Setting wait times to achieve targeted left-without-being-seen rates

Reduced left-without-being-seen rates and impact on disparities after guest services ambassadors implementation

BACKGROUND

The rate of patients who leave without being seen (LWBS) from an emergency department (ED) is a common measurement of quality, operational efficiency, and patient satisfaction. We hypothesized that adding a nonclinical staff role, guest service ambassadors (GSA), to the ED waiting room would decrease LWBS rates and reduce existing differences by race, ethnicity, sex, and primary language for ED patients.

METHODS

We conducted an observational cohort study at a quaternary care academic ED in the Midwestern United States with approximately 60,000 annual visits between April and December 2022. GSAs were trained to guide patients and visitors through the check-in process and help manage the waiting room. LWBS rates were compared between pre- and postimplementation periods using logistic regression. Using two-sample proportion tests, subgroup analyses were performed to assess differences according to race, ethnicity, sex, and primary language.

RESULTS

We analyzed 50,507 ED visits including 9798 during periods of GSA coverage. GSA presence was associated with a reduction in LWBS rate from 3.4% to 2.0% (absolute risk reduction [ARR] of 1.4%, χ2 = 17.357, p < 0.001) with an adjusted odds ratio (OR) of 0.65 (95% confidence interval [CI] 0.49-0.85). There was a greater reduction in LWBS for Black, Indigenous, and people of color (BIPOC) patients compared to White patients (BIPOC ARR 1.8%, 95% CI 0.39%-3.14%; White ARR 1.2%, 95% CI 0.48%-1.94%). There was a reduction in LBWS rates for both males and females (female ARR 1.7%, 95% CI 0.80%-2.63%; male ARR 1.0%, 95% CI 0.06%-1.90%). The reduction in LWBS for patients speaking a language other than English and requiring interpreter services did not meet statistical significance (ARR 1.4%, 95% CI -1.04% to 3.85%).

CONCLUSIONS

Although some disparities remain, our study suggests that GSAs may provide an effective strategy to reduce the overall LWBS rate and reduce disparities across diverse demographic groups including BIPOC and female patients.

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.

Patient experience of emergency department triage: An integrative review

BACKGROUND

Emergency department (ED) triage is often patients' first contact with a health service and a critical point for patient experience. This review aimed to understand patient experience of ED triage and the waiting room.

METHODS

A systematic six-stage approach guided the integrative review. Medline, CINAHL, EmCare, Scopus, ProQuest, Cochrane Library, and JBI database were systematically searched for primary research published between 2000-2022 that reported patient experience of ED triage and/or waiting room. Quality was assessed using established critical appraisal tools. Data were analysed for descriptive statistics and themes using the constant comparison method.

RESULTS

Twenty-nine articles were included. Studies were mostly observational (n = 17), conducted at a single site (n = 23), and involved low-moderate acuity patients (n = 13). Nine interventions were identified. Five themes emerged: 'the who, what and how of triage', 'the patient as a person', 'to know or not to know', 'the waiting game', and 'to leave or not to leave'.

CONCLUSION

Wait times, initiation of assessment and treatment, information provision and interactions with triage staff appeared to have the most impact on patient experience, though patients' desires for each varied. A person-centred approach to triage is recommended.

Urgent Care Versus Emergency Department Utilization for Foot and Ankle Fractures

INTRODUCTION

Foot and ankle fractures are common injuries for which patients may need urgent evaluation and care. Many such injuries are managed in emergency departments (EDs), but urgent care facilities may sometimes be an appropriate setting. Understanding which foot and ankle fractures are managed at which facility might help define care algorithms, improve patient experience, and suggest directions for containing costs.

METHODS

This retrospective cohort study used the 2010 to 2020 M151 PearlDiver administrative database. Adult patients less than 65 years old presenting to EDs and urgent care facilities for foot and ankle fractures were identified using ICD-9 and ICD-10 diagnosis codes, excluding polytrauma, and Medicare patients. Patient/injury variables associated with urgent care utilization relative to ED utilization and utilization trends of urgent care relative to ED were assessed with univariable and multivariable analyses.

RESULTS

From 2010 to 2020, 1,120,422 patients with isolated foot and ankle fractures presented to EDs and urgent care facilities. Urgent care visits evolved from 2.2% in 2010 to 4.4% in 2020 (P , 0.0001). Independent predictors of urgent care relative to ED utilization were defined. In decreasing odds ratios (ORs), these were insurance (relative to Medicaid, commercial OR 8.03), geographic region (relative to Midwest, Northeast OR 3.55, South OR 1.74, West OR 1.06), anatomic location of fracture (relative to ankle, forefoot OR 3.45, midfoot 2.20, hindfoot 1.63), closed fracture (OR 2.20), female sex (OR 1.29), lower ECI (OR 1.11 per unit decrease), and younger age (OR 1.08 per decade decrease) (P , 0.0001 for all).

DISCUSSION

A small but increasing minority of patients with foot and ankle fractures are managed in urgent care facilities relative to EDs. While patients with certain injury types were associated with increased odds of urgent care relative to ED utilization, the greatest predictors were nonclinical, such as geographic regions and insurance type, suggesting areas for optimizing access to certain care pathways.

LEVEL OF EVIDENCE

III.

The association between day of arrival, time of arrival, daily volume and the rate of patients that "left without being seen"

INTRODUCTION

Patients' left without being seen (LWBS) rate is used as an emergency department (ED) quality indicator. Prior research has investigated characteristics of these patients, but there are minimal studies assessing the impact of departmental variables. We evaluate the LWBS rate at a granular level, looking at its relationship to day of week, hour of arrival and total patient volume.

METHODS

Retrospective cohort analysis of 109,983 cases from a single academic center. We captured patient disposition, day of week and hour of day of arrival, and total daily volume. Chi-squared test was performed to determine the difference in LWBS rates based on arrival variables. We ran a polynomial regression for LWBS rates by decile of daily patient volume.

RESULTS

The overall LWBS rate was 1.82% over 2 years. This varied significantly by day of week and hour of day (p < 0.001). Day of week rates ranged from 0.73% on Sunday to 2.45% on Wednesday. Hour of day rates ranged from 0.26% between 8 AM-9 AM, to 3.71% between 10 PM-11 PM. As total daily patient volume increased, LWBS rates gradually increased until the 70th percentile, followed by significant exponential growth afterwards.

DISCUSSION

LWBS rates are not static measurements, and vary greatly depending on ED circumstances. Weekdays and evenings have significantly higher rates. Additionally, LWBS rates climb above 2% as daily registrations reach the 70th percentile, increasing exponentially at each subsequent decile. Understanding these effects will allow for more effective, targeted interventions to minimize this rate and improve throughput.

Crowding is the strongest predictor of left without being seen risk in a pediatric emergency department

BACKGROUND

Emergency Department (ED) patients who leave without being seen (LWBS) are associated with adverse safety and medico-legal consequences. While LWBS risk has been previously tied to demographic and acuity related factors, there is limited research examining crowding-related risk in the pediatric setting. The primary objective of this study was to determine the association between LWBS risk and crowding, using the National Emergency Department Overcrowding Score (NEDOCS) and occupancy rate as crowding metrics.

METHODS

We performed a retrospective observational study on electronic health record (EHR) data from the ED of a quaternary care children's hospital and trauma center during the 14-month study period. NEDOCS and occupancy rate were calculated for 15-min windows and matched to patient arrival time. We leveraged multiple logistic regression analyses to demonstrate the relationship between patientlevel LWBS risk and each crowding metric, controlling for characteristics drawn from the pre-arrival state. We performed a chi-squared test to determine whether a difference existed between the receiver operating characteristic (ROC) curves in the two models. Finally, we executed a dominance analysis using McFadden's pseudo-R 2 to determine the relative importance of each crowding metric in the models.

RESULTS

A total of 54,890 patient encounters were studied, 1.22% of whom LWBS. The odds ratio for LWBS risk was 1.30 (95% CI 1.27-1.33) per 10-point increase in NEDOCS and 1.23 (95% CI 1.21-1.25). per 10% increase in occupancy rate. Area under the curve (AUC) was 86.9% for the NEDOCS model and 86.7% for the occupancy rate model. There was no statistically significant difference between the AUCs of the two models (p-value 0.27). Dominance analysis revealed that in each model, the most important variable studied was its respective crowding metric; NEDOCS accounted for 55.6% and occupancy rate accounted for 53.9% of predicted variance in LWBS.

CONCLUSION

Not only was ED overcrowding positively and significantly associated with individual LWBS risk, but it was the single most important factor that determined a patient's likelihood of LWBS in the pediatric ED. Because occupancy rate and NEDOCS are available in real time, each could serve as a monitor for individual LWBS risk in the pediatric ED.

Racial/ethnic disparities in emergency department wait times in the United States, 2013-2017

BACKGROUND

Previous research shows that Black and Hispanic patients have longer ED wait times than White patients, but these data do not reflect recent changes such as the Affordable Care Act. In addition, previous research does not account for the non-normal distribution of wait times, wherein a sizable subgroup of patients seen promptly and those not seen promptly experience long wait times.

METHODS

We utilized National Hospital Ambulatory Medical Care Survey (NHAMCS) datasets (2013-2017) to examine mean ED wait time comparing visits by Black, Hispanic, and Asian patients to White patients. Using a two-part regression model, we adjusted for patient, hospital, and health system factors, and estimated differences, for each of five triage levels, in (a) likelihood of waiting at least 5 min and (b) difference in wait time among those not seen promptly.

RESULTS

Our cohort included 38,800 White, 14,838 Black, 10,619 Hispanic, and 1257 Asian patient visits. Black (triage level 3) and Hispanic (triage levels 3 and 4) patients had longer mean wait times than White patients. Adjusted likelihood of not being seen promptly was lower among Blacks (triage levels 3, 4 and 5), Hispanics (triage level 5) and Asians (triage level 5) compared to Whites. Among those waiting at least 5 min, adjusted wait time was longer among Blacks in triage level 3 (5.2 min, 95% CI, 1.3 to 9.0) and level 4 (2.5 min, 95% CI, 0.2 to 4.9), Hispanics in triage level 4 (4.7 min, 95% CI, 1.7 to 7.7) and Asians in triage level 5 (16.3 min, 95% CI, 0.6 to 31.9) compared to Whites.

CONCLUSIONS

Minority patients were less likely to wait to be seen, but waited longer if not seen promptly. These data exhibit that ED wait time disparities persist for African American and Hispanic patients and extend this observation to Asian patients.

Emergency Department Patients Who Leave Before Treatment Is Complete

Introduction

Emergency department (ED) patients who leave before treatment is complete (LBTC) represent medicolegal risk and lost revenue. We sought to examine LBTC return visits characteristics and potential revenue effects for a large healthcare system.

Methods

This retrospective, multicenter study examined all encounters from January 1–December 31, 2019 at 18 EDs. The LBTC patients were divided into left without being seen (LWBS), defined as leaving prior to completed medical screening exam (MSE), and left subsequent to being seen (LSBS), defined as leaving after MSE was complete but before disposition. We recorded 30-day returns by facility type including median return hours, admission rate, and return to index ED. Expected realization rate and potential charges were calculated for each patient visit.

Results

During the study period 626,548 ED visits occurred; 20,158 (3.2%) LBTC index encounters occurred, and 6745 (33.5%) returned within 30 days. The majority (41.7%) returned in <24 hours with 76.1% returning in 10 days and 66.4% returning to index ED. Median return time was 43.3 hours, and 23.2% were admitted. Urban community EDs had the highest 30-day return rate (37.8%, 95% confidence interval, 36.41–39.1). Patients categorized as LSBS had longer median return hours (66.0) and higher admission rates (29.8%) than the LWBS cohort. There was a net potential realization rate of $9.5 million to the healthcare system.

Conclusion

In our system, LSBS patients had longer return times and higher admission rates than LWBS patients. There was significant potential financial impact for the system. Further studies should examine how healthcare systems can reduce risk and financial impacts of LBTC patients.

Patients leaving without being seen from the emergency department: A prediction model using machine learning on a nationwide database

OBJECTIVE

The objective of this study was to develop a US-representative prediction model identifying factors with a greater likelihood of patients leaving without being seen.

METHODS

We conducted a retrospective cohort analysis using a 2016 nationwide emergency department (ED) sample. Patient factors considered for analysis were the following: age, sex, acuity, chronic diseases, weekend visit, quarter of presentation, median household income quartile for patient's zip code, primary/secondary insurance, total charges for the visit, and urban/rural household. Hospital factors considered were urban/rural location, trauma center/teaching hospital, and annual ED volume. Multivariable logistic regression was used to find significant predictors and their interactions. A random forest algorithm was used to determine the order of importance of factors.

RESULTS

A total of 32,680,232 hospital-based ED visits with 466,047 incidences of leaving without being seen were included. The cohort comprised 55.5% females, with a median (IQR) age of 37 (21-58) years. Positively associating factors were male sex (odds ratio [OR], 1.22; 99% confidence interval [CI], 1.17-1.26), lower acuity (P < 0.001), and annual ED visits ≥60,000 (OR, 1.44; 99% CI, 1.21-1.7) versus <20,000. Negatively associating factors were primary insurance being Medicare/Tricare or private insurance (P < 0.001); weekend presentations (OR, 0.87; 99% CI, 0.85-0.89); age >64 or <18 years (P < 0.001); and higher median household income for patient's zip code second (OR, 0.86; 99% CI, 0.77-0.97), third (OR, 0.8; 99% CI, 0.7-0.91), and fourth (OR, 0.7; 99% CI, 0.6-0.8) quartiles versus the first quartile. Significant interactions existed between age, acuity, primary insurance, and chronic conditions. Primary insurance was the most predictive.

CONCLUSION

Our derivation model reiterated several modifiable and non-modifiable risk factors for leaving without being seen established previously while rejecting the importance of others.

The Buffering Effect of Humanity of Care in the Relationship between Patient Satisfaction and Waiting Time: A Cross-sectional Study in an Emergency Department

This study aims to examine whether humanity of care and environmental comfort played a role in moderating the relationship between waiting time and patient satisfaction in an emergency department (ED). The study used a cross-sectional and non-randomized design. A total of 260 ED patients in two hospitals in Italy completed a self-report questionnaire. Moderated regression showed that after adjusting for control variables, waiting time was significantly and inversely associated with patient satisfaction. Humanity of care and environmental comfort showed a positive and significant association with patient satisfaction. Finally, the interaction term between waiting time and humanity of care was found to be significant, whereas the interaction effect between waiting time and environmental comfort was not significant. The conditional effect showed that when humanity of care was low, waiting time was negatively and significantly related to patient satisfaction. By contrast, when humanity of care was medium and high, the relationship between waiting time and patient satisfaction was not significant. These findings shed light on the key role of humanity of care in moderating the relationship between waiting time and patient satisfaction. The complex interrelations emerged should be carefully considered when interventions to foster patient satisfaction in an ED context are planned.

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.

An exploration of the reasons why people attend but do not wait to be seen in emergency departments

AIM

The aim of the study was to explore the reasons why people do not always wait to receive treatment after registering in emergency departments (EDs).

METHOD

Patients who attended the ED at a general hospital in the south of England and left without being seen (LWBS) were recorded between 1 June and 31 August 2016 and 597 patient records were analysed. Six patients participated in semi-structured interviews. Data were manually coded.

FINDINGS

The most common presenting complaint for people who LWBS was limb problems, however some had potentially more serious conditions such as chest pain. The six interviewees accessed the ED because of a perceived urgent need, and reasons for leaving before being seen included long waiting time, other commitments, non-availability of specialty services, perceiving their problem as less urgent, resolution of condition and discomfort in the waiting area.

CONCLUSION

People who LWBS may not have trivial health problems, which is a risk for them and hospital trusts. Although many of the people who LWBS did so because of the lengthy waiting time, there may be other factors involved some of which could be prevented.

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.

Characterization of emergency department abandonment using a real-time location system

BACKGROUND

Patients who present to emergency departments (EDs) for evaluation but are noted to have left without being seen (LWBS) are potentially at great risk. Governmental agencies, such as the Centers for Medicare and Medicaid, as well as hospitals and health organizations, are examining the factors which drive LWBS, including accurately quantifying patient tolerance to wait times and targeting interventions to improve patient tolerance to waiting.

OBJECTIVE

Compare traditional methods of estimating time to LWBS with an objective method using a real-time location tracking system (RTLS); examine temporal factors associated with greater LWBS rates.

METHODS

This is a retrospective cohort study of all ED visits to a large, suburban, quaternary care hospital in one calendar year. LWBS was calculated as patient registration to nurse recognition and documentation of patient abandonment (traditional method) vs registration to last onsite RTLS timestamp (study method). Descriptives of patterns of patient abandonment rates and patient demographic data were also included.

RESULTS

Our study shows that traditional methods of measuring LWBS times significantly overestimate actual patient tolerance to waiting times (median 70, mean 92 min). Patients triaged to resource intensive categories (Emergency Severity Index (ESI) 2, 3) wait longer than patients triaged to less resource intensive categories (ESI 4, 5).

CONCLUSION

Compared to traditional methods, RTLS is an efficient and accurate way to measure LWBS rates and helps set the stage for assessing the efficacy of interventions to reduce LWBS and reduce the gap between those seeking evaluation at emergency departments and those ultimately receiving it.

Patients Who Leave the Emergency Department Without Being Seen and Their Follow-Up Behavior: A Retrospective Descriptive Analysis

BACKGROUND

Past studies suggest that patients who leave without being seen (LWBS) by a physician from a hospital's emergency department (ED) represent a quality and safety concern, and thus LWBS rates have often been used as an ED performance metric. There are few recent studies, however, that have examined the characteristics of the LWBS population at hospitals in the United States.

OBJECTIVE

This study describes the LWBS population at a multi-hospital academic health system.

METHODS

This was a retrospective study of electronic medical record data from EDs at two academic hospitals with a shared patient population that analyzed all LWBS visits during the 45-month period between July 2012 and March 2016. Demographic and clinical variables, including patient characteristics, chief complaint, acuity, and evidence of ongoing medical care, were assessed.

RESULTS

During the study period, 2.4% of patients presenting to the study EDs left without being seen. This population tended to have lower-acuity chief complaints and nearly triple the number of ED visits as the general ED patient; 7.8% sought follow-up care from outpatient clinics and 24.8% returned to the ED within 7 days. Of this latter group, 11.5% were subsequently admitted for inpatient care, representing 0.068% of the total ED census during the study period.

CONCLUSIONS

LWBS patients are high ED utilizers who may be effectively targeted by "hotspotting." Our 11.5% admission rate at return after LWBS compares favorably with the overall 20.9% admission rate at the study EDs and represents a small minority of all LWBS visits. Given the paucity of return ED visits after interval clinic encounters, our data suggest that patients who were seen in clinic had their medical complaint adequately resolved on a non-emergent outpatient basis, and that increased LWBS rates may reflect poor access to timely clinic-based care rather than intrinsic systemic issues within the ED.

ED Triage Process Improvement: Timely Vital Signs for Less Acute Patients

PROBLEM

Vital signs can result in an upgrade of patients' Emergency Severity Index (ESI) levels. It is therefore preferable to obtain vital signs early in the triage process, particularly for ESI level 3 patients. Emergency departments have an opportunity to redesign triage processes to meet required protocols while enhancing the quality and experience of care.

METHODS

We performed process analyses to redesign the door-to-vital signs process. We also developed spaghetti diagrams to reconfigure the patient arrival area.

RESULTS

The door-to-vital signs time was reduced from 43.1 minutes to 6.44 minutes. Both patients and triage staff seemed more satisfied with the new process. The patient arrival area was less congested and more welcoming.

DISCUSSION

Performing activities in parallel reduces flow time with no additional resources. Staff involvement in process planning, redesign, and control ensures engagement and early buy-in. One should anticipate how changes to one process might affect other processes.

Lessons Learned From the Development and Parameterization of a Computer Simulation Model to Evaluate Task Modification for Health Care Providers

Computer simulation is a highly advantageous method for understanding and improving health care operations with a wide variety of possible applications. Most computer simulation studies in emergency medicine have sought to improve allocation of resources to meet demand or to assess the impact of hospital and other system policies on emergency department (ED) throughput. These models have enabled essential discoveries that can be used to improve the general structure and functioning of EDs. Theoretically, computer simulation could also be used to examine the impact of adding or modifying specific provider tasks. Doing so involves a number of unique considerations, particularly in the complex environment of acute care settings. In this paper, we describe conceptual advances and lessons learned during the design, parameterization, and validation of a computer simulation model constructed to evaluate changes in ED provider activity. We illustrate these concepts using examples from a study focused on the operational effects of HIV screening implementation in the ED. Presentation of our experience should emphasize the potential for application of computer simulation to study changes in health care provider activity and facilitate the progress of future investigators in this field.

Cannabinoid hyperemesis syndrome presentation to the emergency department: A two-year multicentre retrospective chart review in a major urban area

OBJECTIVE

Cannabinoid hyperemesis syndrome (CHS) is a paradoxical side effect of cannabis use. Patients with CHS often present multiple times to the emergency department (ED) with cyclical nausea, vomiting, and abdominal pain, and are discharged with various misdiagnoses. CHS studies to date are limited to case series. The objective was to examine the epidemiology of CHS cases presenting to two major urban tertiary care centre EDs and one urgent care centre over a 2-year period.

METHODS

Using explicit variables, trained abstractors, and standardized abstraction forms, we abstracted data for all adults (ages 18 to 55 years) with a presenting complaint of vomiting and/or a discharge diagnosis of vomiting and/or cyclical vomiting, during a 2-year period. The inter-rater agreement was measured using a kappa statistic.

RESULTS

We identified 494 cases: mean age 31 (+/-11) years; 36% male; and 19.4% of charts specifically reported cannabis use. Among the regular cannabis users (>three times per week), 43% had repeat ED visits for similar complaints. Moreover, of these patients, 92% had bloodwork done in the ED, 92% received intravenous fluids, 89% received antiemetics, 27% received opiates, 19% underwent imaging, 8% were admitted to hospital, and 8% were referred to the gastroenterology service. The inter-rater reliability for data abstraction was kappa=1.

CONCLUSIONS

This study suggests that CHS may be an overlooked diagnosis for nausea and vomiting, a factor that can possibly contribute to unnecessary investigations and treatment in the ED. Additionally, this indicates a lack of screening for CHS on ED history, especially in quantifying cannabis use and eliciting associated symptoms of CHS.

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.

A comparative study of patient characteristics, opinions, and outcomes, for patients who leave the emergency department before medical assessment

OBJECTIVE

The emergency department (ED) left-without-being-seen (LWBS) rate is a performance indicator, although there is limited knowledge about why people leave, or whether they seek alternate care. We studied characteristics of ED LWBS patients to determine factors associated with LWBS.

METHODS

We collected demographic data on LWBS patients at two urban hospitals. Sequential LWBS patients were contacted and surveyed using a standardized telephone survey. A matched group of patients who did not leave were also surveyed. Data were analysed using the Fisher exact test, chi-square test, and student t-test.

RESULTS

The LWBS group (n=1508) and control group (n=1504) were matched for sex, triage category, recorded wait times, employment and education, and having a family physician. LWBS patients were younger, more likely to present in the evening or at night, and lived closer to the hospital. A long wait time was the most cited reason for leaving (79%); concern about medical condition was the most common reason for staying (96%). Top responses for improved likelihood of waiting were shorter wait times (LWBS, 66%; control, 31%) and more information on wait times (41%; 23%). A majority in both groups felt that their condition was a true emergency (63%; 72%). LWBS patients were more likely to seek further health care (63% v. 28%; p<0.001) and sooner (median time 1 day v. 2-4 days; p=0.002). Among patients who felt that their condition was not a true emergency, the top reason for ED attendance was the inability to see their family doctor (62% in both groups).

CONCLUSION

LWBS patients had similar opinions, experiences, and expectations as control patients. The main reason for LWBS was waiting longer than expected. LWBS patients were more likely to seek further health care, and did so sooner. Patients wait because of concern about their health problem. Shorter wait times and improved communication may reduce the LWBS rate.

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.

Use of the SONET score to evaluate Urgent Care Center overcrowding: a prospective pilot study

OBJECTIVES

To derive a tool to determine Urgent Care Center (UCC) crowding and investigate the association between different levels of UCC overcrowding and negative patient care outcomes.

DESIGN

Prospective pilot study.

SETTING

Single centre study in the USA.

PARTICIPANTS

3565 patients who registered at UCC during the 21-day study period were included. Patients who had no overcrowding statuses estimated due to incomplete collection of operational variables at the time of registration were excluded in this study. 3139 patients were enrolled in the final data analysis.

PRIMARY AND SECONDARY OUTCOME MEASURES

A crowding estimation tool (SONET: Severely overcrowded, Overcrowded and Not overcrowded Estimation Tool) was derived using the linear regression analysis. The average length of stay (LOS) in UCC patients and the number of left without being seen (LWBS) patients were calculated and compared under the three different levels of UCC crowding.

RESULTS

Four independent operational variables could affect the UCC overcrowding score including the total number of patients, the number of results pending for patients, the number of patients in the waiting room and the longest time a patient was stationed in the waiting room. In addition, UCC overcrowding was associated with longer average LOS (not overcrowded: 133±76 min, overcrowded: 169±79 min, and severely overcrowded: 196±87 min, p<0.001) and an increased number of LWBS patients (not overcrowded: 0.28±0.69 patients, overcrowded: 0.64±0.98, and severely overcrowded: 1.00±0.97).

CONCLUSIONS

The overcrowding estimation tool (SONET) derived in this study might be used to determine different levels of crowding in a high volume UCC setting. It also showed that UCC overcrowding might be associated with negative patient care outcomes.