SISTER (system implementation of select transfers in emergency room) model to reduce ED boarding.

OBJECTIVE: This study describes a novel transfer model implemented between an academic, level 1 trauma center (Hospital A) and a nearby affiliate community hospital (Hospital B). Primary outcome is change in boarding hours and percentage of boarders in the Hospital A emergency department. Secondary objectives of this study include how improved flow in the emergency department to reduce boarding improves length of stay, prevents patients from escalating to more acute acuity levels of care, reduces patient morbidity and mortality and therefore improves health care costs as well. METHODS: A retrospective chart review was conducted over a consecutive 14-months period of all patients that presented to main hospital emergency department who were transferred to the Hospital B for inpatient admission. This included analysis of patient cohort characteristics, hospital LOS, return rate to the Hospital A (boomerang), rates of against medical advice (AMA) dispositions, post-discharge recidivism, in addition to enterprise data on total number of boarders, percent of boarders, and total boarding hours. RESULTS: There was a total of 718 transfer encounters during the study period. Percent boarding decreased from 70.6% in the pre-period to 63.8% in the post-period (p < 0.001). Total boarding hours decreased at both the main hospital and the sister hospital with this transfer process. The median length of stay at the sister hospital was 74 h, with 9 upgrades to ICU admissions. Five patients were dispositioned back to the hospital A after admission to hospital B. CONCLUSION: A distributive model was useful in transferring admissions within a healthcare system, reducing number of boarders, percent of boarders, and boarding hours in Hospital A emergency department. Furthermore, the Hospital B was an appropriate location for transfers, based on the low number of ICU transfers and dispositions back to the main hospital.

A Novel Module Based Method of Teaching Electrocardiogram Interpretation for Emergency Medicine Residents.

Audience: This online learning module is designed for PGY 1-3 emergency medicine (EM) residents. Introduction: Interpretation of the 12-lead electrocardiogram (ECG) is an essential skill for EM residents. The traditional approach to ECG interpretation in medical school is primarily didactic, teaching: "rate, rhythm, axis," etc. Throughout residency, EM residents continue to receive lectures and practical ECG teaching to independently interpret ECGs with accuracy and efficiency. In addition to basic rhythm interpretation, physicians must be able to identify cardiac ischemia, abnormal rhythms, and subtle ECG findings that could herald sudden death.1 Life-threatening diagnoses such as digitalis toxicity or hyperkalemia can be made promptly through ECG evaluation and catastrophic if missed. If correctly diagnosed through ECG, many channelopathies can be treated and cardiac events can be prevented.2,3 Lecture-based learning is a necessary part of medical education, but there is a need to supplement the traditional teaching approach with online learning modules. Online learning modules provide learners with an accessible and efficient tool that allows them to improve their ECG skills on their own time. Educational Objectives: After completion of the module learners should be able to: 1) correctly recognize and identify ECG abnormalities including but not limited to abnormal or absent P waves, widened QRS intervals, ST elevations, abnormal QT intervals, and dysrhythmias that can lead to sudden cardiac death; and 2) synthesize findings into a succinct but accurate interpretation of the ECG findings. Educational Methods: An online module was developed using Articulate 360 and was implemented with EM residents. The module covers common ECG findings seen in the emergency department including ischemia, atrioventricular blocks, and bundle branch blocks. The module uniquely emphasizes ECG findings of arrythmias that could lead to sudden cardiac death and highlights that diagnosing sudden cardiac death syndromes relies on both clinical presentation and specific ECG findings. Online modules have proven to be as effective as lecture-based learning at improving ECG interpretation among healthcare professionals and are convenient and easily accessible to the busy EM resident.4,5 Additionally, the module is self-paced, can be completed at any time, and includes elements of active learning by incorporating knowledge checks throughout. This allows learners in real time to see where individualized improvement is needed. The ease of embedment of self-paced questions into the module is one of the salient reasons why module-based learning can be superior to lecture-based learning. This allows for real time retrieval practice, feedback, and repetition, all of which can be powerful and effective tools for learning.6. Research Methods: This module was offered at a single academic institution with a 3-year residency program. The investigation was reviewed and approved for exemption by the Institutional Review Board of Sydney Kimmel Medical College. The module was evaluated using survey data; before the module was disseminated, residents were given a pre-module survey. The survey was used to evaluate the methods residents used to interpret ECGs prior to completion of the module and to evaluate their baseline confidence in ECG interpretation. The residents were then given access to the module and had two weeks to complete it. After the two-week period, the post-module survey was used to evaluate resident satisfaction with the delivery of the module, the methods residents used to interpret ECGs after the module, and resident confidence in ECG interpretation. The objective efficacy of the educational content in the module was assessed using a pre- and post-module assessment. The assessments consisted of 15 ECGs.Residents were asked to provide a one-sentence interpretation for each of the 15 ECGs and the final answers were based on interpretation by an electrophysiologist. Results: A group of 37 EM residents had two weeks to complete the module between pre- and post-tests. There was an 18.2% absolute increase in the mean percent correct after the module, a 42.5% relative increase from pre-test (t= -8.0, p < 0.001). Subjective data demonstrated that after completing the module, residents utilized the novel approach, were more confident in interpreting ECGs, and would use the module as a resource in the future. Discussion: Most participants were not confident in their ability to interpret an ECG prior to completing the module, despite most of the participants having ECG training in the six months prior to the study. Almost all the participants reported using "rate, rhythm, axis" as their method of ECG interpretation. Even with recent training, and an understanding of "rate, rhythm, axis," there was a very low accuracy on the pre-test and lack of perceived baseline confidence in this skill. These findings highlight the need for a concise, effective supplemental ECG tool that can be incorporated into residency program curricula.The online learning module was effective at increasing confidence of ECG interpretation skills in residents as well as increasing accuracy of interpretation. Overall, participants were satisfied with the module as a resource for practicing their ECG interpretation, and most participants reported that they would use the module in the future as a reference. Implementation of the module as an additional resource in resident education is very simple. It can be accessed through any device that has internet and can be completed in a short period of time. Additionally, most experienced ECG readers will speak about "pattern recognition" as an important tool in ECG interpretation. This ability goes above and beyond the "rate, rhythm, axis" approach, but is acquired over time, often after many years of ECG interpretation. It is possible that the modular method may accelerate such pattern recognition abilities. Topics: Electrocardiogram, online module, sudden cardiac death, ischemia.

The impact of COVID-19 on the sensitivity of D-dimer for pulmonary embolism.

OBJECTIVE: This study seeks to evaluate the test characteristics of D-dimer for pulmonary embolism (PE) in patients with a concurrent diagnosis of COVID-19. We hypothesized that the sensitivity of D-dimer for PE at current institutional cut points would be similar to those without COVID-19. METHODS: This is a multicenter retrospective observational cohort study across five urban and suburban EDs in the same health care system. The electronic health record was queried for all computed tomography pulmonary angiography (CTPA) studies from December 1, 2019, to October 22, 2020. All ED patients who underwent CTPA had D-dimer and COVID-19 testing completed in a single encounter were included in the study. Baseline demographics were obtained. Test characteristics of D-dimer for PE were calculated for patients with and without COVID-19. Additionally, receiver operator characteristics (ROC) curves were constructed for two different D-dimer assays. RESULTS: There were 1158 patient encounters that met criteria for analysis. Performance of D-dimer testing for PE was similar between COVID-19-positive and -negative patients. In COVID-19-positive patients, the sensitivity was 100% (95% confidence interval [CI] = 87.6%-100%), specificity was 11.9% (95% CI = 7.9%-17.1%), and negative predictive value (NPV) was 100%. In COVID-19-negative patients the sensitivity was 97.6% (95% CI = 91.5%-99.7%), specificity was 14.4% (95% CI = 12.1%-17%), and NPV was 98.3% (95% CI = 93.8%-99.6%). For assay 1 the area under the curve (AUC) for COVID-19-positive patients was 0.76 (95% CI = 0.68-0.83), and for COVID-19-negative patients, 0.73 (95% CI = 0.69-0.77). For assay 2, AUC for COVID-19-positive patients was 0.85 (95% CI = 0.77-0.92), and for COVID-19-negative patients, 0.80 (95% CI = 0.77-0.84). Inspection of the ROC curve for assay 1 revealed that 100% sensitivity was maintained up to a threshold of 0.67 FEU (fibrinogen equivalent units; from 0.50 FEU) with an increase in specificity to 29% (from 18.7%), and for assay 2, 100% sensitivity was maintained up to a threshold of 662 D-dimer units (DDU; from 230 DDU) with an increased specificity to 59% (from 6.1%). CONCLUSION: Results from this multicenter retrospective study did not find a significant difference in sensitivity of D-dimer for PE due to concomitant COVID-19 infection. Further study is required to determine if PE can safely be excluded based on D-dimer results alone in patients with suspected or proven COVID-19 or if adjusted D-dimer levels could have a role in management.