Comparing the Safety and Efficacy of a Rapid High-Sensitivity Cardiac Troponin I Protocol Between Hospital-Based and Free-Standing Emergency Departments

Study Objectives: Current high sensitivity cardiac troponin I (hs-cTnI) research has been conducted almost exclusively in hospital-based emergency department (HBED) settings and the translation of these protocols into free-standing emergency departments (FSED) has yet to be explored. This study compared the safety and efficacy of applying a rapid-rule out protocol using hs-cTnI for exclusion of acute myocardial infarction (AMI) in HBEDs and FSEDs. Methods: This was a secondary analysis of a randomized trial of patients evaluated for possible AMI in 9 emergency departments (ED) from July 2020 through March 2021. The trial arms included a new 0/1-hour rapid protocol using hs-cTnI versus standard care, which used a 0/3-hour protocol without reporting hs-cTnI values below the 99th percentile. The primary outcome was safe ED discharge, defined as discharge with no death or AMI within 30-days. Analysis included a mixed-effect model adjusting for demographic variables. Results: There was a statistically significant difference in safe discharges from FSEDs when comparing the standard care arm (86.2%) to the rapid rule-out protocol (95.1%). There was a statistically significant reduction in FSED length of stay with application of a rapid rule-out protocol at 3.43 hours vs. 3.97 hours using standard care. The percentage of patients who ruled-out with their initial hs-cTnI (\u3c4 ng/L) at FSEDs (74%) was also significantly larger when compared to HBEDs (54%). Conclusion: Implementation of a hs-cTnI rapid 0/1-hour protocol to evaluate for AMI in FSEDs is feasible and had greater impact on safe ED discharge and length of stay compared to HBEDs

A Comparison of Univariate and Multivariate Forecasting Models Predicting Emergency Department Patient Arrivals during the COVID-19 Pandemic

The COVID-19 pandemic has heightened the existing concern about the uncertainty surrounding patient arrival and the overutilization of resources in emergency departments (EDs). The prediction of variations in patient arrivals is vital for managing limited healthcare resources and facilitating data-driven resource planning. The objective of this study was to forecast ED patient arrivals during a pandemic over different time horizons. A secondary objective was to compare the performance of different forecasting models in predicting ED patient arrivals. We included all ED patient encounters at an urban teaching hospital between January 2019 and December 2020. We divided the data into training and testing datasets and applied univariate and multivariable forecasting models to predict daily ED visits. The influence of COVID-19 lockdown and climatic factors were included in the multivariable models. The model evaluation consisted of the root mean square error (RMSE) and mean absolute error (MAE) over different forecasting horizons. Our exploratory analysis illustrated that monthly and weekly patterns impact daily demand for care. The Holt–Winters approach outperformed all other univariate and multivariable forecasting models for short-term predictions, while the Long Short-Term Memory approach performed best in extended predictions. The developed forecasting models are able to accurately predict ED patient arrivals and peaks during a surge when tested on two years of data from a high-volume urban ED. These short-and long-term prediction models can potentially enhance ED and hospital resource planning

Three-dimensional printed model for cricothyroidotomy training

Intro/Background: Each year second year emergency medicine residents complete a \u27Difficult Airway Course\u27 as part of their medical training. This involves performing surgical cricothyrotomy on pig tracheas which poorly resemble human subjects and are costly. Purpose/Objective: In an effort to improve proficiency and training for a potentially life saving emergency procedure, a 3D printed model of a human trachea was compared to that of a pig trachea to evaluate proficiency, user acceptance, and cost-comparison to that of the standard pig tracheas among second year emergency residents. It is anticipated that this will potentially provide safer patient care by emergency physicians at a lower price. Methods: Residents were divided into two groups - Group 1 performing pig trachea followed by 3D model and Group 2 performing 3D model followed by pig trachea. Data was collected using pre and post procedure questionnaire\u27s and recording time to successful cricothyrotomy. Overall user acceptance with regards to resemblance of human trachea, number of attempts, and time to successful cricothyrotomy were compared between Group 1 and Group 2. Outcomes: Difference in time between 3D and Pig model was 34.9 ±31 sec, 95% CI -3.0 to 72.9, p=0.07 (meaning the 3D model took an additional 34.9 sec on average). Clinicians rated the resemblance higher for the 3D model, mean difference 0.62 (95% CI 0.22 - 1.01), p=0.005. Summary: Cricothyrotomy is a rare but lifesaving procedure that must be taught to emergency medicine residents. Current methods rely on pig trachea models to simulate this procedure. We have developed a 3D printed model as an alternative for simulation. There was a statistically significant higher resemblance of the 3D model versus the standard pig model when compared to the human trachea. The longer procedure times recorded for the 3D model may reflect the procedural complexity inherit to cricothyrotomies. Future studies of this life saving procedure can be validated and compared to that of more experienced physicians and their respective skillset when it comes to cricothyrotomies. The ability to reuse the 3D printed model will provide longevity and consistent training among residents at a lower price point. This 3D model can be demonstrated at a table top demonstration at SAEM

Diagnostic Imaging Utilization in the Emergency Department: Recent Trends in Volume and Radiology Work Relative Value Units

PURPOSE: The aim of this study was to quantify and characterize the recent trend in emergency department (ED) imaging volumes and radiology work relative value units (wRVUs) at level I and level III trauma centers. METHODS: Total annual diagnostic radiology imaging volumes and wRVUs were obtained from level I and level III trauma centers from January 2014 to December 2021. Imaging volumes were analyzed by modality type, examination code, and location. Total annual patient ED encounters (EDEs), annual weighted Emergency Severity Index, and patient admissions from the ED were obtained. Data were analyzed using annual imaging volume or wRVUs per EDE, and percentage change was calculated. RESULTS: At the level I trauma center, imaging volumes per EDE increased for chest radiography (5.5%), CT (35.5%), and MRI (56.3%) and decreased for ultrasound (-5.9%) from 2014 to 2021. Imaging volumes per EDE increased for ultrasound (10.4%), CT (74.6%), and MRI (2.0%) and decreased for chest radiography (-4.4%) at the level III trauma center over the same 8-year period. Total wRVUs per EDE increased at both the level I (34.9%) and level III (76.6%) trauma centers over the study period. CONCLUSIONS: ED imaging utilization increased over the 8-year study period at both level I and level III trauma centers, with an increase in total wRVUs per EDE. There was a disproportionate increased utilization of advanced imaging, such as CT, over time. ED utilization trends suggest that there will be a continued increase in demand for advanced imaging interpretation, including at lower acuity hospitals, so radiology departments should prepare for this increased work demand

MINDtime: Keeping an Eye on the Clock

Background: During an ischemic stroke, time is brain. Patients arriving within 4.5 hours of Last Known Well (LKW) are eligible for treatment with intravenous tissue plasminogen activator (t-PA) based on their respective inclusion/exclusion criteria. It is well established that the benefits of IV t-PA are time-dependent, thus published guidelines recommend a door-to-needle treatment time of 60 minutes. More recently, there has been a nationwide push to treat 50% of t-PA patients within 45 minutes. Numerous steps have been implemented to facilitate rapid decision making and treatment; however, challenges remain. At our Comprehensive Stroke Center, we proposed a simple and non-invasive tool to help expedite the door-to-needle times by attaching a stopwatch to the t-PA eligible patient\u27s bed in an effort to remind all members of the care team that “the clock was ticking.” Methods: Data was collected on all patients who received IV t-PA from 5/29/17 - 11/27/17. Dates ending in an odd number were designated the intervention group, where eligible patients would have a large digital clock attached to their bed that counted upwards from their arrival time. The even number days were the control group, where patients would be assessed and treated based on established hospital protocol. The outcome was measured in minutes. Results: A total of 68 patients were treated with IV t-PA during the pre-specified time period. All patients that met either the 3 hour or 4.5 hour IV t-PA criteria were included in the study. There were 39 patients (50%) treated during the “odd” days with the stopwatch present. The median door-to-needle time was 52 minutes [IQR 43 - 72] for this cohort, while the median door-to-needle time was 49 minutes [IQR 42 - 70] for the other group (p = 0.79). Conclusion: Our study did not demonstrate a significant difference in door-to-needle time between the two groups. We believe there are some possible reasons for these findings. During our study period, there were several simultaneous improvement processes occurring, which could have diluted our study results. We believe that the concept of displaying time to the members of the care team can assist in expediting door-to-needle times. This resource-limited and relatively simple intervention may be attractive to Acute Stroke Ready Hospitals (ASRHs) and some Primary Stroke Centers (PSCs)

Prediction of emergency department patient disposition decision for proactive resource allocation for admission.

We investigate the capability of information from electronic health records of an emergency department (ED) to predict patient disposition decisions for reducing boarding delays through the proactive initiation of admission processes (e.g., inpatient bed requests, transport, etc.). We model the process of ED disposition decision prediction as a hierarchical multiclass classification while dealing with the progressive accrual of clinical information throughout the ED caregiving process. Multinomial logistic regression as well as machine learning models are built for carrying out the predictions. Utilizing results from just the first set of ED laboratory tests along with other prior information gathered for each patient (2.5 h ahead of the actual disposition decision on average), our model predicts disposition decisions with positive predictive values of 55.4%, 45.1%, 56.9%, and 47.5%, while controlling false positive rates (1.4%, 1.0%, 4.3%, and 1.4%), with AUC values of 0.97, 0.95, 0.89, and 0.84 for the four admission (minor) classes, i.e., intensive care unit (3.6% of the testing samples), telemetry unit (2.2%), general practice unit (11.9%), and observation unit (6.6%) classes, respectively. Moreover, patients destined to intensive care unit present a more drastic increment in prediction quality at triage than others. Disposition decision classification models can provide more actionable information than a binary admission vs. discharge prediction model for the proactive initiation of admission processes for ED patients. Observing the distinct trajectories of information accrual and prediction quality evolvement for ED patients destined to different types of units, proactive coordination strategies should be tailored accordingly for each destination unit

Emergency Department Triage Blood Glucose Levels: Outcomes Implications in Patients with Severe Sepsis and Septic Shock

Background: Patients with severe sepsis and septic shock often present with a variety of organ dysfunctions including metabolic derangements. The appropriate metabolic stress response in sepsis includes release of glucose leading to stress-hyperglycemia and is commonly seen in these Emergency Department (ED) patients. Many studies focus on metabolic glucose abnormalities and its effect on outcomes at the time of Intensive Care Unit (ICU) admission. Hyperglycemia present on ICU admission has been associated with adverse outcomes irrespective of the presence or absence of diabetes mellitus. Methods: We analyzed our ED quality sepsis database in concern to triage glucose levels and associated 30 day mortality from August 2015 to October 2016 to determine adjustments in active glucose monitoring in the ED. Results: We identified 683 patients with severe sepsis (N=399) and septic shock (N=284). Average glucose levels at the 1stED laboratory evaluation was 172 mg/ dL (SD=149). Patients with septic shock had on average lower glucose levels (170 mg/dL) than patients with severe sepsis (174 mg/dL). Sepsis survivors had higher triage glucose (176 mg/dL, N=525) than non-survivors (159 mg/dL, N=157). When stratifying patients by glucose levels, we found that patients with glucose levels less than 70 mg/dL at ED triage had the highest mortality. The incidence of glucose of ≤ 70 mg/ dL was 7% (N=49) for all patients with severe sepsis and septic shock combined. The mortality in this group was 44% (21/49) which was significantly (p=0.001) higher than mortality in patients with higher glucose levels (136/634, 21%). In patients with glucose levels of ≥ 180 mg/dL the mortality was not different (35/177, 26%, p=0.9) when compared to patients with glucose levels ranging from 70-180 mg/dL. Conclusion: Glucose monitoring for patients with sepsis in the ED aids recognition of correctable metabolic derangements early in management. In the ED, the metabolic-stress response to sepsis is commonly stress-hyperglycemia, but hypoglycemia can also occur in the early phases of sepsis. Hypoglycemia at ED triage has a higher than expected mortality and needs to be recognized and treated accordingly

Adherence to Canadian computed tomography head rule is associated with improved hospital performance metrics

Background and Objectives: The Michigan Emergency Department Improvement Collaborative (MEDIC) was established in 2015 as a quality improvement network of unaffiliated hospitals linked by a clinical data registry within a structured implementation and incentive program. One of the network\u27s objectives is to lower unnecessary computed tomography for adult minor head injuries using the Canadian CT Head Rule (CCHR) which has previously been shown to safely reduce the number of Head CT studies. We examined whether adherence to the CCHR was associated with significant decreases in length of stay (LOS), number of total imaging studies, and rates of hospital admission. We also examined return visit data to assure no significant difference in outcomes. Methods: Data from the MEDIC registry on ED visits from 6/1/2016-9/30/2019 was used to identify adult patients with a negative CCHR by chart review and classified into two populations: visits where providers either followed the recommendations of the rule and did not order HCT, or violated the recommendations of the rule by ordering HCT. Comparison populations were obtained through propensity score-matching on age, gender, insurance type, triage acuity score, time and day of presentation, and hospital of presentation. Covariate balance was validated through calculation of absolute standardized mean differences. Average LOS, number of imaging studies, admission rates, rate of return visits within 7 days, and whether HCT was obtained or severe head injury detected upon return were examined within these populations. Results: In the patient populations where providers adhered to the recommendations not to obtain CT in patients with low risk (7,502), the LOS was lower (3.01 vs 4.25, p\u3c0.0001), the mean number of imaging studies obtained was fewer (0.96 vs 3.26, p\u3c0.0001), and the hospital admission rate was lower (1.71 vs 3.57, p\u3c0.0001). No statistically significant difference was observed with respect to rate of return visit within 7 days (6.48 vs 5.93, p = 0.1626) irrespective of whether the return visit resulted in HCT (0.96 vs 0.69, p=0.0675) or whether severe head injury was identified (0.01 vs 0.00, p=0.3864). Conclusion: Adherence to the recommendations of the CCHR is associated with lower LOS, fewer overall imaging studies, and decreased hospital admission rates without evident increase in return visits or missed significant findings

Patient Satisfaction and Likelihood to Recommend Between Academic Teaching and Community Emergency Departments

Background and Objectives: Patient surveys are a common means of collecting information on patient satisfaction and likelihood to recommend, both of which are important barometers of a patient’s emergency department (ED) experience. We sought to assess the impact of treatment in an academic teaching vs. community ED on a patient’s likelihood to recommend. Methods: We performed a retrospective analysis of all completed patient surveys (Press Ganey) of discharged patients across 5 EDs within an integrated health system from January 2019 through June 2020. Two EDs were at academic teaching hospitals with EM residencies and 3 were community EDs. Patient responses were dichotomized to “favorable” or “not favorable”, wherein “favorable” denoted a likelihood to recommend of 4 or 5 on a 5-point Likert scale. Operational time metrics were assessed in 10-minute intervals. The analysis included univariate comparisons and generalized linear modeling to adjust for the site, demographic, and operational metrics. We report adjusted odds ratios (aOR) with 95% confidence intervals (95% CI). Results: There were 7,694 surveys completed. The majority of respondents were female (64.4%), \u3e50 years (68.2%), and presented to a teaching hospital (54.0%). In univariate analysis, male sex, white race, older age, treatment in a community ED, shorter time to a room, and shorter overall ED length of stay were associated with a higher likelihood of a favorable survey response. In adjusted analysis, the odds of a favorable response were higher in males (aOR 1.25, 95% CI 1.12 - 1.39), white patients (aOR 1.16, 95% CI 1.02 -1.32), and older adults (aOR 1.02, 95% CI 1.01-1.02 with each year of increasing age). Time metrics such as longer overall length of stay (aOR 0.95, 95% CI 0.93-0.97) and longer time to be placed in a room (aOR 0.95, 95% CI 0.93 -0.97) were associated with lower odds of a favorable response. Patients managed at an academic teaching site had significantly lower odds of a favorable response compared to community EDs (aOR 0.54, 95% CI 0.48 – 0.61) in adjusted analysis. Factors not associated with a favorable response included ethnicity, emergency severity index, mode of arrival, arrival time, and arrival day of the week. Conclusion: When adjusted for operational and demographic metrics, academic teaching sites had lower associated rates of a favorable response from patient satisfaction surveys

IIT Sustainability Branding (Semester Unknown) IPRO 311: IITSustainableBrandingIPRO311MidTermPresentationSp09

This is a continuing IPRO with the overall aim of improving and enhancing the image of Illinois Institute of Technology, both as an institution and a physical campus, in regards to sustainability and “green” practices. To that end, the current semester is focused on several design projects based on concepts generated in the previous semesters along with input from the current semester to enhance a new “green” campus. We will also be providing information on how IIT is currently acting in a sustainable fashion and how students on campus can contribute to our image as a sustainable campusDeliverable