National Emergency Department Overcrowding Study Research Articles

Emergency department overcrowding and its associated factors at HARME medical emergency center in Eastern Ethiopia

IntroductionEmergency department (ED) overcrowding has become a significant concern as it can lead to compromised patient care in emergency settings. Various tools have been used to evaluate overcrowding in ED. However, there is a lack of data regarding this issue in resource-limited countries, including Ethiopia. This study aimed to validate NEDOCS, assess level of ED overcrowding and identify associated factors at HARME Medical Emergency Center, located in Hiwot Fana Comprehensive Specialized Hospital, Harar, Ethiopia. MethodsA cross-sectional study was conducted at the HARME Medical Emergency Center, Hiwot Fana Comprehensive Specialized Hospital, involving a total of 899 patients during 120 sampling intervals. The area under the receiver operating characteristic curves (AUC) was calculated to evaluate the agreement between objective and subjective assessments of ED overcrowding. A multivariable logistic regression analysis was employed to identify factors associated with ED overcrowding and statistically significant association was declared using 95 % confidence level and a p-value < 0.05. ResultsThe interrater agreement showed a strong correlation with a Cohen's kappa (κ) of 0.80. The National Emergency Department Overcrowding Study Score demonstrated a strong association with subjective assessments from residents and case team nurses, with an AUC of 0.81 and 0.79, respectively. According to residents' perceptions, ED were considered overcrowded 65.8 % of the time. Factors significantly associated with ED overcrowding included waiting time for triage (AOR: 2.24; 95 % CI: 1.54–3.27), working time (AOR: 2.23; 95 % CI: 1.52–3.26), length of stay (AOR: 2.40; 95 % CI: 1.27–4.54), saturation level (AOR: 2.35; 95 % CI: 1.31–4.20), chronic illness (AOR: 2.19; 95 % CI: 1.37–3.53), and abnormal pulse rate (AOR: 1.52; 95 % CI: 1.06–2.16). ConclusionThe study revealed that ED were overcrowded approximately two-thirds of the time.

Comparison of the International Crowding Measure in Emergency Departments (ICMED) and the National Emergency Department Overcrowding Study (NEDOCS) in Tertiary Care Hospital to Measure Emergency Department Crowding

Objective: To compare NEDOCS with ICMED in predicting clinicians' concerns regarding crowding in the Emergency Department of a tertiary care hospital in Pakistan.&#x0D; Study Design: Prospective comparative study.&#x0D; Place and Duration of Study: Accident &amp; Emergency Department, Pak Emirates Military Hospital, Rawalpindi Pakistan, from Dec 2021 to Jan 2022.&#x0D; Methodology: This study was conducted at the Accident and Emergency Department over 14 different days, 30 data sets of 3-hour intervals each were collected using the NEDOCS and ICMED proforma. NEDOCS Scores and ICMED scores were calculated. In addition, perceptions of the staff regarding crowding and danger to the patient's status were recorded on Visual Analogue scales.&#x0D; Results: The mean recorded NEDOCS score was 577.94±251.57, with 29 'extremely overcrowded' and 1 'overcrowded' data set.The mean ICMED score was 2.86±0.83. Twenty-four (80%) sets did not have crowding, with only six (20%) sets being categorized as 'crowded'. The NEDOCS score had a moderately positive correlation with the crowding perception of the staff (Correlation coefficient (r)=0.593).&#x0D; Conclusion: NEDOCS was a more suitable measure for recording ED crowding in Pakistan, as it recorded the quantitative component of waiting time. ICMED, on the other hand, only recorded waiting time on a binary scale, with the waiting time impact not translated fully on the total score.

Effects of Emergency Department Crowding and Time to Antibiotics in Pneumonia

Objective: To evaluate the relationship between emergency department (ED) crowding and time to antibiotic treatment in pneumonia patients. The secondary objective was to look for other factors related to delayed antibiotic treatment. Materials and Methods: The present study was a retrospective medical chart review between February 1 and June 30, 2015 of the patients aged 18 years and older with the ED diagnoses of pneumonia. The present study was performed in the ED of a tertiary care teaching hospital. One hundred seventy patients met the enrollment criteria. The patients were divided into ED crowded or non-crowded using the National Emergency Department Overcrowding Study tool for the main outcome of ED crowding and time to antibiotic treatment in pneumonia. Results: In the 170 pneumonia patients, 117 patients (68.8%) came to the ED during a crowded shift. The characteristics of the patients were similar in both the crowded and non-crowded shifts. Of the 170 pneumonia patients, 51.8% had CURB-65 scores of 1 or 2. Patients who came to the ED during the crowded shift and non-crowded shift received antibiotics at the median times of 125 and 110 minutes, respectively (p=0.125). Delayed antibiotic treatments of more than four hours occurred in 19 patients (16.2%) during the crowded shift and in three patients (5.7%) in the non-crowded shift (p=0.098). Other factors related to time to antibiotics were the first doctor to see the patient (p=0.05), severity of disease (p&lt;0.01), and admission type (p=0.01). Conclusion: ED crowding was not related to time to antibiotic treatment in pneumonia patients. However, if the clinical conditions of the patients looked severe or the doctor who cared for the patients was an emergency medicine resident, the patients received early administration of antibiotics. Keywords: Emergency department crowding, Pneumonia, Time to antibiotics

Overcrowding an encumbrance for an emergency health-care system: A perspective of Health-care providers from tertiary care center in Northern India.

BACKGROUND:Emergency department (ED) overcrowding is one of the leading problems of health-care organizations, discerned by ED medical staff, but it has never been measured objectively.OBJECTIVE:A 2 months prospective cross-sectional study was conducted to compare ED overcrowding measurement tools with the perceptions of ED emergency physician and ED assistant nursing superintendent (EDEP/EDANS).RESULTS:The results have shown that perceptions of ED overcrowding as noted by EDEP and EDANS, taken on a Likert scale, were 83.34% and 86.67%, respectively. Kappa values show a significant agreement between EDEP and EDANS subjective perceptions with objective values of the National Emergency Department Overcrowding Study (NEDOCS), Real-time Emergency Analysis of Demand Indicators (READI), and Emergency Department Work Index (EDWIN) scales. Furthermore, all three scales have statistically significant correlation; NEDOCS and READI had highest level of correlation coefficient (r = 0.662, P < 0.01) whereas READI and EDWIN shows least correlation coefficient value (r = 0.155, P < 0.01).CONCLUSION:Therefore, these scales may serve to quantify the subjective impressions of ED overcrowding. Evidence is clear of overcrowding harms, measures are needed to provide urgent medical care and future work up is need of the hour to systematically evaluate interventions and guide evidence-based policies.

NEDOCS: is it really useful for detecting emergency department overcrowding today?

The Emergency Department (ED) overcrowding is an ongoing problem all over the world. The scoring systems are available for the detection of this problem. This study aims to test the applicability of the National Emergency Department Overcrowding Study (NEDOCS) scoring system, one of the scoring systems that evaluate the ED overcrowding.In this prospective observational study, the survey was applied on on-duty doctors, nurses, paramedics, intern doctors, and ward persons working in a University Adult Emergency Department and agreed to participate in the study, between certain hours during the day and the NEDOCS score was calculated simultaneously. The demographic characteristics of the on-duty staff, overcrowding of ED, and the number of the on-duty staff members were recorded in the questionnaires.During the study, 153 measurements were performed, and 3221 questionnaires were filled. The NEDOCS mean score was determined as 101.59 and the most reached result was “extremely busy but not overcrowded” (32%). The ED was rated mostly as “busy” (33.7%) by the on-duty staff. A significant difference was found between ED overcrowding and NEDOCS score. There is a significant difference between ED overcrowding and on-duty emergency nurse and intern doctor count.The NEDOCS score is not suitable for evaluating ED overcrowding. Accurate determination of the ED overcrowding is very important to avoid the negative consequences of the ED overcrowding. Increasing emergency nurse and intern doctor count will decrease ED overcrowding. Also, there is an urgent need to constitute local hospitals and also public health policies to satisfy the increasingly ED's presentations.

The mitigation strategy of emergency department overcrowding

Objective To investigate the present situation and reasons of emergency department overcrowding, and put forward effective mitigation strategy. Methods By using input-throughput-outputmodel and choosing the method of fishbone diagram analysis, detaily analysis factors of emergency department overcrowding, then implement three-dimensional intervention in hospital, department, personal. Results Patients who stay > 48 h in the emergency department(ED) decreased from 11.9%(15 225/127 941) to 5.3%(7 245/136 698); patients who stay > 6 h in the Frist Aid Room of ED decreased from 54.6%(3 016/5 526)to 17.8%(987/5 526), both have statistically significant (χ2=3 705.04, χ2=1 186.32, P<0.01); before the intervention the National ED Overcrowding Study (NEDOCS) index at 0900, 1300, 2100, 0100 was 234.22±62.31, 253.55±59.26, 303.73±160.24, 187.36±25.73; after the intervention the degree of crowdedness of ED at this four points of time was significantly alleviated, NEDOCS index was 193.09±31.87, 187.09±22.65, 187.36±25.73, 154.03±21.56; there were significant differences between the two groups before and after the intervention (t=2.35-4.32, P<0.05). Conclusions To study and discuss the reasons of emergency department overcrowding, it can effectively relieve the happening of emergency department overcrowding through comprehensive intervention measures such as improve the environment, optimize the process, strengthen emergency medical personnel training and management, improve the service level hospital auxiliary support system. Key words: Emergency department; Overcrowding; Mitigation strategy

24 Use of the SONET Score to Evaluate Emergency Department Crowding: A Comparison to the National Emergency Department Overcrowding Study Scoring Tool

24 Use of the SONET Score to Evaluate Emergency Department Crowding: A Comparison to the National Emergency Department Overcrowding Study Scoring Tool

The inaccuracy of determining overcrowding status by using the National ED Overcrowding Study Tool

BackgroundEmergency 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. ObjectiveThe 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 methodsThis 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. ResultsIn 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). ConclusionUsing the NEDOCS tool to determine ED crowding might be inaccurate in an extremely high-volume ED setting.

Backboard time for patients receiving spinal immobilization by emergency medical services

BackgroundUse of backboards as part of routine trauma care has recently come into question because of the lack of data to support their effectiveness. Multiple authors have noted the potential harm associated with backboard use, including iatrogenic pain, skin ulceration, increased use of radiographic studies, aspiration and respiratory compromise. An observational study was performed at a level 1 academic trauma center to determine the total and interval backboard times for patients arriving via emergency medical services (EMS).FindingsPatients were directly observed. Transport time was recorded as an estimate of initiation of backboard use; arrival time, nurse report time and time of removal from the backboard were all recorded. National Emergency Department Overcrowding Study (NEDOCS) score, Emergency Severity Index (ESI) and demographic information were recorded for each patient encounter. Forty-six patients were followed. The mean total backboard time was 54 min (SD ±65). The mean EMS interval was 33 min (SD ±64), and the mean ED interval was 21 min (SD ±15). The ED backboard interval trended inversely to ESI (1 = 5 min, 2 = 10 min, 3 = 25 min, 4 = 26 min, 5 = 32 min).ConclusionPatients had a mean total backboard time of around an hour. The mean EMS interval was greater than the mean ED interval. Further study with a larger sample directed to establishing associated factors and to target possible reduction strategies is warranted.

The impact of overcrowding on the bacterial contamination of blood cultures in the ED

ObjectivesThis study aims to determine the risk factors associated with the bacterial contamination of blood cultures among adults visiting the emergency department (ED). MethodsClinical variables and medical records of adults with bacterial growth of blood cultures in the ED as well as the degree of ED crowding, between August 2007 and July 2008, were prospectively collected. ResultsOf the 11 491 adults who underwent blood culture sampling, the medical records of 558 (4.86%) eligible patients with bacterial growth in their blood cultures were analyzed. Most patients (366, or 3.19%) had true bacteremia, whereas 192 (1.67%) were regarded as contaminated. In multivariate analyses, ED overcrowding (scoring was based on a National Emergency Department Overcrowding Study [NEDOCS] score ≥100 points) was independently associated with blood culture contamination (odds ratio [OR], 1.58; P = .04). In contrast, other medical comorbidities, such as liver cirrhosis (OR, 0.31; P = .02), thrombocytopenia (<100 000/mm3; OR, 0.28; P = .002), or high serum levels of C-reactive protein (>100 mg/L; OR, 0.24; P < .001), were negatively associated with blood culture contamination. On further analysis of the 5 crowding categories as stratified by NEDOCS scores, which included not busy and busy (0-60 points), extremely busy but not overcrowded (60-100), overcrowded (100-140), severely overcrowded (140-180), and dangerously overcrowded (180-200), there was a strong correlation between blood culture contamination rates and the degrees of ED crowding (γ = 0.99, P < .001). ConclusionsEmergency department overcrowding may have an adverse impact on the quality of clinical care, including increasing the risk of blood culture contamination.

An Independent Evaluation of Four Quantitative Emergency Department Crowding Scales

Emergency department (ED) overcrowding has become a frequent topic of investigation. Despite a significant body of research, there is no standard definition or measurement of ED crowding. Four quantitative scales for ED crowding have been proposed in the literature: the Real-time Emergency Analysis of Demand Indicators (READI), the Emergency Department Work Index (EDWIN), the National Emergency Department Overcrowding Study (NEDOCS) scale, and the Emergency Department Crowding Scale (EDCS). These four scales have yet to be independently evaluated and compared. The goals of this study were to formally compare four existing quantitative ED crowding scales by measuring their ability to detect instances of perceived ED crowding and to determine whether any of these scales provide a generalizable solution for measuring ED crowding. Data were collected at two-hour intervals over 135 consecutive sampling instances. Physician and nurse agreement was assessed using weighted kappa statistics. The crowding scales were compared via correlation statistics and their ability to predict perceived instances of ED crowding. Sensitivity, specificity, and positive predictive values were calculated at site-specific cut points and at the recommended thresholds. All four of the crowding scales were significantly correlated, but their predictive abilities varied widely. NEDOCS had the highest area under the receiver operating characteristic curve (AROC) (0.92), while EDCS had the lowest (0.64). The recommended thresholds for the crowding scales were rarely exceeded; therefore, the scales were adjusted to site-specific cut points. At a site-specific cut point of 37.19, NEDOCS had the highest sensitivity (0.81), specificity (0.87), and positive predictive value (0.62). At the study site, the suggested thresholds of the published crowding scales did not agree with providers' perceptions of ED crowding. Even after adjusting the scales to site-specific thresholds, a relatively low prevalence of ED crowding resulted in unacceptably low positive predictive values for each scale. These results indicate that these crowding scales lack scalability and do not perform as designed in EDs where crowding is not the norm. However, two of the crowding scales, EDWIN and NEDOCS, and one of the READI subscales, bed ratio, yielded good predictive power (AROC >0.80) of perceived ED crowding, suggesting that they could be used effectively after a period of site-specific calibration at EDs where crowding is a frequent occurrence.

National Emergency Department Overcrowding Study tool is not useful in an Australian emergency department

To determine the accuracy and usefulness of the National Emergency Department Overcrowding Study (NEDOCS) tool in an urban hospital ED in Australia by direct comparison with subjective assessment by senior ED staff. A sample of simultaneous subjective and objective data pairs were collected six times a day for a period of 3 weeks. All senior medical staff in the ED answered a brief questionnaire along with the senior charge nurse for the ED. Simultaneously, the senior charge nurse also documented the total number of patients in the ED, the number of patients awaiting admission, the number of patients on ventilators, the longest time waited by an ED patient for ward bed, and the waiting time for the last patient from the Waiting Room placed on a trolley. The objective indicators were entered into a Web-based NEDOCS tool and transformed scores were compared with the averaged and transformed subjective scores for each sample time. Bland-Altmann and Kappa statistics were used to test the agreement between the objective and subjective measuring methods. The mean difference between the subjective and objective methods was small (3.5 [95% confidence interval -0.875-7.878] ); however, the 95% limits of agreement was wide (-46.52-53.43). The Kappa statistic used to assess the extent of reproducibility between categorical variables was 0.31 (95% confidence interval 0.17-0.45). The present study suggests that NEDOCS method of processing the objective overcrowding data does not accurately reflect the subjective assessment of the senior staff working at that time in the ED. This might be because the assumptions of the original NEDOCS study are flawed.

Estimating the degree of emergency department overcrowding in academic medical centers: results of the National ED Overcrowding Study (NEDOCS).

No single universal definition of emergency department (ED) overcrowding exists. The authors hypothesize that a previously developed site-sampling form for academic ED overcrowding is a valid model to quantify overcrowding in academic institutions and can be used to develop a validated short form that correlates with overcrowding. A 23-question site-sampling form was designed based on input from academic physicians at eight medical schools representative of academic EDs nationwide. A total of 336 site-samplings at eight academic medical centers were conducted at 42 computer-generated random times over a three-week period by independent observers at each site. These sampling times ranged from very slow to severely overcrowded. The outcome variable was the degree of overcrowding as assessed by the charge nurse and ED physicians. The full model consisted of objective data that were obtained by counting the number of patients, determining patients' waiting times, and obtaining information from registration, triage, and ancillary services. Specific objective data were indexed to site-specific demographics. The outcome and objective data were compared using a multiple linear regression to determine predictive validity of the full model. A five-question reduced model was calculated using a backward stepdown procedure. Predictive validity and relationships between the outcome and objective data were assessed using a mixed-effects linear regression model, treating center as random effect. Overcrowding occurred 12% to 73% of the time (mean, 35%), with two hospitals being overcrowded more than 50% of the time. Comparison of objective and outcome data resulted in an R(2) of 0.49 (p < 0.001), indicating a good degree of predictive validity. A reduced five-question model predicted the full model with 88% accuracy. Overcrowding varied widely between academic centers during the study period. Results of a five-question reduced model are valid and accurate in predicting the degree of overcrowding in academic centers.