic and triage level during POST, despite a decrease in daily ED volume compared with PRE. LWBS rates were significantly associated with patients with an Emergency Severity Index score of 2, mean ED census, and staff productivity within multiple periods. Patient characteristics associated with LWBS included lower assigned triage levels and arrival between 8 pm and 4 am.

CONCLUSIONS

LWBS rates have shown a large and sustained increase since July 2021, even for high-acuity patients. We identified system factors that may provide opportunities to reduce LWBS. Further work should develop strategies to prevent LWBS in at-risk patients.

Machine learning to identify attributes that predict patients who leave without being seen in a pediatric emergency department

PURPOSE

To characterize patients who left without being seen (LWBS) from a Canadian pediatric Emergency Department (ED) and create predictive models using machine learning to identify key attributes associated with LWBS.

METHODS

We analyzed administrative ED data from April 1, 2017, to March 31, 2020, from IWK Health ED in Halifax, NS. Variables included: visit disposition; Canadian Triage Acuity Scale (CTAS); triage month, week, day, hour, minute, and day of the week; sex; age; postal code; access to primary care provider; visit payor; referral source; arrival by ambulance; main problem (ICD10); length of stay in minutes; driving distance in minutes; and ED patient load. The data were randomly divided into training (80%) and test datasets (20%). Five supervised machine learning binary classification algorithms were implemented to train models to predict LWBS patients. We balanced the dataset using Synthetic Minority Oversampling Technique (SMOTE) and used grid search for hyperparameter tuning of our models. Model evaluation was made using sensitivity and recall on the test dataset.

RESULTS

The dataset included 101,266 ED visits where 2009 (2%) records were excluded and 5800 LWBS (5.7%). The highest-performing machine learning model with 16 patient attributes was XGBoost which was able to identify LWBS patients with 95% recall and 87% sensitivity. The most influential attributes in this model were ED patient load, triage hour, driving minutes from home address to ED, length of stay (minutes since triage), and age.

CONCLUSION

Our analysis showed that machine learning models can be used on administrative data to predict patients who LWBS in a Canadian pediatric ED. From 16 variables, we identified the five most influential model attributes. System-level interventions to improve patient flow have shown promise for reducing LWBS in some centres. Predicting patients likely to LWBS raises the possibility of individual patient-level interventions to mitigate LWBS.

Why do patients leave the Pediatric Emergency Department and what happens to them?

BACKGROUND

The dropout rate is an important indicator of the quality of emergency services. The authors intend to evaluate factors that influence abandonments in the Pediatric Emergency Department (PED) and to assess outcome and destination of the highest triage leveled patients.

METHODS

Retrospective analysis of the abandonment cases occurring between 2014 and 2016 in a tertiary hospital, including sociodemographic characterization, temporal factors, triage level, referral from other health services, waiting time and patient attendance. The outcome of the highest triage level was also accessed.

RESULTS

In the three years analyzed, there were 240171 PED visits, with an abandonment rate of 2.57%. PED abandonment was influenced by higher patient attendance and waiting time, a younger age, and less urgent triage level. Only 1.78% of the urgent or emergent patients (level three or two) abandoned the PED. Of these, 44% sought medical care in the next five days, 41% of which in private institutions, 40% in public hospitals and 19% in primary care. Only 0.81% of those were hospitalized.

CONCLUSIONS

The majority of patients who leave the PED do not correspond to urgent cases. Health education awareness campaigns, clinical counseling platforms (online or phone services) and the improved accessibility of primary health care may optimize the usage of health resources. The reinforcement of the teams in times of greater affluence may contribute to decrease the rate of abandonment.

Pediatric ED departmental complexity: a different approach to the concept of ED crowding

OBJECTIVE

Emergency department (ED) crowding is a significant problem in Canada and internationally and is associated with the potential for patient harm. Although pediatric patients represent a significant proportion of overall ED visits, there is limited research on pediatric ED crowding. The Canadian Association of Emergency Physicians defines department crowding as a mismatch between the required and available resources to provide timely emergency care. We propose that rather than crowding, it is better to think of ED patient populations as being more or less "complex" as defined by proxies of the human and physical resources needed for patient management. The study objectives are to explore the utility of a simple and easily available retrospective metric of ED complexity, and to assess the relationship this measure has on patient outcomes in a pediatric ED.

METHODS

Using administrative data from a tertiary care pediatric ED, we developed a departmental complexity score based on patient registration number, triage acuity, and departmental length of stay as a proxy for the resources necessary to provide ED care. We then explored the relationship between this departmental complexity score and clinical care indices.

RESULTS

The score shows a strong relationship with the number of patients who left without being seen by a physician, as well as time to initial MD assessment, both measures which have been used to represent ED crowding in previous research. We found no association between our departmental complexity score and adverse impacts on patient care outcomes of hospital admission, pediatric ICU admission, or patients returning to the ED within 72 h of leaving.

CONCLUSIONS

The departmental complexity score has promise as a retrospective measure of departmental resource requirement and may have a role in the ongoing assessment of patient flow.

Leaving Without Being Seen From a Pediatric Emergency Department: Identifying Caregivers' Perspectives Using Q-methodology

OBJECTIVE

National rates of left (or leaving) without being seen (LWBS) in pediatric emergency departments (PED) are higher than general emergency departments. We investigated coexisting perspectives on LWBS.

METHODS

Q-methodology was implemented through a mixed-methods design. Semistructured interviews elicited a concourse of caregivers' thoughts on waiting in the PED and their consideration of LWBS. Themes from the concourse were identified and framed as statements. Caregivers sorted these statements, which ranged from choosing to stay versus leave the PED before their child is seen by a physician. Sorted data were analyzed through centroid factor analysis.

RESULTS

Seventy-seven caregivers contributed interview data, from which 31 themes were identified and framed as statements. Thirty-one different caregivers contributed Q-sort data, from which 2 factors were revealed, each representing a unique perspective on LWBS. Most caregivers (26 of 31) shared the following perspective: "I would leave the PED before my child is seen by a doctor if there are no reassessments for my child while we are in the queue, no updates on our queue position, or no explanations for wait time." The remaining caregivers (5 of 31) perceived feelings of uncertainty and helplessness, lack of updates, and competing obligations as primary influences on LWBS.

CONCLUSIONS

Elements that factor into caregivers' decision to LWBS from a PED include lack of reassessments, lack of updates on queue position, and lack of information about the triage process. Quality improvement interventions for decreasing LWBS rates should account for diverse coexisting perspectives such as these.

The Waiting Room Assessment to Virtual Emergency Department pathway: Initiating video-based telemedicine in the pediatric emergency department

The COVID-19 pandemic has presented pediatric emergency departments with unique challenges, resulting in a heightened demand for adapted clinical pathways. In response to this need, the Montreal Children's Hospital pediatric emergency department introduced the WAVE (Waiting Room Assessment to Virtual Emergency Department) pathway, a video-based telemedicine pathway for selected non-critical patients, aiming to reduce safety issues related to emergency department overcrowding, while providing timely care to all children presenting and registering at our emergency department. The objective of the WAVE pilot phase was to evaluate the feasibility and acceptability of telemedicine in our pediatric emergency department, which was previously unfamiliar with this mode of care delivery. During the six-week, three-evening per week deployment, we conducted 18 five-hour telemedicine shifts. In total, 27 patients participated in the WAVE pathway. Results from this pilot phase met four of five a priori feasibility and acceptability criteria. Overall, participating families were satisfied with this novel care pathway and reported no disruptive technological barriers.

Multi-dimensional Measurements of Crowding for Pediatric Emergency Departments: A Systematic Review

The absence of accepted crowding measurement tools that encompass the unique characteristics of pediatric emergency departments (EDs) creates a deficit in advancing efforts to identify and evaluate solutions for this growing problem. In this systematic review, we examined 4 studies that reported on the development and testing of multidimensional pediatric ED crowding measurements. Two investigations involved models (PEDOCS, SOTU-PED) that measured factors indicative or contributory to crowding. A third investigation developed a model mapping the flow of patients through the pediatric ED. The final study modeled the magnitude of physician’s work load, particularly when this load is high when crowding is likely present, based on patient arrivals, presenting complaints and conditions, and tests ordered. These works from 4 studies on measuring crowding in pediatric EDs show promise, but this field is at an early stage. Future work should concentrate on comparing the utility of crowding measurements across multiple pediatric ED settings.

The Impact of On-duty Emergency Medicine Trainees on Left-Without-Being-Seen Rates in an Academic Emergency Department

Objectives: One of the endpoints for assessing the emergency department (ED) performance is the left-without-being-seen (LWBS) proportion. This study aimed to evaluate the impact of increasing proportions of on-duty emergency medicine (EM) trainees on LWBS rates in clinical shifts. Methods: The study was conducted at an urban-academic-ED (annual census: 452,757) over a period of one year. We employed multivariate linear regression (p < 0.05) defining significance to identify and adjust for multiple LWBS influencers related to patient care. Results: After analyzing over 1098 shifts, the median LWBS rate was 8.9% (interquartile range 5.3% to 13.5%). The increasing number of EM trainees in the ED did not adversely impact the LWBS; the opposite was noted. In univariate analysis, the increasing proportion of on-duty EM trainee physicians was significantly (p < 0.001) associated with a decrease in the LWBS rates. The multivariate model adjusted for the statistically significant and confounding LWBS influencers, with an absolute increase of 1% in trainees’ proportion of overall on-duty physician coverage, was associated with an absolute decrease of 2.1% in LWBS rates (95% confidence interval 0.43% to 3.8%, p = 0.014). Conclusions: At the study site, there was a statistically and operationally significant improvement in LWBS associated with partial replacement of board-certified specialist-grade EM physicians with EM residents and fellow trainees.

A Time-and-Motion Study of Clinical Trial Eligibility Screening in a Pediatric Emergency Department

OBJECTIVE

Challenges with efficient patient recruitment including sociotechnical barriers for clinical trials are major barriers to the timely and efficacious conduct of translational studies. We conducted a time-and-motion study to investigate the workflow of clinical trial enrollment in a pediatric emergency department.

METHODS

We observed clinical research coordinators during 3 clinically staffed shifts. One clinical research coordinator was shadowed at a time. Tasks were marked in 30-second intervals and annotated to include patient screening, patient contact, performing procedures, and physician contact. Statistical analysis was conducted on the patient enrollment activities.

RESULTS

We conducted fifteen 120-minute observations from December 12, 2013, to January 3, 2014 and shadowed 8 clinical research coordinators. Patient screening took 31.62% of their time, patient contact took 18.67%, performing procedures took 17.6%, physician contact was 1%, and other activities took 31.0%.

CONCLUSIONS

Screening patients for eligibility constituted the most time. Automated screening methods could help reduce this time. The findings suggest improvement areas in recruitment planning to increase the efficiency of clinical trial enrollment.

Impact of Emergency Department Phlebotomists on Left-Before-Treatment-Completion Rates

Introduction

The emergency department (ED) serves as the primary access point to the healthcare system. ED throughput efficiency is critical. The percentage of patients who leave before treatment completion (LBTC) is an important marker of department efficiency. Our study aimed to assess the impact of an ED phlebotomist, dedicated to obtaining blood specimen collection on waiting patients, on LBTC rates.

Methods

This study was conducted as a retrospective observational analysis over approximately 18 months (October 5, 2015–March 31, 2017) for patients evaluated by a triage provider with a door-to-room (DtR) time of > 20 minutes (min). LBTC rates were compared in 10-min DtR increments for when the ED phlebotomist collected the patient’s specimen vs not.

Results

Of 71,942 patient encounters occurring during the study period, 17,349 (24.1%) met study inclusion criteria. Of these, 1842 (10.6%) had blood specimen collection performed by ED phlebotomy. The overall LBTC rate for encounters included in the analysis was 5.26% (95% confidence interval [CI], 4.94%–5.60%). Weighting the LBTC rates for each 10-min DtR interval using the fixed effects model led to an overall LBTC rate of 2.74% (95% CI, 2.09%–3.59%) for patient encounters with ED phlebotomist collection vs 5.31% (95% CI, 4.97%–5.67%) in those which did not, yielding a relative reduction of 48% (95% CI, 34%–63%). The effect of the phlebotomist on LBTC rates increased as DtR times increased. The difference in the rate of the rise of LBTC percentages, per 10-min interval, was 0.50% (95% CI, 0.19%–0.81%) higher for non-ED phlebotomist encounters vs phlebotomist encounters.

Conclusion

ED phlebotomy demonstrated a significant reduction in ED LBTC rates. Further, as DtR times increased, the impact of ED phlebotomy became increasingly significant. Adult EDs with increased rates of LBTC patient encounters may want to consider the implementation of ED phlebotomy.

Patients who leave Emergency Department without being seen or during treatment in the Lazio Region (Central Italy): Determinants and short term outcomes

Background and Aims

Patients who leave Emergency Department before physician’s visit (LWBS) or during treatment (LDT) represent a useful indicator of the emergency care's quality. The profile of patients LWBS was described: they are generally males, young, with lower urgency triage allocation and longer waiting time. They have a greater risk of ED re-admission compared to discharged patients, but effect on hospitalization and mortality are more controversial. The aims of this study are to identify determinants and adverse short term outcomes for LWBS and LDT patients.

Methods

This is a retrospective cohort study that include all ED visits of LWBS, LDT and discharged patients in 2015 in the Lazio region, Central Italy. Determinants of LWBS or LDT were selected from gender, age, citizenship, residence area, triage category, chronic comorbidities, number of uncompleted ED visit in the previous year, mode of arrival in ED, time-band, day of the week, waiting time and ED crowding, using a multi-level logistic regression. A multivariate logistic regression was used to test if LWBS or LDT have a greater risk of short term adverse outcome compared to discharged patients.

Results

The cohort consists in 835,440 visits in ED, 86.8% subjects visited and discharged, 8.9% subjects are LWBS patients and 4.3% LDT. LWBS and LDT patients are mainly young, males, with a less severe triage, with long waiting times in ED. Moreover, ED crowding and leaving ED before physician’s visit in the previous year are risk factors of self-discharging. LWBS and LDT patients have a higher risk of readmission (LWBS: OR = 4.63, 95%CI 4.5–4.7; OR = 2.89, 95%CI 2.8–2.9; LDT: OR = 3.12, 95%CI 3–3.2; OR = 2.25, 95%CI2.2–2.3 for readmissions within 2 and 7 days respectively) and hospitalization (LWBS: OR = 3.65, 95%CI 3.4–3.9; OR = 2.25, 95%CI 2.1–2.4; LDT: OR = 3.96, 95%CI 3.6–4.3; OR = 2.62, 95%CI 2.4–2.8 for hospitalization within 2 and 7 days respectively). Furthermore, we find a mortality excess of risk for LWBS patients compared to the reference group (OR = 2.56, 95%CI1.6–4.2; OR = 1.7, 95%CI 1.3–2.2 within 2 and 7 days respectively).

Conclusions

Determinants of LWBS confirmed what already known, but LDT patients should be further investigated. There could be adverse health effects for people with LWBS and LDT behaviour. This could be an issue that the Regional Health System should deal with.

The effect on the patient flow in a local health care after implementing reverse triage in a primary care emergency department: a longitudinal follow-up study

OBJECTIVE

Reverse triage means that patients who are not considered to be in need of medical services are not placed on the doctor's list in an emergency department (ED) but are sent, after face-to-face evaluation by a triage nurse, to a more appropriate health care unit. It is not known how an abrupt application of such reverse triage in a combined primary care ED alters the demand for doctors' services in collaborative parts of the health care system.

DESIGN

An observational study.

SETTING

Register-based retrospective quasi-experimental longitudinal follow-up study based on a before-after setting in a Finnish city.

SUBJECTS

Patients who consulted different doctors in a local health care unit.

MAIN OUTCOME MEASURES

Numbers of monthly visits to different doctor groups in public and private primary care, and numbers of monthly referrals to secondary care ED from different sources of primary care were recorded before and after abrupt implementation of the reverse triage.

RESULTS

The beginning of reverse triage decreased the number of patient visits to a primary ED doctor without increasing mortality. Simultaneously, there was an increase in doctor visits in the adjacent secondary care ED and local private sector. The number of patients who came to secondary care ED without a referral or with a referral from the private sector increased.

CONCLUSIONS

The data suggested that the reverse triage causes redistribution of the use of doctors' services rather than a true decrease in the use of these services.

Partial replacement of board-certified specialist-grade physicians with emergency medicine trainees in a busy emergency department: Lack of adverse effect on time to physician

Objectives: Standard emergency department (ED) operation goals include minimization of the time interval between patients' initial ED presentation and initial emergency physician (EP) evaluation. Following up on previous work defining factors influencing the “time to physician” (tMD) in a busy ED, the current study was undertaken to evaluate whether tMD was adversely impacted by the ED's partial replacement of specialist-grade EPs with emergency medicine (EM) trainees (at the resident and fellow level). Methods: This retrospective study was conducted for four months (September–December 2015) using an ED administrative database (EDAD) in an urban academic tertiary ED with an annual census of approximately 500,000; during the four study months, the ED census was 165,969. To minimize confounding by time of day and related factors, data analysis focused solely on the “day shift” (0600–1400) of each of the study period's 122 days. EDAD data were combined with EP rostering data to generate a multivariate linear regression model that assessed the dependent variable tMD, for significant changes associated with increasing proportion – not necessarily always the same as increasing the absolute number of trainees (i.e., summed residents and fellows as a total percent of all on-duty EPs). There were trainees in the study ED throughout the study, but the trainee numbers as a proportion of the overall physician staffing fluctuated, thus providing a basis for analysis. The model adjusted for covariates previously demonstrated to impact tMD at the study center. Analyses were conducted with Stata 14MP, with statistical significance defined at p < 0.05 and confidence intervals (CIs) reported at the 95% level. Results: In an acceptable regression model that adjusted for multiple parameters influencing tMD, the introduction of a covariate representing the proportion of on-duty trainee physicians was very small in magnitude (β estimate 0.07, 95% CI − 0.16 to 0.30) and not statistically significant (p = 0.53). Conclusions: A multivariate analysis adjusting for variables contributing to tMD showed no indication of adverse tMD impact from partial replacement of board-certified specialist-grade EPs with EM trainees given adequate supervision by properly trained faculty.

Marginal analysis in assessing factors contributing time to physician in the Emergency Department using operations data

Background: Standard Emergency Department (ED) operations goals include minimization of the time interval (tMD) between patients' initial ED presentation and initial physician evaluation. This study assessed factors known (or suspected) to influence tMD with a two-step goal. The first step was generation of a multivariate model identifying parameters associated with prolongation of tMD at a single study center. The second step was the use of a study center-specific multivariate tMD model as a basis for predictive marginal probability analysis; the marginal model allowed for prediction of the degree of ED operations benefit that would be affected with specific ED operations improvements. Methods: The study was conducted using one month (May 2015) of data obtained from an ED administrative database (EDAD) in an urban academic tertiary ED with an annual census of approximately 500,000; during the study month, the ED saw 39,593 cases. The EDAD data were used to generate a multivariate linear regression model assessing the various demographic and operational covariates' effects on the dependent variable tMD. Predictive marginal probability analysis was used to calculate the relative contributions of key covariates as well as demonstrate the likely tMD impact on modifying those covariates with operational improvements. Analyses were conducted with Stata 14MP, with significance defined at p < 0.05 and confidence intervals (CIs) reported at the 95% level. Results: In an acceptable linear regression model that accounted for just over half of the overall variance in tMD (adjusted r² 0.51), important contributors to tMD included shift census (p = 0.008), shift time of day (p = 0.002), and physician coverage n (p = 0.004). These strong associations remained even after adjusting for each other and other covariates. Marginal predictive probability analysis was used to predict the overall tMD impact (improvement from 50 to 43 minutes, p < 0.001) of consistent staffing with 22 physicians. Conclusions: The analysis identified expected variables contributing to tMD with regression demonstrating significance and effect magnitude of alterations in covariates including patient census, shift time of day, and number of physicians. Marginal analysis provided operationally useful demonstration of the need to adjust physician coverage numbers, prompting changes at the study ED. The methods used in this analysis may prove useful in other EDs wishing to analyze operations information with the goal of predicting which interventions may have the most benefit.

[Not Available]

Objectif

L’objectif de cette étude rétrospective était d’identifier les facteurs associés aux décomptes quotidiens de départs avant prise en charge médicale (DAPCM) dans les deux salles d’urgence du Centre hospitalier universitaire de Sherbrooke, Fleurimont (HF) et Hôtel-Dieu (HD).

Méthode

Des données cliniques et démographiques anonymisées, ainsi que des données hospitalières, ont été extraites de la banque de données du Centre Informatisé de Recherche Évaluative en Services et Soins de Santé pour la période du 1er avril 2011 au 30 juin 2012. Les variables étant corrélées au nombre de DAPCM par jour par site lors des analyses univariées ont été retenues pour l’analyse de régression linéaire multivariée.

Résultats

Les analyses de régression multivariées démontrent que le nombre de DAPCM par jour diminue pour les deux sites lorsque la durée moyenne de séjour des patients non hospitalisés à l’urgence diminue (HF:b=1,17, p<0,001; HD:b=1,41, p<0,001) et lorsqu’un médecin dédié aux patients ambulatoires est présent (HF:b=-4,35, p<0,001; HD:b=-5,48, p<0,001). De plus, des facteurs reliés à l’achalandage des salles d’urgence et la raison primaire de consultation ont également eu un effet sur le nombre de DAPCM par jour.

Conclusion

Des efforts devraient être faits afin de diminuer la durée moyenne de séjour des patients non hospitalisés à l’urgence et d’assurer la présence d’un médecin dédié aux patients ambulatoires pour diminuer le nombre de DAPCM.

Identifying Patient Door-to-Room Goals to Minimize Left-Without-Being-Seen Rates

Introduction

Emergency department (ED) patients in the leave-without-being-seen (LWBS) group risk problems of inefficiency, medical risk, and financial loss. The goal at our hospital is to limit LWBS to <1%. This study’s goal was to assess the influence on LWBS associated with prolonging intervals between patient presentation and placement in an exam room (DoorRoom time). This study’s major aim was to identify DoorRoom cutoffs that maximize likelihood of meeting the LWBS goal (i.e. <1%).

Methods

We conducted the study over one year (8/13–8/14) using operations data for an ED with annual census ~50,000. For each study day, the LWBS endpoint (i.e. was LWBS <1%: “yes or no”) and the mean DoorRoom time were recorded. We categorized DoorRoom means by intervals starting with ≤10min and ending at >60min. Multivariate logistic regression was used to assess for DoorRoom cutoffs predicting high LWBS, while adjusting for patient acuity (triage scores and admission %) and operations parameters. We used predictive marginal probability to assess utility of the regression-generated cutoffs. We defined statistical significance at p<0.05 and report odds ratio (OR) and 95% confidence intervals (CI).

Results

Univariate results suggested a primary DoorRoom cutoff of 20′, to maintain a high likelihood (>85%) of meeting the LWBS goal. A secondary DoorRoom cutoff was indicated at 35′, to prevent a precipitous drop-off in likelihood of meeting the LWBS goal, from 61.1% at 35′ to 34.4% at 40′. Predictive marginal analysis using multivariate techniques to control for operational and patient-acuity factors confirmed the 20′ and 35′ cutoffs as significant (p<0.001). Days with DoorRoom between 21–35′ were 74% less likely to meet the LWBS goal than days with DoorRoom ≤20′ (OR 0.26, 95% CI [0.13–0.53]). Days with DoorRoom >35′ were a further 75% less likely to meet the LWBS goal than days with DoorRoom of 21–35′ (OR 0.25, 95% CI [0.15–0.41]).

Conclusion

Operationally useful DoorRoom cutoffs can be identified, which allow for rational establishment of performance goals for the ED attempting to minimize LWBS.