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BackgroundEmergency 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.MethodsWe 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.ResultsA 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.ConclusionNot 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.  相似文献   

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Objectives

The primary aim of this study was to evaluate for differences in acuity level and rate of admission on return visit between patients who leave without being seen (LWBS) and those who are initially evaluated by a physician. Our secondary aim was as well as to identify predictors of which LWBS patients will return to the ED with high acuity or require admission.

Methods

A cross-sectional study using an administrative database at an academic tertiary-care pediatric hospital in the United States from January 1, 2006, to December 31, 2008 was done.

Results

There were 3525 patients who LWBS during the study period (1.2% of total ED visits). Of these, 87% were triaged as nonurgent, and 13% as urgent at their initial visit. Two hundred eighty-nine (8%) of LWBS patients returned to the ED within 48 hours. Compared with the population who returned to the ED after previous evaluation, patients who LWBS from their initial visit and returned had significantly lower odds of urgent acuity at time of return visit (odds ratio [OR], 0.22; 95% confidence interval [CI], 0.15-0.32) and of being admitted (OR, 0.58; 95% CI, 0.40-0.84). Urgent acuity at initial visit (OR, 2.86; 95% CI, 1.35-6.04) and number of ED visits in last 6 months (OR, 1.24; 95% CI, 1.02-1.52) were significant predictors of admission at return visit among the LWBS population.

Conclusions

Generally, patients who LWBS from a pediatric ED were unlikely to return for ED care, and those who did were unlikely to either be triaged as urgent or require hospital admission. This study showed that urgent acuity during the initial visit and number of previous ED visits were significant predictors of admission on return. Identification of these predictors may allow a targeted intervention to ensure follow-up of patients who meet these criteria after they LWBS from the pediatric ED.  相似文献   

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We developed a statistical model that would identify and quantify the relative contributions of different factors hypothesized to impact the frequency of emergency center (EC) patients who leave without being seen (LWBS). We performed an analysis of the daily counts of patients that registered in our EC during a 21-month period who then LWBS. Candidate predictor variables included the number of patients seen, and the number admitted to the hospital, for each area of our EC, as well as the hours of faculty double coverage, and the day of the week. Univariate analyses were performed using standard methods. Multivariate analysis was performed using the general linear model. A backward selection procedure was used to eliminate statistically insignificant variables until all remaining independent variables had P-values < or = .05. External validation and analysis of the stability of the estimated regression coefficients of the model were evaluated using bootstrap methods. Two-tailed tests and a type I error of 0.05 were used. During the period studied, 133,666 patients were registered in the EC and 9,894 (7.4%) left. Multivariate analysis identified six variables that were significantly associated with LWBS. The fitted model containing all six variables explained 52.8% of the variability observed in LWBS frequency. The most powerful predictor of LWBS was total number of patients cared for in the main ED. This accounted for 46.4% of the observed variation in LWBS. The total number of trauma and resuscitation patients, and the total number of observation unit admissions to the hospital were also associated with increased LWBS. More pediatric cases seen in the main ED, weekends, and additional faculty coverage were associated with fewer patients leaving. Efforts to decrease the LWBS rate will be most successful if they address the issue of main ED volume.  相似文献   

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Background

Emergency department (ED) crowding has become more common, and perceptions of crowding vary among different health care providers. The National Emergency Department Overcrowding Study (NEDOCS) tool is the most commonly used tool to estimate ED crowding but still uncertain of its reliability in different ED settings.

Objective

The objectives of this study are to determine the accuracy of using the NEDOCS tool to evaluate overcrowding in an extremely high-volume ED and assess the reliability and consistency of different providers’ perceptions of ED crowding.

Material and methods

This was a 2-phase study. In phase 1, ED crowding was determined by the NEDOCS tool. The ED length of stay and number of patients who left without being seen were analyzed. In phase 2, a survey of simulated ED census scenarios was completed by different providers. The interrater and intrarater agreements of ED crowding were tested.

Results

In phase 1, the subject ED was determined to be overcrowded more than 75% of the time in which nearly 50% was rated as severely overcrowded by the NEDOCS tool. No statistically significant difference was found in terms of the average length of stay and the number of left without being seen patients under different crowding categories. In phase 2, 88 surveys were completed. A moderate level of agreement between health care providers was reached (κ = 0.5402, P < .0001). Test-retest reliability among providers was high (r = 0.8833, P = .0007). The strength of agreement between study groups and the NEDOCS was weak (κ = 0.3695, P < .001).

Conclusion

Using the NEDOCS tool to determine ED crowding might be inaccurate in an extremely high-volume ED setting.  相似文献   

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Background: Emergency department (ED) crowding is just beginning to be quantified. The only two scales presently available are the National Emergency Department Overcrowding Scale (NEDOCS) and the Emergency Department Work Index (EDWIN). Objectives: To assess the value of the NEDOCS and the EDWIN in predicting overcrowding. The hypothesis of this study was that the NEDOCS and the EDWIN would be equally sensitive and specific for overcrowding. Methods: The NEDOCS, the EDWIN, and an overcrowding measure (OV) were determined every two hours for a ten‐day period in December 2004. The NEDOCS is a statistically derived calculation, and the EDWIN is a formula‐based calculation. The overcrowding measure is a composite of physician and charge nurse expert opinion on the degree of overcrowding as measured on a 100‐mm visual analogue scale (VAS). The primary outcome, overcrowding, was based on the dichotomized OV VAS score at the midpoint of 50 mm (≥50, overcrowded; <50, not overcrowded). The area under the receiver operator characteristic curve (AUC) and an index of adequacy (relative prognostic content) of each measure, on the basis of the likelihood ratio chi‐square statistic, were computed to evaluate the performance of NEDOCS and EDWIN. Results: There were 130 completed sampling times over ten days. The OV indicated that the ED was overcrowded 62% of the time. The AUC for the NEDOCS was 0.83 (95% CI = 0.75 to 0.90), and the AUC for the EDWIN was 0.80 (95% CI = 0.73 to 0.88). The NEDOCS score accounts for 97% of the prognostic information provided by combining all variables used in each model into one combined model. The EDWIN score accounts for only 86% (χ2 test for difference, p = 0.02). Conclusions: Both scales had high AUCs, correlated well with each other, and showed good discrimination for predicting ED overcrowding. This establishes construct validity for these scales as measures of overcrowding. Which scale is used in an ED is dependent on which set of data is most readily available, with the favored scale being the NEDOCS.  相似文献   

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Patients who leave the ED without being seen (LWBS) are unlikely to be satisfied with the quality of the service provided and might be at risk from conditions that have not been assessed or treated. We therefore examined the available research literature to inform the following questions: (i) In patients who attend for ED care, what factors are associated with the decision to LWBS? (ii) In patients who attend for ED care, are there adverse health outcomes associated with the decision to LWBS? (iii) Which interventions have been used to try to reduce the number of patients who attend for ED care and LWBS? From the available literature, there was insufficient evidence to draw firm conclusions; however, the literature does suggest that patients who LWBS have conditions of lower urgency and lower acuity, are more likely to be male and younger, and are likely to identify prolonged waiting times as a central concern. LWBS patients generally have very low rates of subsequent admission, and reports of serious adverse events are rare. Many LWBS patients go on to seek alternative medical attention, and they might have higher rates of ongoing symptoms at follow‐up. Further research is recommended to include comprehensive cohort or well‐designed case–control studies. These studies should assess a wide range of related factors, including patient, hospital and other relevant factors. They should compare outcomes for groups of LWBS patients with those who wait and should include cross‐sectoral data mapping to truly detect re‐attendance and admission rates.  相似文献   

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