Emergency Department Census Research Articles

Emergency department crowding associated with increased 30-day mortality: a cohort study in Stockholm Region, Sweden, 2012 to 2016.

ObjectivesEmergency department (ED) crowding is a major problem across the world. Studies investigating the association between crowding and mortality are many, but the quality is inconsistent and there are very few large, high‐quality multicenter studies that are properly designed to deal with confounding due to case mix. The aim of this study is to investigate the association between ED crowding and 30‐day mortality.MethodsWe conducted an observational cohort study at all 7 EDs in Stockholm Region, Sweden 2012–2016. The crowding exposure was defined as the mean hourly ED census during the shift that the exposed patient arrived, divided with the expected ED census for this shift. The expected ED census was estimated using a separate linear model for each hospital with year and shift as predictors. The exposure was categorized in 3 groups: reference (lowest 75% of observations), moderate (75%–95% of observations), and high (highest 5% of observations). Hazard ratios (HR) for all‐cause mortality within 30 days were estimated with a Cox proportional hazards model. The model was adjusted for age, sex, triage priority, arrival hour, weekend, arrival mode, chief complaint, number of prior hospital admissions, and comorbidities.Results884,228 patients who visited the ED 2,252,656 times were included in the analysis. The estimated HR (95% confidence interval) for death within 30‐days was 1.00 (0.97–1.03) in crowding category 75%‐95% and 1.08 (1.03–1.14) in the 95%‐100% category.ConclusionsIn a large cohort study including 7 EDs in Stockholm Region, Sweden we identified a significant association between high levels of ED crowding and increased 30‐day mortality.

Braving the COVID-19 Pandemic.

I peeked at the clock as it struck 10:55 am—just 5 minutes until we would be free from further admissions. I could identify only one patient on the emergency department's census who looked unwell enough to be hospitalized: a young man with the most convincing story for a COVID-19 diagnosis. He had a non-productive cough, fevers, lymphopenia, dyspnea upon exertion with associated hypoxemia, and recent travel with friends who were confirmed to have COVID-19. The hospitalists had been caring for these patients thus far, though rumors had been circulating that their teams were full, and the resident teams would be up next. It was barely before 11:00 when my pager went off. “Call the ER for admission of 31 y/o M with dyspnea, concerning for COVID-19.” My heart sank.The last couple of months had been sobering as we watched our friends in New York take on the COVID-19 health crisis. We awaited, with a mix of fear and anticipation, for the surge of patients that we knew was coming. The longer we waited, the more conflicted I felt by how society had been portraying people like me—we were the so-called “health care heroes.” Though, to tell you the truth, I had never been more terrified. I looked around the room and sensed a similar uneasiness as my peers acknowledged the page I had received. At that moment we understood that our time to be at the frontlines had begun.I had noticed an escalating tension in the hospital over the last couple of weeks as our staff had begun caring for patients under investigation for COVID-19. Now, in the moment, the fear was clear on the faces of the ER staff waiting for me downstairs. For many of us, this person was likely to be our first positive case. The nurse's hands trembled as he handed me supplies for monitoring vitals and performing blood draws. There was no sense in having multiple providers in the room assessing the patient when I could do it and prevent them from further exposure. The ER staff gathered in a crowd, along with my team and our infectious disease consultants, all of whom nervously watched as I stepped into the anteroom and gowned up to enter the unknown.Weeks later, we have all become more familiar and comfortable with caring for patients with COVID-19. The clinical trajectory has become more predictable for us, though not always with the outcomes we had hoped. Our anxiety and fear of the unknown have transformed into a deep sorrow. We watched as several patients lose their battles, not knowing what we could have done differently to save them. How can we practice evidence-based medicine, when the only existing studies are either too small, unrandomized, or unblinded? Where do we find guidance when no one has cared for a patient with this illness before? It felt like I was wobbling in place with the weight of the world on my shoulders as I stood unsure of which direction to take.It was not long before we started hearing about health care workers losing their lives to COVID-19 as well. It hits the hardest when I hear that a resident passed on from this disease. There is an existential crisis that follows with every loss, layered with feelings of guilt, grief, and a sense of injustice. But the COVID-19 pandemic is unforgiving. There is no time to dwell, as patients keep coming in at an alarming rate. Most of us at the frontlines have largely suppressed these emotional reactions to allow for a clear mind amid the pandemic. This health crisis has been a life-altering experience that has challenged us and brought the medical community together in ways we could never have imagined. When the world someday begins to recover, we too must find ways to heal from the emotional burden we harbored as trainees.The Hippocratic Oath promises a life of service that places value on the principles of patient autonomy and nonmaleficence. At no point is there an agreement to be brave, though it is implicit with our current pandemic that we must try our best. We are the “health care heroes.” When alone in the anteroom, we must decide whether to remain paralyzed by fear or whether to open that next door. By doing the latter, we follow through with our duty to our patients while empowering each other to face this new challenge together. As we continue facing the surge of COVID-19 cases, I feel committed to complete the mission started by those in the health care field who fought, despite their fears, and lost their lives. Even with the wobbling sensation of the world on my shoulders, I choose to go forward.

Resuscitation Resident Impact in the Treatment of Sepsis.

BackgroundThe resuscitation of septic patients is a fundamental skill of emergency medicine (EM) training. We developed a required rotation designed to augment resident training in resuscitating critically ill patients in the emergency department (ED). The purpose of this study was to evaluate the successful completion of sepsis core measures alongside clinical outcomes between patients with a resuscitation resident (RR) involved in care versus patients without.MethodsThis retrospective study was conducted at a single site tertiary care Level 1 trauma center with an ED census of 130,000 visits annually. Data were collected from January 1, 2015, to December 31, 2016, using the electronic medical record (EMR) via an Epic query (Epic Systems Corp., Verona, WI). Patients admitted with severe sepsis or septic shock (Surviving Sepsis Campaign guidelines) were included and separated into two groups, one with RR involvement and one without. Emergency department length of stay, time to initial lactic acid draw, lactic acid value, time to bolus fluid initiation, time to antibiotic initiation, need for medical intensive care unit (ICU) admission, and 30-day mortality were compared between the two groups. Chi-square tests and Fisher’s exact tests were used to analyze the categorical variables. Two-sided t-tests and Wilcoxon rank-sum tests were used to examine continuous variables.ResultsOut of 4,746 patients admitted, 101 patients had an RR participate in their care. The median time to initial lactic acid draw was shorter (0.53 vs 1.05 hours; p < 0. 0001) and the lactic acid level was higher (2.5 vs 1.8 mmol/L; p < 0. 0001) with the presence of an RR. Resuscitation resident was correlated with a decrease in time to antibiotics and appropriate 30 cc/kg bolus, however, these were not statistically significant (p = 0.10 and p = 0.09 respectively). Resuscitation resident involvement was also associated with more medical ICU (45.5% vs 18.8%; p<0.0001) admissions and a higher 30-day mortality (14.9% vs 29.7%; p < 0. 0001). All other variables were not statistically significant.ConclusionResuscitation residents demonstrate a statistically significant impact on lactic acid-related bundle compliance and help facilitate the care of higher acuity severe sepsis and septic shock patients.

Envisioning the Post-COVID-19, Pre-Vaccine Emergency Department.

Envisioning the Post-COVID-19, Pre-Vaccine Emergency Department.

P119: Emergency department census is useful as a real-time measure of crowding

Introduction: Crowding is associated with poor patient outcomes in emergency departments (ED). Measures of crowding are often complex and resource-intensive to score and use in real-time. We evaluated single easily obtained variables to establish the presence of crowding compared to more complex crowding scores. Methods: Serial observations of patient flow were recorded in a tertiary Canadian ED. Single variables were evaluated including total number of patients in the ED (census), in beds, in the waiting room, in the treatment area waiting to be assessed, and total inpatient admissions. These were compared with Crowding scores (NEDOCS, EDWIN, ICMED, three regional hospital modifications of NEDOCS) as predictors of crowding. Predictive validity was compared to the reference standard of physician perception of crowding, using receiver operator curve analysis. Results: 144 of 169 potential events were recorded over 2 weeks. Crowding was present in 63.9% of the events. ED census (total number of patients in the ED) was strongly correlated with crowding (AUC = 0.82 with 95% CI = 0.76 - 0.89) and its performance was similar to that of NEDOCS (AUC = 0.80 with 95% CI = 0.76 - 0.90) and a more complex local modification of NEDOCS, the S-SAT (AUC = 0.83, 95% CI = 0.74 - 0.89). Conclusion: The single indicator, ED census was as predictive for the presence of crowding as more complex crowding scores. A two-stage approach to crowding intervention is proposed that first identifies crowding with a real-time ED census statistic followed by investigation of precipitating and modifiable factors. Real time signalling may permit more standardized and effective approaches to manage ED flow.

Equitable and Timely Care of Febrile Neonates: A Cross-Sectional Study.

In pediatric emergency departments (EDs), racial/ethnic minorities are less likely to receive needed and timely care; however, clinical protocols have the potential to mitigate disparities. Neonatal fever management is protocolized in many EDs, but the timeliness to antibiotic administration is likely variable. We investigated the timeliness of antibiotic administration for febrile neonates and whether timeliness was associated with patients' race/ethnicity. Retrospective cross-sectional study of febrile neonates evaluated in one pediatric ED that uses an evidence-based guideline for the management of neonatal fever between March 2010 and December 2015. Primary outcome was time from ED arrival to antibiotic administration. Analysis of variance tests compared mean time with antibiotic administration across race/ethnicity. Multivariable linear regression investigated racial/ethnic differences in time to antibiotic administration after adjusting for patient demographics, timing of visit, the number of physicians involved, and ED census. We evaluated 317 febrile neonates. Of the 269 patients with racial/ethnic data (84.9%), 54% were white non-Hispanic, 13% were black non-Hispanic, and 23% were Hispanic. The mean time to antibiotic administration was 204 minutes (range = 51-601 minutes). There was no significant association between patient race/ethnicity and time to first antibiotic administration. Emergency department census was significantly associated with timeliness. There was a 10-hour range in the time to antibiotic administration for febrile neonates; however, variability in timeliness did not differ by race or ethnicity. This study demonstrates the need to further examine the role of protocols in mitigating disparities as well as factors that influence timeliness in antibiotic administration to febrile neonates.

Decision Support for the Optimization of Provider Staffing for Hospital Emergency Departments with a Queue-Based Approach.

Deployment or distribution of valuable medical resources has emerged as an increasing challenge to hospital administrators and health policy makers. The hospital emergency department (HED) census and workload can be highly variable. Improvement of emergency services is an important stage in the development of the healthcare system and research on the optimal deployment of medical resources appears to be an important issue for HED long-term management. HED performance, in terms of patient flow and available resources, can be studied using the queue-based approach. The kernel point of this research is to approach the optimal cost on logistics using queuing theory. To model the proposed approach for a qualitative profile, a generic HED system is mapped into the M/M/R/N queue-based model, which assumes an R-server queuing system with Poisson arrivals, exponentially distributed service times and a system capacity of N. A comprehensive quantitative mathematical analysis on the cost pattern was done, while relevant simulations were also conducted to validate the proposed optimization model. The design illustration is presented in this paper to demonstrate the application scenario in a HED platform. Hence, the proposed approach provides a feasibly cost-oriented decision support framework to adapt a HED management requirement.

114 Emergency Department Factors Associated With Early Rapid Responses Activation After Admission

To assess the impact of emergency department (ED) and Hospital Census on the likelihood of the rapid response team being called to a patient's bedside within 24 hours (Early RR) of their admission from the ED. A retrospective review of all rapid responses and cardiac arrest codes in an academic tertiary care hospital for calendar year 2017. Those responses that occurred within 24 hours of admission from the ED were then identified. The hospital and ED census and bed availability data for 2017 was also reviewed and merged. A total of 21 factors were identified to be studied. Data was presented as mean (standard deviation) or median (interquartile range) for continuous variables and frequency (percentage) for categorical variables. Continuous variables were compared using a t-test or Wilcoxon sum rank test, as appropriate. Categorical data was analyzed using a chi-squared test or Fisher’s exact test, as appropriate. SAS Enterprise Guide 7.15 HF3 (SAS Institute, Inc, Cary, NC) was used to conduct the statistical analysis. A total of 581 rapid responses were documented. Of those, 94 were Early RRs called on 87 unique patients. Half occurred overnight(7P-7A), and half in daylight(7A-7P). Reasons reported for rapid response team activation during the Early RRs included 40 with respiratory, 27 with neurologic and 34 with cardiac. Nineteen were on non- internal medicine services. Only one of the Early RRs converted to a code and the total in-hospital mortality was 17%. During 2017, an early rapid response or an early code occurred on 80 (22%) and 6 (1.6%) days, respectively. On days when an early rapid response occurred, the total number of available beds in the morning (mean (SD): 29 (10)) is significantly higher (p-value = 0.0004) than on days where there were no early rapid responses called (mean (SD): 22 (9.5)). How census and flow affect patient outcomes is a complex question. Given previous literature showing increased mortality associated with increased ED boarding times and delayed ICU admission times, a full hospital is likely to stress resources such that more rapid responses occur. However, our research shows that as bed availability increases, so does the chance of rapid response. This may indicate that easy availability of ready floor beds allow patients to be inappropriately evaluated and dispositioned. This should be kept in mind as metrics for ED quality are developed and measured. As we expand working on this data set we hope to build on this initial analysis. We suspect that that likelihood of rapid response in correlation to time spent in the ED is likely U-shaped rather than linear.

Hospital, health, and community burden after oil refinery fires, Richmond, California 2007 and 2012

IntroductionEmergency Departments experience a significant census burst after disasters. The aim of this study is to describe patient presentations at Emergency Departments in Contra Costa County, California following chemical release incidents at an oil refinery in 2007 and 2012. Specific areas of focus include hospital and community burden with an emphasis on disease classes.MethodsSearching 4 weeks before through 4 weeks after each event, Emergency Department abstracts identified patients living in Contra Costa County and seeking care there or in neighboring Alameda County. City and ZIP-code of residence established proximity to the refinery. This provided the following contrast groups: Event (2007, 2012), time (before, after), location (bayside, rest of county), and within bayside, warned or not warned to shelter in place. Using the Multi-Level Clinical Classification Software, we classified primary health groups recorded 4 weeks before and after the events, then summarized the data, calculated rates, and made tables, graphs, and maps to highlight findings.ResultsNumber of visits meeting selection criteria totalled 105020 records. Visits increased modestly but statistically significantly after the 2007 incident. After the 2012 incident, two Emergency Departments took the brunt of the surge. Censuses increased from less than 600 a week each to respectively 5719 and 3072 the first week, with the greatest number 2 days post-event. It took 4 weeks for censuses to return to normal. The most common diagnosis groups that spiked were nervous/sensory, respiratory, circulatory, and injury. Bayside communities had statistically significant increases in residents seeking care. Specifically, visits of residents in warned communities nearest the refinery increased by a factor of 3.7 while visits of residents in other nearby un-warned communities increased by a factor of 1.5.ConclusionsThe 2012 Emergency Department census peaked in the first week and did not return to normal for 4 weeks. Diagnoses changed to reflect conditions associated with reactions to chemical exposures. Surrounding communities and nearby hospitals experienced significant emergent burdens. In addition to changes from such events in patient diagnoses and community burden, the discussion highlights the long-term implications of failures to require adequate monitoring and warning systems and failures of health planning.

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

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. This study describes the LWBS population at a multi-hospital academic health system. 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. 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 7days. Of this latter group, 11.5% were subsequently admitted for inpatient care, representing 0.068% of the total ED census during the study period. 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.

MP32: Mid-morning huddle: a coordinated team approach to facilitating disposition of older adults

Background: Older adults in the emergency department (ED) take an increasingly larger portion of resources, have increased length of stay and a higher likelihood of adverse outcomes. In many cases bad planning, multiple vague handovers, and lack of coordinated care exacerbate this problem. With the impending onset of our aging population this is a situation that can be expected to compound in complexity in the years to come. Aim Statement: We describe daily interdisciplinary review of ED patients over the age of 75 years (or otherwise identified as a challenging discharge) to discuss barriers and facilitators to discharge/disposition. We will use data to identify the impact of this particular population to ED flow. Measures &amp;amp; Design: This initiative developed from our participation in the Acute Care of the Elderly (ACE) Collaborative and applies Plan/Do/Study/Act (PDSA) cycles and run reports to compare: length of stay; Identification of Seniors at Risk (ISAR) screening tool; ED census, admission/discharge rates, bounce back rates, consulting services, and interdisciplinary participation. Evaluation/Results: The average daily census of our ED between the months of July-October of 2018 was over 211 patients/day, of which over 12% were patients 75 years and older. We conducted over 70 huddles, reviewing an average of 11 patients per day. The average length of stay for patients at the time of the huddle was 19 hours, significantly higher than the general emergency population. Next day admission and discharge rates were comparable, 44.8% and 43.1% respectively with the additional patients remaining in the ED with no disposition. Internal medicine was consulted on 30% of all huddle patients and 38.4% subsequently admitted. Thirty day bounce back rates for huddle patients discharged home was 29.3%. Around 60% of patients 75 and older were screened with the ISAR and 55.7% of these were positive (2 or more questions). Discussion/Impact: Older patients consume a disproportionate amount of ED resources. Daily interdisciplinary ‘geriatric huddles’ improved communication between members of the ED team and with consulting services. The huddles enhanced awareness of the unique demands that older adults place on the flow of the ED, and identified opportunities to enhance patient flow.

LO10: Associations between ED crowding metrics and 72h-hour ED re-visits: Which crowding metrics are most highly associated with patient-oriented adverse outcomes?

Introduction: Emergency Department (ED) crowding is a pervasive problem and is associated with adverse patient outcomes. Yet, there are no widely accepted, universal ED crowding metrics. The objective of this study is to identify ED crowding metrics with the strongest association to the risk of ED revisits within 72 hours, which is a patient-oriented adverse outcome. Methods: Crowding metrics, patient characteristics and outcomes were obtained from administrative data for all ED encounters from 2011-2014 for three adult EDs in Calgary, AB. The data were randomly divided into three partitions for cross-validation, and further divided by CTAS category 1, 2/3 and 4/5. Twenty unique ED crowding metrics were calculated and assigned to each patient seen on each calendar day or shift, to standardize the exposure. Logistic regression models were fitted with 72h ED revisit as the dependent variable, and an individual crowding metric along with a common list of confounders as independent variables. Adjusted odds ratios (OR) for the 72h return visits were obtained for each crowding metric. The strength of associations between 72h revisits and crowding metrics were compared using Akaike's Information Criterion and Akaike weights. Results: This analysis is based on 1,149,939 ED encounters. Across all CTAS groups, INPUT metrics (ED census, ED occupancy, waiting time, EMS offload delay, LWBS%) were only weakly associated with the risk of 72h re-visit. Among THROUGHPUT metrics, ED Length of Stay and MD Care Time had similar adjusted ORs for 72h ED re-visit (range 0.99-1.15). Akaike weights ranging from 0.3/1.00 to 0.4/1.00 indicate that both THROUGHPUT metrics are reasonable predictors of 72h ED re-visits. All OUTPUT metrics (boarding time, # of boarded patients, % of beds occupied by boarded patients, hospital occupancy) had statistically significant ORs for 72h ED re-visits. The median boarding time had the highest adjusted OR for 72h ED re-visit (adjusted OR 1.40, 95% CI 1.33-1.47) and highest Akaike weight (0.97/1.00) compared to all other OUTPUT metrics, indicating that median boarding time had the strongest association with 72h re-visits. Conclusion: ED THROUGHPUT and OUTPUT metrics had consistent associations with 72h ED re-visits, while INPUT metrics had little to no association with 72h re-visits. Median boarding time is the strongest predictor of 72h re-visits, indicating that this may be the most meaningful measure of ED crowding.

LO81: Interrater agreement and time it takes to assign a Canadian Triage and Acuity Scale score pre and post implementation of eCTAS

Introduction: In addition to its clinical utility, the Canadian Triage and Acuity Scale (CTAS) has become an administrative metric used by governments to estimate patient care requirements, emergency department (ED) funding and workload models. The electronic Canadian Triage and Acuity Scale (eCTAS) initiative aims to improve patient safety and quality of care by establishing an electronic triage decision support tool that standardizes that application of national triage guidelines across Ontario. The objective of this study was to evaluate triage times and score agreement in ED settings where eCTAS has been implemented. Methods: This was a prospective, observational study conducted in 7 hospital EDs, selected to represent a mix of triage processes (electronic vs. manual), documentation practices (electronic vs. paper), hospital types (rural, community and teaching) and patient volumes (annual ED census ranged from 38,000 to 136,000). An expert CTAS auditor observed on-duty triage nurses in the ED and assigned independent CTAS in real time. Research assistants not involved in the triage process independently recorded triage time. Interrater agreement was estimated using unweighted and quadratic-weighted kappa statistics with 95% confidence intervals (CIs). Results: 1491 (752 pre-eCTAS, 739 post-implementation) individual patient CTAS assessments were audited over 42 (21 pre-eCTAS, 21 post-implementation) seven-hour triage shifts. Exact modal agreement was achieved for 567 (75.4%) patients pre-eCTAS, compared to 685 (92.7%) patients triaged with eCTAS. Using the auditor's CTAS score as the reference standard, eCTAS significantly reduced the number of patients over-triaged (12.0% vs. 5.1%; Δ 6.9, 95% CI: 4.0, 9.7) and under-triaged (12.6% vs. 2.2%; Δ 10.4, 95% CI: 7.9, 13.2). Interrater agreement was higher with eCTAS (unweighted kappa 0.89 vs 0.63; quadratic-weighted kappa 0.91 vs. 0.71). Research assistants captured triage time for 3808 patients pre-eCTAS and 3489 post implementation of eCTAS. Median triage time was 312 seconds pre-eCTAS and 347 seconds with eCTAS (Δ 35 seconds, 95% CI: 29, 40 seconds). Conclusion: A standardized, electronic approach to performing CTAS assessments improves both clinical decision making and administrative data accuracy without substantially increasing triage time.

Patient Reported Experience in a Pediatric Emergency Department.

Objectives:To describe patient-reported experience in a pediatric emergency department (ED) and determine: (1) whether there are differences between the experience children report in comparison to their parents; and (2) whether factors such as time of visit (day, evening, night) and ED census are associated with patient experience.Methods:We conducted a prospective cross-sectional survey of children ≥8 years of age and the parents/guardians of children 0 to 17 years who visited a pediatric ED using a validated patient experience measure. The proportion of respondents for each question indicating that an aspect of their care could have been improved was calculated as problem scores for each survey item. The primary outcome was the overall problem scores for all respondents combined and for children and parents separately.Results:A total of 237 parents and 109 children completed surveys. The areas with the highest problem scores identified by both parents and children were: having enough to do while waiting to be seen (53.5; 95% confidence interval [CI]: 48.1, 58.8) and when to restart usual activities (34.7; 95% CI: 29.7, 40.0). There were meaningful differences in problem scores between children and parents including: doctors and nurses explaining what they were doing (parents: 19; 95% CI: 14.3, 24.7, child 40.4; 95% CI: 31.2, 50.2) and privacy when examined and treated (parents: 17.3; 95% CI: 12.8, 22.9, child: 36.7; 95% CI: 27.8, 46.5).Conclusion:There are differences in reported experience between children and their parents. This highlights the importance of including children when assessing patient experience in a pediatric setting.

10 Boarding Psychiatric Patients in the Emergency Department is Associated With Increased Emergency Department Violence

The national shortage of available inpatient psychiatric beds has led to many emergency departments (EDs) boarding patients on involuntary psychiatric holds for hours to days. Psychiatric holds absorb ED resources, consume beds that could be used for other acute care patients, and often delay adequate psychiatric treatment. Our study sought to determine if ED psychiatric holds also contribute to increased violence in the emergency department. A secondary objective was to determine if other variables, such as weather or proximity to the first day of the month (when financial assistance funds arrive), could predict ED violence. Staff hypothesized that more assaults occur toward the end of the month as some patients desire their holds revoked around the time of monthly financial support distributions. When an assault on staff occurs an overhead code is called and logged. We reviewed 1 year of these logs and compared them to logs showing the number of psychiatric holds in the department, the maximum temperature and occurrence of rain on a given day, whether a given day was in the first or last 10 days of a month, and the total ED census of a given day. The hospital is an urban level 2 academic trauma center and regional referral center in southern California that sees 120,000 patients per year. Between May 1, 2016 and April 30, 2017, 297 assaults resulting in an overhead code call occurred in the hospital with 57 of them in the ED. 94% of the ED assaults occurred during days with 4 or more patients on a hold, compared with 6% on days with 3 or fewer holding patients (p<0.04). A logistic regression analysis that included the number of holds (4 or greater versus less than 4), the maximum daily temperature, the total ED census, whether rain occurred on a given day, and the 10-day period of the month (early versus late) showed 2 significant associations. Having more psychiatric holds (4 or more) predicted assault, even with total ED census controlled (p=0.02), and more assaults occurred in the last 10 days of the month than the first 10 (p=0.03). Weather patterns were not associated with assaults. Increased boarding of psychiatric patients in the ED is associated with increased assaultive behavior, demonstrating another adverse impact of psychiatric patient boarding. Weather failed to predict assaults but as predicted more assaults occurred toward the end of the month.

329 Using Digital Health to Enhance Medical Screening Exam in the Emergency Department

Surges in patient arrivals put stress on emergency department (ED) resources contributing to increased time-to-provider, increased walk-outs and decreased patient satisfaction. A medical screening exam (MSE) performed by a Provider-in-Triage (PIT) has been shown to both aid in early identification of seriously ill patients as well as those with non-critical illness. PIT assessments are frequently encumbered by interruptions as the provider navigates through the physical space of the ED. Research suggests that so-called “task switching” causes disruption in the primary task and may contribute to error. We sought to enhance our MSE process by incorporating digital health / telemedicine during peak hours. Specifically, we compared the Provider-In-Triage (PIT) model to a remote Telemedicine medical screening exam (TeleMSE) which had the enhanced capability to quickly navigate between 3 patient triage stations without interruption in work flow. Our hypothesis was that TeleMSE would improve time-to-provider and patient satisfaction while decreasing walk-outs. We conducted a retrospective observational study at a single urban academic tertiary care center, with an annual ED census of 96,000 visits. All 3 processes (PIT MSE, single-station TeleMSE and multi-station TeleMSE) were launched sequentially. The following metrics were analyzed: 1) time-to-provider (initial and full) and 2) total number of patients screened per hour. Initial time-to-provider was defined as the time to the PIT MSE or TeleMSE encounter during which the patients had a brief assessment done by a provider who placed necessary orders to initiate care. Full time-to-provider was defined as the time patients saw a local provider who determined the need for further work-up and disposition. Data on ESI (Estimated Severity Index) level, sex, and age were collected to assess for potential confounding. Data were abstracted from March 1, 2017-May 31, 2017; June 1, 2017-September 14, 2017 and September 15, 2017-December 10, 2017 for PIT MSE, singles station TeleMSE and multi-station TeleMSE respectively. PIT had an average of 3.7 patients per hour MSE encounter, with a median time-to-provider initial evaluation at 21 minutes and a full evaluation at 61.8 minutes. Single-station TeleMSE performed an average of 3.12 patients per hour, with a median time-to-provider initial evaluation at 10.8 minutes and a full evaluation at 30.6 minutes. Lastly, the multi-station TeleMSE model performed 4.8 patients per hour, with an initial time-to-provider evaluation of 15 minutes and a full evaluation at 48.6 minutes. Walk out rates were 4.3%, 4.3%, and 4.1% for PIT, single-station tele MSE and multi-station TeleMSE respectively. Initial results suggest that the TeleMSE process is associated with decreased time-to-provider in comparison to the PIT model. This may be due to decreased interruptions and streamlined work flow. With remote access it also allows for flexible staffing increases during surge and peak times. Multi-station TeleMSE was associated with increased rate of patients seen per hour in comparison to single station TeleMSE. The TeleMSE model has the potential to positively impact the Medical Screening Exam process and patient care.

351 Resuscitation Resident Impact on Patients With Severe Sepsis and Septic Shock

A required clinical rotation was developed at our institution to augment resident training in resuscitation with focus on critically ill patients in the emergency department (ED). Given their involvement, residents on this rotation may help expedite the care of these patients. The objective of this study was to compare sepsis metrics and clinical outcome between patients with resuscitation resident involved in care and those without. This retrospective study was conducted at a single site tertiary care center with an ED census of 130,000 visits annually. Data was collected from 1/1/2015 to 12/31/2016 via electronic medical record query. Patients greater than 17 years of age and admission diagnosis of severe sepsis and septic shock were included. Patients were dichotomized by whether or not there was resuscitation resident involvement. ED length of stay, time to initial lactic acid draw, lactic acid value, time to bolus fluid initiation and whether 30 cc/kg bolus was administered, time to antibiotic initiation, medical intensive care unit (ICU) admission and 30 day mortality were compared between the 2 groups. Fisher's Exact tests were used to analyze the variables. 4746 patients were admitted, 917 of which were placed in the medical ICU. 101 total admitted patients had resuscitation resident participate in their care. Time to initial lactic acid draw was shorter (0.53 versus 1.05 hours; p<0.0001) and mean lactic acid level was higher (2.5 versus 1.8; p<0.0001) in the cohort with the resuscitation resident involved. More patients received a 30 cc/kg bolus with resuscitation resident involvement (15.0% versus 8.7%), however this was not statistically significant (p=0.09). Resuscitation resident involvement was also associated with more medical ICU (45.5% versus 18.8%; p<0.0001) admissions and a higher 30 day mortality (29.7% versus 14.9% ; p<0.0001). All other variables were not statistically significant. On subset analysis of the patients admitted to the medical ICU patient population, there was no difference in variables between patients with resuscitation resident involvement and those without. Severe sepsis and septic shock with resuscitation resident involvement demonstrated statistically significant benefit in time to initial lactic acid draw. One limitation of the study is the unbalanced cohorts. This rotation offers potential to improve care of ED sepsis patients and increase resident exposure to greater percentage of septic ICU admissions.

The Impact of Behavioral Health Patients on a Pediatric Emergency Department's Length of Stay and Left Without Being Seen.

Emergency department (ED) boarding of admitted patients negatively impacts ED length of stay (LOS). Behavioral health (BH) patients are often challenging to safely discharge. We examined the association between daily BH census and non-BH LOS and left without being seen (LWBS) rates. Retrospective analysis of BH and non-BH patients at a high-volume tertiary care pediatric ED from December 2014 to June 2016 examined the association between BH patients and non-BH LOS and LWBS rates. Behavioral health patients were identified by presence of social work assessment and BH chief complaint and/or final diagnosis. Data were analyzed using 1-sample test of proportions, Student t test, Spearman and Pearson correlations, logistic regression, and odds ratios with 95% confidence intervals. A total of 143,141 patients were seen, 3% (n = 4351) for BH presentations. Median LOS for discharged non-BH patients was 128 minutes compared with 446 minutes for BH patients. Daily LOS and bed hold hours were significantly longer for BH than for non-BH patients (P < 0.0001 for each analysis). After adjusting for ED census, daily BH census was significantly associated with increasing LWBS rates and non-BH LOS. Behavioral health census and bed hold hours were significantly associated with increased LOS and LWBS rates and with our inability to meet desired LOS and LWBS rates. These associations support the existence of a threshold where the ED has reached capacity and is no longer able to absorb BH patients. Improving BH facility access may help improve overall pediatric ED patient care.

Emergency department utilization by a jail population

BackgroundIncarcerated individuals represent a significant proportion of the US population and face unique healthcare challenges. Scarce articles have been published about emergency department (ED) care of these patients. We studied the ED visits from one urban jail to better describe this population. MethodsA cohort study design was used, identifying patients who were sent to the ED from a city jail in 2015. Demographics, triage information, length of stay, number of studies, billing codes, diagnoses, and disposition data were collected. These were compared to the overall ED patient population in the same year. Results868 ED visits by jail patients occurred, representing 1.3% of the ED census. Compared to the general population, incarcerated patients were younger (32.1 years vs. 44.0 years, p < .01), healthier based on Elixhauser comorbidity scores (0.71 vs. 0.98, p < .01), and had lower admission rates (11.29% vs. 21.54%, p < .01). An abnormal vital sign was noted in 25% of incarcerated patients. Laboratory (61% vs. 57%, p < .02) and radiologic (63% vs 45%, p < .001) testing was more frequent for inmates and length of stay was longer (271 vs. 225 min, p < .01). ConclusionED visits from jail were common, involving a relatively young and healthy population with a low incidence of abnormal vital signs and admission. Given the high costs associated with ED care and the medical resources available at some jails, further study should evaluate if increased jail medical capabilities could improve care and decrease costs by decreasing ED visits.

P130: Cumulative daily boarding time: a new way to measure emergency department congestion and hospital-wide flow

Introduction: Bed boarding of admitted patients in the Emergency Department (ED) is one of the major contributors to ED overcrowding, and an indicator of hospital-wide deficiencies in capacity and flow. Most indicators of ED overcrowding have measured either counts or percentages of patient subgroups (e.g. number/percentage of patients waiting in triage or number/percentage of admitted patients as compared to full ED census), or specific process time intervals related to patient movement through the hospital (e.g. Physician to Initial Assessment (PIA) time or total ED Length of Stay (EDLOS)). We sought to 1) devise an alternative measure of ED overcrowding that captured the dynamic and disproportionate resource utilization of admitted versus non-admitted patients in the ED, and to 2) determine the association of this measure with selected ED quality metrics for non-admitted patients. Methods: We conducted a retrospective multi-centre observational study at three very high-volume community hospitals in the Greater Toronto Area. Data on all patients visiting the ED during the period between January 1, 2015 and December 31, 2016 were included in the study. We calculated the total daily cumulative boarding time - or time to bed (TTB) - for each day of the study duration. The daily cumulative TTB was calculated as the time from decision to admit to transfer from the ED for all admitted patients within a 24-hour period. We conducted linear regression analysis to determine the association between our measured daily cumulative TTB and daily median and 90th percentile PIA and EDLOS times for non-admitted patients. Results: Preliminary results for 2015 indicate a total cumulative TTB time ranging from 50,973 hours to 191,093 patient-hours for the year, with daily mean cumulative TTB ranging from 140 524 patient-hours/day among the three hospitals. In all three hospitals, there was a statistically significant (p&lt;0.01) positive association between daily cumulative TTB and both median and 90th percentile PIA times for all patients, and median EDLOS times for non-admitted CTAS 1 -3 patients. There was a statistically significant (p&lt;0.05) positive association between daily cumulative TTB and 90th percentile EDLOS for non-admitted CTAS 1-3 patients in two of the three hospitals, with the third hospital showing a positive but non-significant association. Conclusion: Bed boarding constitutes a significant resource cost for EDs, and has a negative impact on timeliness of ED care for the general ED population, particularly more complex (CTAS 1-3) non-admitted patients.