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Background Emergency department (ED) crowding is a recognized issue and it has been suggested that it can affect clinician decision-making. Objectives Our objective was to determine whether ED census was associated with changes in triage or disposition decisions made by ED nurses and physicians. Methods We performed a retrospective study using one year of data obtained from a US academic center ED (65,065 patient encounters after cleaning). Using a cumulative logit model, we investigated the association between a patient's acuity group (low, medium, and high) and ED census at triage time. We also used multivariate logistic regression to investigate the association between the disposition decision for a patient (admit or discharge) and the ED census at the disposition decision time. In both studies, control variables included census, age, gender, race, place of treatment, chief complaint, and certain interaction terms. Results We found statistically significant correlation between ED census and triage/disposition decisions. For each additional patient in the ED, the odds of being assigned a high acuity versus medium or low acuity at triage is 1.011 times higher (95% confidence interval [CI] for Odds Ratio [OR] = [1.009,1.012]), and the odds of being assigned medium or high acuity versus low acuity at triage is 1.009 times higher (95% CI for OR = [1.008,1.010]). Similarly, the odds of being admitted versus discharged increases by 1.007 times (95% CI for OR = [1.006,1.008]) per additional patient in the ED at the time of disposition decision. Conclusion Increased ED occupancy was found to be associated with more patients being classified as higher acuity as well as higher hospital admission rates. As an example, for a commonly observed patient category, our model predicts that as the ED occupancy increases from 25 to 75 patients, the probability of a patient being triaged as high acuity increases by about 50% and the probability of a patient being categorized as admit increases by around 25%.

Objective Medical errors in the emergency department (ED) occur frequently. Yet, common adverse event detection methods, such as voluntary reporting, miss 90% of adverse events. Our objective was to demonstrate the use of patient-reported data in the ED to assess patient safety, including medical errors. Methods Analysis of patient-reported survey data collected over a 1-year period in a large, academic emergency department. All patients who provided a valid e-mail or cell phone number received a brief electronic survey within 24 hours of their ED encounter by e-mail or text message with Web link. Patients were asked about ED safety-related processes. Results From Aug 2012 to July 2013, we sent 52,693 surveys and received 7103 responses (e-mail response rate 25.8%), including 2836 free-text comments (44% of respondents). Approximately 242 (8.5%) of 2836 comments were classified as potential safety issues, including 12 adverse events, 40 near-misses, 23 errors with minimal risk of harm, and 167 general safety issues (eg, gaps in care transitions). Of the 40 near misses, 35 (75.0%) of 40 were preventable. Of the 52 adverse events or near misses, 5 (9.6%) were also identified via an existing patient occurrence reporting system. Conclusions A patient-reported approach to assess ED-patient safety yields important, complementary, and potentially actionable safety information.

Importance Physicians need information on how to use the first available high-sensitivity troponin (hsTnT) assay in the United States to identify patients at very low risk for 30-day adverse cardiac events (ACE). Objective To determine whether a negative hsTnT assay at 0 and 3 hours following emergency department presentation could identify patients at less than 1% risk of a 30-day ACE. Design, Setting, and Participants A prospective, observational study at 15 emergency departments in the United States between 2011 and 2015 that included individuals 21 years and older, presenting to the emergency department with suspected acute coronary syndrome. Of 1690 eligible individuals, 15 (no cardiac troponin T measurement) and 320 (missing a 0-hour or 3-hour sample) were excluded from the analyses. Exposures Serial hsTnT measurements (fifth-generation Roche Elecsys hsTnT assay). Main Outcomes and Measures Serial blood samples from each patient were collected after emergency department presentation (once identified as a potential patient with acute coronary syndrome) and 3 hours, 6 to 9 hours, and 12 to 24 hours later. Adverse cardiac events were defined as myocardial infarction, urgent revascularization, or death. The upper reference level for the hsTnT assay, defined as the 99th percentile, was established as 19 ng/L in a separate healthy US cohort. Patients were considered ruled out for acute myocardial infarction if their hsTnT level at 0 hours and 3 hours was less than the upper reference level. Gold standard diagnoses were determined by a clinical end point committee. Evaluation of assay clinical performance for acute myocardial infarction rule-out was prespecified; the hypothesis regarding 30-day ACE was formulated after data collection. Results In 1301 healthy volunteers (50.4% women; median age, 48 years), the upper reference level was 19 ng/L. In 1600 patients with suspected acute coronary syndrome (48.4% women; median age, 55 years), a single hsTnTlevel less than 6 ng/L at baseline had a negative predictive value for AMI of 99.4%. In 974 patients (77.1%) with both 0-hour and 3-hour hsTnT levels of 19 ng/L or less, the negative predictive value for 30-day ACE was 99.3% (95% CI, 99.1-99.6). Using sex-specific cutpoints, C statistics for women (0.952) and men (0.962) were similar for acute myocardial infarction. Conclusions and Relevance A single hsTnT level less than 6 ng/L was associated with a markedly decreased risk of AMI, while serial levels at 19 ng/L or less identified patients at less than 1% risk of 30-day ACE.

According to American College of Emergency Physicians, emergency department (ED) crowding occurs when the identified need for emergency services exceeds available resources for patient care in the ED, hospital, or both. ED crowding is a widely reported problem and several crowding scores are proposed to quantify crowding using hospital and patient data as inputs for assisting healthcare professionals in anticipating imminent crowding problems. Using data from a large academic hospital in North Carolina, we evaluate three crowding scores, namely, EDWIN, NEDOCS, and READI by assessing strengths and weaknesses of each score, particularly their predictive power. We perform these evaluations by first building a discrete-event simulation model of the ED, validating the results of the simulation model against observations at the ED under consideration, and utilizing the model results to investigate each of the three ED crowding scores under normal operating conditions and under two simulated outbreak scenarios in the ED. We conclude that, for this hospital, both EDWIN and NEDOCS prove to be helpful measures of current ED crowdedness, and both scores demonstrate the ability to anticipate impending crowdedness. Utilizing both EDWIN and NEDOCS scores in combination with the threshold values proposed in this work could provide a real-time alert for clinicians to anticipate impending crowding, which could lead to better preparation and eventually better patient care outcomes.

Background Guidelines recommend initiation of appropriate antimicrobial therapy within 1 h of severe sepsis diagnosis. Few sepsis bundles exist in the literature emphasizing initiation of specific antibiotic therapy. Objective To determine the impact of an antibiotic-specific sepsis bundle on the timely initiation of appropriate antibiotics. Methods For this before-and-after interventional study, the sepsis bundle at this 803-bed academic tertiary-care facility was redesigned to include specific antibiotic selection and dosing, based on suspected source of infection and susceptibility patterns. Protocol education and advertising was completed and bundle-specific antibiotics were put in the automated medication cabinet. Results Stepwise analysis of timely initiation of appropriate antibiotics included: 1) Was the initial antibiotic appropriate? 2) If so, was it initiated within 1 h of diagnosis? 3) If so, were all necessary appropriate antibiotics started? and 4) If so, were they started within 3 h of diagnosis? In comparing the 3-month-before group and 3-month-after group (n = 124), the appropriate initial antibiotic was started in 33.9% vs. 54.8% of patients (odds ratio [OR] 0.42, 95% confidence interval [CI] 0.19–0.93, p = 0.03) and within 1 h in 22.6% vs. 14.5% of patients (OR 1.71, 95% CI 0.62–4.92, p = 0.36), respectively. All necessary appropriate antibiotics were initiated in 16.1% vs. 12.9% of patients (OR 1.30, 95% CI 0.42–4.10, p = 0.80), and within 3 h in 14.5% vs. 9.7% of patients, respectively (OR 1.58, 95% CI 0.46–5.78, p = 0.58). Conclusions An updated antibiotic-specific sepsis bundle, with antibiotics put in an automated medication cabinet, can result in improvements in the initiation of appropriate initial antibiotic therapy for severe sepsis in the emergency department.

Background The yield of urine culture testing in the emergency department (ED) is often low, resulting in wasted laboratory and ED resources. Use of a reflex culture cancellation protocol, in which urine cultures are canceled when automated urinalysis results predict that culture yield will be low, may help to conserve these resources. Study Objectives To identify a reflex culture cancellation protocol consisting of urinalysis-based criteria to limit urine culture over-utilization. Methods We studied patients aged 5 years and older whose ED evaluation included both an automated urinalysis and urine culture. Logistic regression models incorporating individual urinalysis components were used to predict culture growth. Receiver operating characteristic curves corresponding to each model were constructed, and the area under the curve was used to identify the model that best predicted positive urine culture growth. Results There were 1546 ED patients who met study inclusion criteria. Of these, 314 (20%) had positive urine cultures. Restriction of culture testing to samples with white blood cells > 10 per high-power field, positive nitrites, positive leukocyte esterase, or positive bacteria provided a sensitivity of 96.5% (95% confidence interval [CI] 93.6–98.1%) and specificity of 48.1% (95% CI 45.3–51.0%) for positive urine culture. Implementation of a reflex culture cancellation protocol based on these criteria would have eliminated 604 of 1546 cultures (39%); 11 of 314 positive cultures (3.5%) would have been missed. Conclusion These results suggest that a substantial reduction in urine culture testing might be achievable by implementing this protocol. Confirmation of these findings in a validation cohort is necessary.