The Emergency Severity Index (version 3) 5-level triage system scores predict ED resource consumption

Models to predict length of stay in the emergency department: a systematic literature review and appraisal

INTRODUCTION

Prolonged Length of Stay (LOS) in ED (Emergency Department) has been associated with poor clinical outcomes. Prediction of ED LOS may help optimize resource utilization, clinical management, and benchmarking. This study aims to systematically review models for predicting ED LOS and to assess the reporting and methodological quality about these models.

METHODS

The online database PubMed, Scopus, and Web of Science (10 Sep 2023) was searched for English language articles that reported prediction models of LOS in ED. Identified titles and abstracts were independently screened by two reviewers. All original papers describing either development (with or without internal validation) or external validation of a prediction model for LOS in ED were included.

RESULTS

Of 12,193 uniquely identified articles, 34 studies were included (29 describe the development of new models and five describe the validation of existing models). Different statistical and machine learning methods were applied to the papers. On the 39-point reporting score and 11-point methodological quality score, the highest reporting scores for development and validation studies were 39 and 8, respectively.

CONCLUSION

Various studies on prediction models for ED LOS were published but they are fairly heterogeneous and suffer from methodological and reporting issues. Model development studies were associated with a poor to a fair level of methodological quality in terms of the predictor selection approach, the sample size, reproducibility of the results, missing imputation technique, and avoiding dichotomizing continuous variables. Moreover, it is recommended that future investigators use the confirmed checklist to improve the quality of reporting.

The Management of Children and Youth With Pediatric Mental and Behavioral Health Emergencies

Mental and behavioral health (MBH) visits of children and youth to emergency departments are increasing in the United States. Reasons for these visits range from suicidal ideation, self-harm, and eating and substance use disorders to behavioral outbursts, aggression, and psychosis. Despite the increase in prevalence of these conditions, the capacity of the health care system to screen, diagnose, and manage these patients continues to decline. Several social determinants also contribute to great disparities in child and adolescent (youth) health, which affect MBH outcomes. In addition, resources and space for emergency physicians, physician assistants, nurse practitioners, and prehospital practitioners to manage these patients remain limited and inconsistent throughout the United States, as is financial compensation and payment for such services. This technical report discusses the role of physicians, physician assistants, and nurse practitioners, and provides guidance for the management of acute MBH emergencies in children and youth. Unintentional ingestions and substance use disorder are not within the scope of this report and are not specifically discussed.

Five Level Triage vs. Four Level Triage in a Quaternary Emergency Department: National Analysis on Waiting Time, Validity, and Crowding-The CREONTE (Crowding and RE-Organization National TriagE) Study Group

Background and Objectives: Triage systems help provide the right care at the right time for patients presenting to emergency departments (EDs). Triage systems are generally used to subdivide patients into three to five categories according to the system used, and their performance must be carefully monitored to ensure the best care for patients. Materials and Methods: We examined ED accesses in the context of 4-level (4LT) and 5-level triage systems (5LT), implemented from 1 January 2014 to 31 December 2020. This study assessed the effects of a 5LT on wait times and under-triage (UT) and over-triage (OT). We also examined how 5LT and 4LT systems reflected actual patient acuity by correlating triage codes with severity codes at discharge. Other outcomes included the impact of crowding indices and 5LT system function during the COVID-19 pandemic in the study populations. Results: We evaluated 423,257 ED presentations. Visits to the ED by more fragile and seriously ill individuals increased, with a progressive increase in crowding. The length of stay (LOS), exit block, boarding, and processing times increased, reflecting a net raise in throughput and output factors, with a consequent lengthening of wait times. The decreased UT trend was observed after implementing the 5LT system. Conversely, a slight rise in OT was reported, although this did not affect the medium-high-intensity care area. Conclusions: Introducing a 5LT improved ED performance and patient care.

Palliative care patient emergency department visits at tertiary university-based emergency department in Ireland

INTRODUCTION

Palliative care patients often present to the emergency department (ED) for various reasons e.g., acute illness, pain, altered mental status, and complications of therapy. Many visits involve less severe etiologies e.g., dyspnea, constipation, fear as patients approach the end of life, which may be more effectively and efficiently managed outside of the ED. The objective of this study is to identify and assess the frequency of presenting complaints, primary diagnosis, triage acuity, need for admission, in an Irish setting.

METHODS

A single-center retrospective, observational study of palliative care patients presenting to a tertiary-care university hospital emergency department in Dublin, Ireland. Study subjects were identified using the palliative care database and cross-referencing with the ED electronic patient record system database. The primary objective to identify potential areas to minimize ED visits and improve patient care and quality of life by elucidating reasons for visits. Outcome measures include presenting complaint, primary diagnosis, triage severity score, admission, discharge, death in hospital. Statistical analysis presented as descriptive statistics.

RESULTS

Four-hundred-ninety-nine ED visits, 245 (49%) were male, and 254 (51%) were female with a mean age of 69.3 years-of-age. Most patients, 285 (57.1%) self-referred to the emergency department, with general practitioners and skilled nursing facility referrals 72 (14.4%) and 39 (7.8%), respectively. Primary diagnoses were various cancers, chronic obstructive pulmonary disease, congestive heart failure, and dementia. Major reasons for visits were dyspnea, pain, falls, trauma, fever, and altered mental status. Two-hundred-eighty-nine patients (58%) had an emergency severity index (ESI) score of 1 or 2 demonstrating a higher level of acuity. Three-hundred-fifty-eight (71.7%) were admitted, 141 (28.3%) discharged to home, 64 (12.8%) admitted patients died during their hospital admission.

CONCLUSIONS

Palliative care patients utilize ED services not uncommonly. Though many of these patients presented with higher acuity triage scores, 42% had lower ESI scores and may be effectively managed outside of the ED. These data suggest developing mechanisms for these patients to be urgently evaluated in their homes or facilities obviating the need for an ED evaluation.

Decreased readmission rates following use of modified trauma-specific frailty index in older trauma patients: A follow-up study

INTRODUCTION

Post-discharge readmission rates using modified Trauma-Specific Frailty Index (mTSFI) compared to the Emergency Severity Index (ESI) are unknown. In our pilot study, we demonstrated that mTSFI usage more accurately triages older trauma patients. In the current study, we hypothesized that adult trauma patients triaged using mTSFI would have lower readmission rates at the 30-day interval post discharge.

METHODS

Retrospective review of readmission rates for 96 trauma patients ≥ 50 years old was performed. The two study groups were categorized as mTSFI-concordant and ESI-concordant. Fisher's exact test was performed.

RESULTS

Mean ages for ESI and mTSFI groups were 63.8 (SD 10.6) and 65.2 (SD 10.8) years. The 30-day readmission rate was 0% (0/32) in the mTSFI group vs 11% (7/64) in the ESI group (p = 0.104).

CONCLUSIONS

Utilization of mTSFI for adult trauma patients may lead to lower 30-day readmission rates compared to using ESI, despite our sample sizes being too small to demonstrate a statistically significant difference.

Application of job shop scheduling approach in green patient flow optimization using a hybrid swarm intelligence

With the increasing demand for hospital services amidst the COVID-19 pandemic, allocation of limited public resources and management of healthcare services are of paramount importance. In the field of patient flow scheduling, previous research primarily focused on classical-based objective functions, while ignoring environmental-based objective functions. This study presents a flexible job shop scheduling problem to optimize patient flow and, thereby, minimize the total carbon footprint, as the sustainability-based objective function. Since flexible job shop scheduling is an NP-hard problem, a metaheuristic optimization algorithm, called Chaotic Salp Swarm Algorithm Enhanced with Opposition-Based Learning and Sine Cosine (CSSAOS), was developed. The proposed algorithm integrates the Salp Swarm Algorithm (SSA) with chaotic maps to update the position of followers, the sine cosine algorithm to update the leader position, and opposition-based learning for a better exploration of the search space. generating more accurate solutions. The proposed method was successfully applied in a real-world case study and demonstrated better performance than other well-known metaheuristic algorithms, including differential evolution, genetic algorithm, grasshopper optimization algorithm, SSA based on opposition-based learning, quantum evolutionary SSA, and whale optimization algorithm. In addition, it was found that the proposed method is scalable to different sizes and complexities.

Patient disposition using the Emergency Severity Index: a retrospective observational study at an interdisciplinary emergency department

OBJECTIVES

Early patient disposition is crucial to prevent crowding in emergency departments (EDs). Our study aimed to characterise the need of in-house resources for patients treated in the ED according to the Emergency Severity Index (ESI) and the presenting complaint at the timepoint of triage.

DESIGN

A retrospective single-centre study was conducted.

SETTING

Data of all patients who presented to the interdisciplinary ED of a tertiary care hospital in Munich, Germany, from 2014 to 2017 were analysed.

PARTICIPANTS

n=113 694 patients were included.

MEASURES

ESI Score, medical speciality according to the chief complaint, mode of arrival, admission rates and discharge destination from the ED were evaluated.

RESULTS

Patient disposition varied according to ESI scores in combination with the chief complaint. Patients with low ESI scores were more likely to be admitted after treatment in the ED than patients with high ESI scores. Highly prioritised patients (ESI 1) mainly required admission to an intensive care unit (ICU, 27%), intermediate care unit (IMC, 37%) or immediate intervention (11%). In this critical patient group, 30% of patients with neurological or medical symptoms required immediate intensive care, whereas only 17% of patients with surgical problems were admitted to an ICU. A significant number of patients (particularly with neurological or medical problems) required hospital (and in some cases even ICU or IMC) admission despite high ESI scores.

CONCLUSIONS

Overall, ESI seems to be a useful tool to anticipate the need for specialised in-hospital resources on arrival. Patients with symptoms pointing at neurological or medical problems need particular attention as ESI may fail to sufficiently predict the care facility level for this patient group.

A Comparative Analysis of Hospital Triage Systems in the Geriatric Adult Trauma Patients: A Quality Improvement Pilot Study

BACKGROUND

The objective of our study is to compare the predicted hospital admission disposition based on the level of risk as determined by the modified Trauma-Specific Frailty Index (mTSFI) score with those determined by arbitrary decisions made based on the Emergency Severity Index (ESI) severity level.

METHODS

We surveyed 100 trauma patients ages 50 and older, admitted to a level 1 trauma center between April 2019 and July 2019. We retrospectively reviewed the hospital admission disposition of each patient under the ESI, which was then compared to the mTSFI-predicted hospital admission disposition. The mTSFI scores were calculated by surveying each patient. Statistical analysis was performed to identify any statistical significance of concordance and discordance when comparing the mTSFI and ESI.

RESULTS

The average age was 57.6 ± 4.2 years old in the non-geriatric group vs 76.3 ± 7.3 years old in the geriatric group. There was a male predominance in both groups (61% vs 69.5%). The mTSFI identified a higher percentage of triage discordance in the non-geriatric group (73%) compared to the geriatric cohort (53%) (95% difference CI, [39.6-40], P = .05).

DISCUSSION

Non-geriatric patients have higher recorded rate of frailty than previously recognized and screening should begin at age 50, not 65. The mTSFI may be an effective tool to appropriately triage adult trauma patients at increased risk due to frailty and may reduce in-hospital complications.

Impact of COVID-19 lockdown on routine oncology versus emergency care at a high volume cancer centre

BACKGROUND

We investigated the influence of population-wide COVID-19 lockdown measures implemented on 16, March 2020 on routine and emergency care of cancer outpatients at a tertiary care cancer centre in Vienna, Austria.

METHODS

We compared the number/visits of cancer outpatients receiving oncological therapies at the oncologic day clinic (DC) and admissions at the emergency department (ED) of our institution in time periods before (pre-lockdown period: 1 January - 15 March 2020) and after (post-lockdown period: 16 March- 31 May 2020) lockdown implementation with the respective reference periods of 2018 and 2019. Additionally, we analysed Emergency Severity Index (ESI) score of unplanned cancer patient presentations to the ED in the same post-lockdown time periods. Patient outcome was described as 3-month mortality rate (3-MM).

RESULTS

In total, 16 703 visits at the DC and 2664 patient visits for the respective time periods were recorded at the ED. No decrease in patient visits was observed at the DC after lockdown implementation (P = .351), whereas a substantial decrease in patient visits at the ED was seen (P < .001). This translates into a 26%-31% reduction of cancer-related patient visits per half month after the lockdown at the ED (P < .001 vs. 2018 + 2019). There was no difference in the distribution of ESI scores at ED presentation (P = .805), admission rates or 3-MM in association with lockdown implementation (P = .086).

CONCLUSION

We demonstrate the feasibility of maintaining antineoplastic therapy administration during the COVID-19 pandemic. However, our data underline the need for adapted management strategies for emergency presentations of cancer patients.

Racial/ethnic disparities in emergency department wait times in the United States, 2013-2017

BACKGROUND

Previous research shows that Black and Hispanic patients have longer ED wait times than White patients, but these data do not reflect recent changes such as the Affordable Care Act. In addition, previous research does not account for the non-normal distribution of wait times, wherein a sizable subgroup of patients seen promptly and those not seen promptly experience long wait times.

METHODS

We utilized National Hospital Ambulatory Medical Care Survey (NHAMCS) datasets (2013-2017) to examine mean ED wait time comparing visits by Black, Hispanic, and Asian patients to White patients. Using a two-part regression model, we adjusted for patient, hospital, and health system factors, and estimated differences, for each of five triage levels, in (a) likelihood of waiting at least 5 min and (b) difference in wait time among those not seen promptly.

RESULTS

Our cohort included 38,800 White, 14,838 Black, 10,619 Hispanic, and 1257 Asian patient visits. Black (triage level 3) and Hispanic (triage levels 3 and 4) patients had longer mean wait times than White patients. Adjusted likelihood of not being seen promptly was lower among Blacks (triage levels 3, 4 and 5), Hispanics (triage level 5) and Asians (triage level 5) compared to Whites. Among those waiting at least 5 min, adjusted wait time was longer among Blacks in triage level 3 (5.2 min, 95% CI, 1.3 to 9.0) and level 4 (2.5 min, 95% CI, 0.2 to 4.9), Hispanics in triage level 4 (4.7 min, 95% CI, 1.7 to 7.7) and Asians in triage level 5 (16.3 min, 95% CI, 0.6 to 31.9) compared to Whites.

CONCLUSIONS

Minority patients were less likely to wait to be seen, but waited longer if not seen promptly. These data exhibit that ED wait time disparities persist for African American and Hispanic patients and extend this observation to Asian patients.

The development and validation of a resource consumption score of an emergency department consultation

Background

Emergency Department (ED) visits and health care costs are increasing globally, but little is known about contributing factors of ED resource consumption. This study aims to analyse and to predict the total ED resource consumption out of the patient and consultation characteristics in order to execute performance analysis and evaluate quality improvements.

Methods

Characteristics of ED visits of a large Swiss university hospital were summarized according to acute patient condition factors (e.g. chief complaint, resuscitation bay use, vital parameter deviations), chronic patient conditions (e.g. age, comorbidities, drug intake), and contextual factors (e.g. night-time admission). Univariable and multivariable linear regression analyses were conducted with the total ED resource consumption as the dependent variable.

Results

In total, 164,729 visits were included in the analysis. Physician resources accounted for the largest proportion (54.8%), followed by radiology (19.2%), and laboratory work-up (16.2%). In the multivariable final model, chief complaint had the highest impact on the total ED resource consumption, followed by resuscitation bay use and admission by ambulance. The impact of age group was small. The multivariable final model was validated (R² of 0.54) and a scoring system was derived out of the predictors.

Conclusions

More than half of the variation in total ED resource consumption can be predicted by our suggested model in the internal validation, but further studies are needed for external validation. The score developed can be used to calculate benchmarks of an ED and provides leaders in emergency care with a tool that allows them to evaluate resource decisions and to estimate effects of organizational changes.

HRSA's evidence-based tele-emergency network grant program: Multi-site prospective cohort analysis across six rural emergency department telemedicine networks

Background

The Health Resources and Services Administration (HRSA), Federal Office of Rural Health Policy (FORHP) funded the Evidence-Based Tele-Emergency Network Grant Program (EB TNGP) to serve the dual purpose of providing telehealth services in rural emergency departments (teleED) and systematically collecting data to inform the telehealth evidence base. This provided a unique opportunity to examine trends across multiple teleED networks and examine heterogeneity in processes and outcomes.

Method and findings

Six health systems received funding from HRSA under the EB TNGP to implement teleED services and they did so to 65 hospitals (91% rural) in 11 states. Three of the grantees provided teleED services to a general patient population while the remaining three grantees provided teleED services to specialized patient populations (i.e., stroke, behavioral health, critically ill children). Over a 26-month period (November 1, 2015 –December 31, 2017), each grantee submitted patient-level data for all their teleED encounters on a uniform set of measures to the data coordinating center. The six grantees reported a total of 4,324 teleED visits and 99.86% were technically successful. The teleED patients were predominantly adult, White, not Latinx, and covered by Medicare or private insurance. Across grantees, 7% of teleED patients needed resuscitation services, 58% were rated as emergent, and 30% were rated as urgent. Across grantees, 44.2% of teleED patients were transferred to another inpatient facility, 26.0% had a routine discharge, and 24.5% were admitted to the local inpatient facility. For the three grantees who served a general patient population, the most frequent presenting complaints for which teleED was activated were chest pain (25.7%), injury or trauma (17.1%), stroke symptoms (9.9%), mental/behavioral health (9.8%), and cardiac arrest (9.5%). The teleED consultation began before the local clinician exam in 37.8% of patients for the grantees who served a general patient population, but in only 1.9% of patients for the grantees who provided specialized services.

Conclusions

Grantees used teleED services for a representative rural population with urgent or emergent symptoms largely resulting in transfer to a distant hospital or inpatient admission locally. TeleED was often available as the first point of contact before a local provider examination. This finding points to the important role of teleED in improving access for rural ED patients.

Prediction of emergency department resource requirements during triage: An application of current natural language processing techniques

OBJECTIVE

Accurate triage in the emergency department (ED) is critical for medical safety and operational efficiency. We aimed to predict the number of future required ED resources, as defined by the Emergency Severity Index (ESI) triage protocol, using natural language processing of nursing triage notes.

METHODS

We constructed a retrospective cohort of all 265,572 consecutive ED encounters from 2015 to 2016 from 3 separate clinically heterogeneous academically affiliated EDs. We excluded encounters missing relevant information, leaving 226,317 encounters. We calculated the number of resources used by patients in the ED retrospectively and based outcome categories on criteria defined in the ESI algorithm: 0 (30,604 encounters), 1 (49,315 encounters), and 2 or more (146,398 encounters). A neural network model was trained on a training subset to predict the number of resources using triage notes and clinical variables at triage. Model performance was evaluated using the test subset and was compared with human ratings.

RESULTS

Overall model accuracy and macro F1 score for number of resources were 66.5% and 0.601, respectively. The model had similar macro F1 (0.589 vs 0.592) and overall accuracy (65.9% vs 69.0%) compared to human raters. Model predictions had slightly higher F1 scores and accuracy for 0 resources and were less accurate for 2 or more resources.

CONCLUSIONS

Machine learning of nursing triage notes, combined with clinical data available at ED presentation, can be used to predict the number of required future ED resources. These findings suggest that machine learning may be a valuable adjunct tool in the initial triage of ED patients.

A Method for Grouping Emergency Department Visits by Severity and Complexity

INTRODUCTION

Triage functions to quickly prioritize care and sort patients by anticipated resource needs. Despite widespread use of the Emergency Severity Index (ESI), there is still no universal standard for emergency department (ED) triage. Thus, it can be difficult to objectively assess national trends in ED acuity and resource requirements. We sought to derive an ESI from National Hospital Ambulatory Medical Care Survey (NHAMCS) survey items (NHAMCS-ESI) and to assess the performance of this index with respect to stratifying outcomes, including hospital admission, waiting times, and ED length of stay (LOS).

METHODS

We used data from the 2010-2015 NHAMCS, to create a measure of ED visit complexity based on variables within NHAMCS. We used NHAMCS data on chief complaint, vitals, resources used, interventions, and pain level to group ED visits into five levels of acuity using a stepwise algorithm that mirrored ESI. In addition, we examined associations of NHAMCS-ESI with typical indicators of acuity such as waiting time, LOS, and disposition. The NHAMCS-ESI categorization was also compared against the "immediacy" variable across all of these outcomes. Visit counts used weighted scores to estimate national levels of ED visits.

RESULTS

The NHAMCS ED visits represent an estimated 805,726,000 ED visits over this time period. NHAMCS-ESI categorized visits somewhat evenly, with most visits (42.5%) categorized as a level 3. The categorization pattern is distinct from that of the "immediacy" variable within NHAMCS. Of admitted patients, 89% were categorized as NHAMCS-ESI level 2-3. Median ED waiting times increased as NHAMCS-ESI levels decreased in acuity (from approximately 14 minutes to 25 minutes). Median LOS decreased as NHAMCS-ESI decreased from almost 200 minutes for level 1 patients to nearly 80 minutes for level 5 patients.

CONCLUSION

We derived an objective tool to measure an ED visit's complexity and resource use. This tool can be validated and used to compare complexity of ED visits across hospitals and regions, and over time.

Validity and Reliability of Emergency Severity Index and Conventional Three-Tier Triage System in the Emergency Department, Hospital Universiti Sains Malaysia

Background

The study aimed to examine the reliability and validity of the existing three-tier triaging system and a new five-level emergency triaging system, emergency severity index (ESI), in the Emergency Department (ED) of Hospital Universiti Sains Malaysia (HUSM).

Methods

This study was conducted in HUSM’s ED over two study periods. In the first three months, 300 patients were triaged under the three-tier triaging system, and, in the subsequent three months, 280 patients were triaged under the ESI. The patients were triaged by junior paramedics and the triage records were retained and later re-triaged by senior paramedics. The inter-rater reliability was evaluated using Cohen's Kappa statistics. The acuity ratings of the junior paramedics were compared with those of the expert panel to determine the sensitivity and specificity of each acuity level for both the ESI and the three-tier triaging system. The over-triage rate, under-triage rate, amount of resources used, admission rate and discharge rate were also determined.

Results

The inter-rater agreement for the three-tier triaging system was 0.81 while that of the ESI was 0.75. The ESI had a higher average sensitivity of 74.3% and a specificity of 94.4% while the three-tier system’s average sensitivity was 68.5% and its specificity 87.0%. The average under-triage and over-triage rates for the ESI were 10.7% and 6.2%, respectively, which were lower than the three-tier system’s average under-triage rate of 13.1% and over-triage rate of 17.1%. The urgency levels of both the ESI and the three-tier system were associated with increased admission rates and resources used in the ED.

Conclusion

The ESI’s inter-rater reliability was comparable to the three-tier triaging system and it demonstrated better validity than the existing three-tier system.

The Korean Triage and Acuity Scale: associations with admission, disposition, mortality and length of stay in the emergency department

OBJECTIVE

The Korean Triage and Acuity Scale (KTAS) was implemented in our emergency department (ED) in May 2016 and is fully integrated into the electronic medical record (EMR) system. Our objective was to determine whether the KTAS is associated with changes in admissions to the hospital, admission disposition, inpatient mortality and length of stay (LOS).

DESIGN

Quasi-experimental, uncontrolled before-and-after study.

SETTING

The urban tertiary teaching hospital with 1100 beds and receives approximately annual 90 000 ED visits.

PARTICIPANTS

122 370 patients who visited the ED during the before-and-the after period.

INTERVENTIONS

ED staff were educated on the KTAS for 1 month, after which the KTAS evaluation period began. Admission, disposition, mortality and LOS were compared between the 'before' period (1 June 2015 to 30 April 2016) and the 'after' period (1 June 2016 to 30 April 2017).

MAIN OUTCOME MEASURES

Admissions to the hospital, admission disposition, inpatient mortality and LOS.

RESULTS

A total of 59 220 and 63 150 patients were included in the before-and-after periods of KTAS implementation, respectively. The pattern of admission and disposition changed significantly after implementation of the KTAS. The mean LOS was 343 min (standard deviation [SD] = 432 min) during the before period, which significantly decreased to 289 min (SD = 333 min) after implementation (P < 0.001). The total mortality rate was significantly reduced after implementation of the KTAS (213 (0.36%) vs. 179 (0.28%), P = 0.020).

CONCLUSION

Implementation of the KTAS changed admission and disposition patterns and reduced the LOS and mortality in the ED.

Two-step predictive model for early detection of emergency department patients with prolonged stay and its management implications

OBJECTIVE

To develop a novel model for predicting Emergency Department (ED) prolonged length of stay (LOS) patients upon triage completion, and further investigate the benefit of a targeted intervention for patients with prolonged ED LOS.

MATERIALS AND METHODS

A two-step model to predict patients with prolonged ED LOS (>16 h) was constructed. This model was initially used to predict ED resource usage and was subsequently adapted to predict patient ED LOS based on the number of ED resources using binary logistic regressions and was validated internally with accuracy. Finally, a discrete event simulation was used to move patients with predicted prolonged ED LOS directly to a virtual Clinical Decision Unit (CDU). The changes of ED crowding status (Overcrowding, Crowding, and Not-Crowding) and savings of ED bed-hour equivalents were estimated as the measures of the efficacy of this intervention.

RESULTS

We screened a total of 123,975 patient visits with final enrollment of 110,471 patient visits. The overall accuracy of the final model predicting prolonged patient LOS was 67.8%. The C-index of this model ranges from 0.72 to 0.82. By implementing the proposed intervention, the simulation showed a 12% (1044/8760) reduction of ED overcrowded status - an equivalent savings of 129.3 ED bed-hours per day.

CONCLUSIONS

Early prediction of prolonged ED LOS patients and subsequent (simulated) early CDU transfer could lead to more efficiently utilization of ED resources and improved efficacy of ED operations. This study provides evidence to support the implementation of this novel intervention into real healthcare practice.

Indirect impact of violent events on emergency department utilization and disease patterns

Background

The health effects of war and armed conflict on casualties and mental health of those directly exposed has been well described, but few studies have explored the indirect health effects of violent events. This paper assesses the indirect health impact of several violent events that took place in Beirut in 2013–2014 on ED visit utilization and disease patterns.

Methods

As tracked by media reports, there were 9 violent events in Beirut during 2013–2014. We compared visits to the Emergency Department of a major medical center during weeks when violent events happened and weeks without such events (the preceding week and the same week in preceding years). After re-coding de-identified data from the medical records of 23,067 patients, we assessed differences in the volume of visits, severity index, and discharge diagnoses. Individual control charts were used to analyze ED visit trends post-event.

Results

Comparisons of weeks with violent events and weeks without such events indicate that the socio-demographic characteristics of patients who visited the Emergency Department were similar. Patients seen during violent weeks were significantly more likely to be admitted to the hospital, and less likely to present with low acuity complaints, indicating greater complexity of their conditions. The discharge diagnoses that were significantly higher during violent event weeks included anxiety disorders, sprains, and gastritis. Daily ED visits dropped post events by 14.111%, p < 0.0001.

Conclusions

The results indicate that violent events such as bombs, explosions, and terrorist attacks reverberate through the population, impact patterns of ED utilization immediately post-event and are associated with adverse health outcomes, even among those who are not directly affected by the events.

Use of natural language processing to improve predictive models for imaging utilization in children presenting to the emergency department

OBJECTIVE

To examine the association between the medical imaging utilization and information related to patients' socioeconomic, demographic and clinical factors during the patients' ED visits; and to develop predictive models using these associated factors including natural language elements to predict the medical imaging utilization at pediatric ED.

METHODS

Pediatric patients' data from the 2012-2016 United States National Hospital Ambulatory Medical Care Survey was included to build the models to predict the use of imaging in children presenting to the ED. Multivariable logistic regression models were built with structured variables such as temperature, heart rate, age, and unstructured variables such as reason for visit, free text nursing notes and combined data available at triage. NLP techniques were used to extract information from the unstructured data.

RESULTS

Of the 27,665 pediatric ED visits included in the study, 8394 (30.3%) received medical imaging in the ED, including 6922 (25.0%) who had an X-ray and 1367 (4.9%) who had a computed tomography (CT) scan. In the predictive model including only structured variables, the c-statistic was 0.71 (95% CI: 0.70-0.71) for any imaging use, 0.69 (95% CI: 0.68-0.70) for X-ray, and 0.77 (95% CI: 0.76-0.78) for CT. Models including only unstructured information had c-statistics of 0.81 (95% CI: 0.81-0.82) for any imaging use, 0.82 (95% CI: 0.82-0.83) for X-ray, and 0.85 (95% CI: 0.83-0.86) for CT scans. When both structured variables and free text variables were included, the c-statistics reached 0.82 (95% CI: 0.82-0.83) for any imaging use, 0.83 (95% CI: 0.83-0.84) for X-ray, and 0.87 (95% CI: 0.86-0.88) for CT.

CONCLUSIONS

Both CT and X-rays are commonly used in the pediatric ED with one third of the visits receiving at least one. Patients' socioeconomic, demographic and clinical factors presented at ED triage period were associated with the medical imaging utilization. Predictive models combining structured and unstructured variables available at triage performed better than models using structured or unstructured variables alone, suggesting the potential for use of NLP in determining resource utilization.

Patient classification based on volume and case-mix in the emergency department and their association with performance

Predicting daily patient volume is necessary for emergency department (ED) strategic and operational decisions, such as resource planning and workforce scheduling. For these purposes, forecast accuracy requires understanding the heterogeneity among patients with respect to their characteristics and reasons for visits. To capture the heterogeneity among ED patients (case-mix), we present a patient coding and classification scheme (PCCS) based on patient demographics and diagnostic information. The proposed PCCS allows us to mathematically formalize the arrival patterns of the patient population as well as each class of patients. We can then examine the volume and case-mix of patients presenting to an ED and investigate their relationship to the ED's quality and time-based performance metrics. We use data from five hospitals in February, July and November for the years of 2007, 2012, and 2017 in the city of Calgary, Alberta, Canada. We find meaningful arrival time patterns of the patient population as well as classes of patients in EDs. The regression results suggest that patient volume is the main predictor of time-based ED performance measures. Case-mix is, however, the key predictor of quality of care in EDs. We conclude that considering both patient volume and the mix of patients are necessary for more accurate strategic and operational planning in EDs.

Emergency Department Management of Bronchiolitis in the United States

OBJECTIVE

The aim of this study was to examine differences between general and pediatric emergency departments (PEDs) in adherence to the American Academy of Pediatrics bronchiolitis management guidelines.

METHODS

We conducted a nationally representative study of ED visits by infants younger than 24 months with bronchiolitis from 2002 to 2011 using the National Hospital Ambulatory Medical Care Survey. Diagnostic testing (complete blood counts, radiographs) and medication use (albuterol, corticosteroids, antibiotics and intravenous fluids) in general emergency departments (GEDs) were compared with those in PEDs before and after 2006 American Academy of Pediatrics guideline publication. Weighted percentages were compared, and logistic regression evaluated the association between ED type and resource use.

RESULTS

Of more than 2.5 million ED visits for bronchiolitis from 2002 to 2011, 77.3% occurred in GEDs. General emergency departments were more likely to use radiography (62.7% vs 42.1%; adjusted odds ratio [aOR], 2.4; 95% confidence interval [CI], 1.4-4.1), antibiotics (41.3% vs 18.8%; aOR, 2.8; 95% CI, 1.5-5.2), and corticosteroids (24.3% vs 12.5%; aOR, 2.1; 95% CI, 1.0-4.5) compared with PEDs. Compared with preguideline, after guideline publication PEDs had a greater decrease in radiography use (-19.7%; 95% CI, -39.3% to -0.03%) compared with GEDs (-12.2%; 95% CI, -22.3% to -2.1%), and PEDs showed a significant decline in corticosteroid use (-12.4%; 95% CI, -22.1% to -2.8%), whereas GEDs showed no significant decline (-4.6%; 95% CI, -13.5% to 4.3%).

CONCLUSIONS

The majority of ED visits for bronchiolitis in the United States occurred in GEDs, yet GEDs had increased use of radiography, corticosteroids, and antibiotics and did not show substantial declines with national guideline publication. Given that national guidelines discourage the use of such tests and treatments in the management of bronchiolitis, efforts are required to decrease ED use of these resources in infants with bronchiolitis, particularly in GEDs.

Racial/Ethnic Variation in Emergency Department Care for Children With Asthma

OBJECTIVE

To assess the variation between racial/ethnic groups in emergency department (ED) treatment of asthma for pediatric patients.

METHODS

This study was a cross-sectional analysis of pediatric (2-18 years) asthma visits among 6 EDs in the Upper Midwest between June 2011 and May 2012. We used mixed-effects logistic regression to assess the odds of receiving steroids, radiology tests, and returning to the ED within 30 days. We conducted a subanalysis of asthma visits where patients received at least 1 albuterol treatment in the ED.

RESULTS

The sample included 2909 asthma visits by 1755 patients who were discharged home from the ED. After adjusting for demographics, insurance type, and triage score, African American (adjusted odds ratio [aOR], 1.78; 95% confidence interval [CI], 1.40-2.26) and Hispanic (aOR, 1.64; 95% CI, 1.22-2.22) patients had higher odds of receiving steroids compared with whites. African Americans (aOR, 0.58; 95% CI, 0.46-0.74) also had lower odds of radiological testing compared with whites. Asians had the lowest odds of 30-day ED revisits (aOR, 0.26; 95% CI, 0.08-0.84), with no other significant differences detected between racial/ethnic groups. Subgroup analyses of asthma patients who received albuterol revealed similar results, with American Indians showing lower odds of radiological testing as well (aOR, 0.47; 95% CI, 0.22-1.01).

CONCLUSIONS

In this study, children from racial/ethnic minority groups had higher odds of steroid administration and lower odds of radiological testing compared with white children. The underlying reasons for these differences are likely multifactorial, including varying levels of disease severity, health literacy, and access to care.

A National Study of U.S. Emergency Departments: Racial Disparities in Hospitalizations for Heart Failure

INTRODUCTION

Racial disparities in heart failure hospitalizations are well documented. The majority of heart failure hospitalizations originate from emergency departments, but emergency department hospitalization patterns for heart failure and the factors that influence hospitalization are poorly understood. This gap in knowledge was examined using a nationally representative sample of emergency department visits for heart failure.

METHODS

National Hospital Ambulatory Medicare Care Survey data on 2001-2010 emergency department visits were analyzed in 2015-2017 to examine age-related racial differences in hospitalization patterns for heart failure, using multivariable modified Poisson regression models.

RESULTS

More than 12million adult visits for heart failure to U.S. emergency departments occurred from 2001 to 2010, with 23% of visits by blacks. Overall, 71% of visits resulted in hospitalization (57% to floor beds and 14% to intensive care units). Among floor admissions for higher clinical acuity visits, whites were more likely than blacks to be hospitalized. Whites with higher clinical acuity were more likely to be hospitalized than those with lower clinical acuity (71% vs 63%, p=0.005). This expected pattern was not observed in blacks, particularly those aged ≥65years, who were hospitalized in 71% of lower clinical acuity visits, but only 61% of higher acuity visits. Among adults aged ≥65years, there was a significant interaction between clinical acuity Xrace with regard to hospitalization (p=0.037).

CONCLUSIONS

These results suggest age and racial disparities in hospitalization rates for emergency department patients with heart failure. The reasons for these disparities in hospitalization are unclear. Further studies on emergency department hospitalization decisions, and the impact of emergency department clinical factors, may help clarify this finding.

SUPPLEMENT INFORMATION

This article is part of a supplement entitled African American Men's Health: Research, Practice, and Policy Implications, which is sponsored by the National Institutes of Health.

NHAMCS Validation of Emergency Severity Index as an Indicator of Emergency Department Resource Utilization

Introduction

Triage systems play a vital role in emergency department (ED) operations and can determine how well a given ED serves its local population. We sought to describe ED utilization patterns for different triage levels using the National Hospital Ambulatory Medical Care Survey (NHAMCS) database.

Methods

We conducted a multi-year secondary analysis of the NHAMCS database from 2009-2011. National visit estimates were made using standard methods in Analytics Software and Solutions (SAS, Cary, NC). We compared patients in the mid-urgency range in regard to ED lengths of stay, hospital admission rates, and numbers of tests and procedures in comparison to lower or higher acuity levels.

Results

We analyzed 100,962 emergency visits (representing 402,211,907 emergency visits nationwide). In 2011, patients classified as triage levels 1–3 had a higher number of diagnoses (5.5, 5.6 and 4.2, respectively) when compared to those classified as levels 4 and 5 (1.61 and 1.25). This group also underwent a higher number of procedures (1.0, 0.8 and 0.7, versus 0.4 and 0.4), had a higher ED length of stay (220, 280 and 237, vs. 157 and 135), and admission rates (32.2%, 32.3% and 15.5%, vs. 3.1% and 3.6%).

Conclusion

Patients classified as mid-level (3) triage urgency require more resources and have higher indicators of acuity as those in triage levels 4 and 5. These patients’ indicators are more similar to those classified as triage levels 1 and 2.

Effects of medical scribes on physician productivity in a Canadian emergency department: a pilot study

BACKGROUND

Emergency department efficiency is a priority across Canada. In the United States, scribes may increase the number of patients seen per hour per physician; however, Canadian data are lacking. We sought to implement scribes in a Canadian emergency department with the hypothesis that scribes would increase the number of patients seen per hour per physician.

METHODS

We conducted a 4-month quality improvement pilot study in a community emergency department in Ottawa, Ontario. Data collection began January 2015 after scribe training. Physicians received shifts with and without a scribe for a period of 4 months. Across the study, the mean number of patients seen per hour was determined for each physician during shifts with and without a scribe. We compared mean (± standard deviation [SD]) number of patients seen per hour based on presence or absence of a scribe by 2-tailed paired-samples t test.

RESULTS

Eleven scribes participated and ranged in age from 18 to 23 years. Twenty-two full- or part-time emergency physicians were followed. We documented 463 physician-hours without use of a scribe and 693.75 physician-hours with use of a scribe. Across all 22 physicians, 18 (81.8%) saw more patients per hour with use of a scribe. Overall, the number of patients seen per hour per physician was significantly greater (+12.9%) during shifts with a scribe (mean [± SD] 2.81 [± 0.78]) than during shifts without a scribe (mean [± SD] 2.49 [± 0.60]; p = 0.006).

INTERPRETATION

In this pilot study, the use of scribes resulted in an increased number of patients seen per hour per physician. Because this was a small study at a single centre, further research on the effects of scribes in Canada is warranted.

Simulation-Based Design of ED Operations with Care Streams to Optimize Care Delivery and Reduce Length of Stay in the Emergency Department

Faced with the opportunity to significantly deviate from classic operations, a new emergency department (ED) and novel strategy for patient care delivery were simultaneously initiated with the aid of model-based simulation. To answer the design and implementation questions, a traditional strategy for construction of discrete-eventmodel simulation was employed to define ED operations for a newly constructed facility in terms of workflow, variables, resources, structure, process logic and associated assumptions. Benefits were achieved before, during and after implementation of an unprecedented operations strategy-i.e., the organization of the ED care delivery around four care streams: Critical, Diagnostic, Therapeutic and Fast Track. Prior to opening, it shed light on the range of context variables where benefits might be anticipated, and it facilitated staff understanding and judgements of performance. Two years after opening, the operations data is compared to the simulation with encouraging results that shed light on where to continue pursuit of improvement.

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks

OBJECTIVE

To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural language processing elements.

METHODS

Using data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), a cross-sectional probability sample of United States EDs from 2012 and 2013 survey years, we developed several predictive models with the outcome being admission to the hospital or transfer vs. discharge home. We included patient characteristics immediately available after the patient has presented to the ED and undergone a triage process. We used this information to construct logistic regression (LR) and multilayer neural network models (MLNN) which included natural language processing (NLP) and principal component analysis from the patient's reason for visit. Ten-fold cross validation was used to test the predictive capacity of each model and receiver operating curves (AUC) were then calculated for each model.

RESULTS

Of the 47,200 ED visits from 642 hospitals, 6,335 (13.42%) resulted in hospital admission (or transfer). A total of 48 principal components were extracted by NLP from the reason for visit fields, which explained 75% of the overall variance for hospitalization. In the model including only structured variables, the AUC was 0.824 (95% CI 0.818-0.830) for logistic regression and 0.823 (95% CI 0.817-0.829) for MLNN. Models including only free-text information generated AUC of 0.742 (95% CI 0.731- 0.753) for logistic regression and 0.753 (95% CI 0.742-0.764) for MLNN. When both structured variables and free text variables were included, the AUC reached 0.846 (95% CI 0.839-0.853) for logistic regression and 0.844 (95% CI 0.836-0.852) for MLNN.

CONCLUSIONS

The predictive accuracy of hospital admission or transfer for patients who presented to ED triage overall was good, and was improved with the inclusion of free text data from a patient's reason for visit regardless of modeling approach. Natural language processing and neural networks that incorporate patient-reported outcome free text may increase predictive accuracy for hospital admission.

Five-level emergency triage systems: variation in assessment of validity

INTRODUCTION

Triage systems are scales developed to rate the degree of urgency among patients who arrive at EDs. A number of different scales are in use; however, the way in which they have been validated is inconsistent. Also, it is difficult to define a surrogate that accurately predicts urgency. This systematic review described reference standards and measures used in previous validation studies of five-level triage systems.

METHODS

We searched PubMed, EMBASE and CINAHL to identify studies that had assessed the validity of five-level triage systems and described the reference standards and measures applied in these studies. Studies were divided into those using criterion validity (reference standards developed by expert panels or triage systems already in use) and those using construct validity (prognosis, costs and resource use).

RESULTS

A total of 57 studies examined criterion and construct validity of 14 five-level triage systems. Criterion validity was examined by evaluating (1) agreement between the assigned degree of urgency with objective standard criteria (12 studies), (2) overtriage and undertriage (9 studies) and (3) sensitivity and specificity of triage systems (7 studies). Construct validity was examined by looking at (4) the associations between the assigned degree of urgency and measures gauged in EDs (48 studies) and (5) the associations between the assigned degree of urgency and measures gauged after hospitalisation (13 studies). Particularly, among 46 validation studies of the most commonly used triages (Canadian Triage and Acuity Scale, Emergency Severity Index and Manchester Triage System), 13 and 39 studies examined criterion and construct validity, respectively.

CONCLUSION

Previous studies applied various reference standards and measures to validate five-level triage systems. They either created their own reference standard or used a combination of severity/resource measures.

Traditional Risk Indices as Predictors of Future Utilization and Charges in the Context of Population Health for an Uninsured Cohort

INTRODUCTION

The uninsured population presents unique challenges to the application of an integrated approach to population health. Our objective is to compare and test population risk indices for identifying a cohort of uninsured patients at high-risk for avoidable healthcare utilization and costs.

METHODS

Patients who had a least one visit at a safety-net clinic, had a primary address in Mecklenburg County, were aged 18-74, and had the most recent healthcare visit coded as 'uninsured' were identified in the baseline period. The five risk indices used were: the HHS Hierarchical Conditions Category (HCC), the Charlson Comorbidity Index (CCI), Total Cost Index, Total Inpatient Visits Index, and Total Emergency Department Visits Index. First, agreement across the five indices was analyzed. Then, the accuracy of the five risk indices was tested in predicting future utilization and costs for the subsequent 12-month follow-up period.

RESULTS

Kappa statistics and percent overlap values showed below average to poor agreement between indices when comparing scorers.The strongest predictors of being in the 90th percentile of total cost during the 12 months follow-up period were the Total Cost Index at baseline (C statistic=0.75) and the HCC (C-statistic=0.73). The CCI and Total Inpatient Visit Index's demonstrated the lowest accuracy for predicting an unnecessary ED visit (C-statistic=0.51, for both).

DISCUSSION/CONCLUSION

Prior cost and ED utilization were key in predicting their corresponding 12-month metrics. In contrast, the Total Inpatient Visit Index had the worst predictive performance for future hospitalization rates. Some indices were similarly predictive as compared to insured cohorts but others showed contrasting results.

Proposing a two-criterion quality loss function using critical process capability indices

Purpose

Average quadratic quality loss function (QQLF) measures quality of a given process using mean shift from its target value and variance. While it has a target parameter for the mean, it lacks a target for the variance revisable for counting any progress of the process across different quality levels, above/below the standard level; thus, it appears too general. Hence, in this research, it was initially supposed that all processes are located at two possible quality spaces, above/below the standard level. The purpose of this paper is to propose a two-criterion QQLF, in which each criterion is specifically proper to one of the quality spaces.

Design/methodology/approach

Since 1.33 is a literarily standard or satisfactory value for two most important process capability indicesCpandCpk, its upper/lower spaces are assumed as high-/low-quality spaces. Then the indices are integrated into traditional QQLF, of type nominal the best (NTB), to develop a two-criterion QQLF, in which each criterion is more suitable for each quality space. These two criteria have also been innovatively embedded in the plan-do-check-act (PDCA) cycle to help continuous improvement. Finally, the proposed function has been examined in comparison with the traditional one in Feiz Hospital in the province of Isfahan, Iran.

Findings

Results indicate that the internal process of the studied case is placed on the lower quality space. So the first criterion of revised QQLF gives a more relevant evaluation for that process, compared with the traditional function. Moreover, this study has embedded both proposed criteria in the PDCA cycle as well.

Research limitations/implications

Formulating the two-criterion QQLF only for observations of normal and symmetric distributions, and offering it solely for NTB characteristics are limitations of this study.

Practical implications

Two more relevant quality loss criteria have been formulated for each process (service or manufacturing). However, in order to show the comprehensiveness of the proposed method even in service institutes, emergency function of Feiz Hospital has been examined.

Originality/value

The traditional loss function of type NTB merely and implicitly targets zero defect for variance. In fact, it calculates quality loss of all processes placed on different quality spaces using a same measure. This study, however, provides a practitioner with opportunity of targeting excellent or satisfactory targets.

Association of Bronchiolitis Clinical Pathway Adherence With Length of Stay and Costs

OBJECTIVES

To examine the associations between the level of adherence to bronchiolitis clinical pathway recommendations, health care use, and costs.

METHODS

We conducted a retrospective cohort study of 267 patients ≤24 months old diagnosed with bronchiolitis from 12/2009 to 7/2012. Clinical pathway adherence was assessed by using a standardized scoring system (0-100) for 18 quality measures obtained by medical record review. Level of adherence was categorized into low, middle, and high tertiles. Generalized linear models were used to examine relationships between adherence tertile and (1) length of stay (LOS) and (2) costs. Logistic regression was used to examine the associations between adherence tertile and probability of inpatient admission and 7-day readmissions.

RESULTS

Mean adherence scores were: ED, 78.8 (SD, 18.1; n = 264), inpatient, 95.0 (SD, 6.3; n = 216), and combined ED/inpatient, 89.1 (SD, 8.1; n = 213). LOS was significantly shorter for cases in the highest versus the lowest adherence tertile (ED, 90 vs 140 minutes, adjusted difference, -51 [95% confidence interval (CI), -73 to -29; P <.05]; inpatient, 3.1 vs 3.8 days, adjusted difference, -0.7 [95% CI, -1.4 to 0.0; P <.05]). Costs were less for cases in the highest adherence tertile (ED, -$84, [95% CI, -$7 to -$161; P <.05], total, -$1296 [95% CI, -126.43 to -2466.03; P <.05]). ED cases in the highest tertile had a lower odds of admission (odds ratio, 0.38 [95% CI, 0.15-0.97; P < .05]). Readmissions did not differ by tertile.

CONCLUSIONS

High adherence to bronchiolitis clinical pathway recommendations across care settings was associated with shorter LOS and lower cost.

The Copenhagen Triage Algorithm: a randomized controlled trial

BACKGROUND

Crowding in the emergency department (ED) is a well-known problem resulting in an increased risk of adverse outcomes. Effective triage might counteract this problem by identifying the sickest patients and ensuring early treatment. In the last two decades, systematic triage has become the standard in ED's worldwide. However, triage models are also time consuming, supported by limited evidence and could potentially be of more harm than benefit. The aim of this study is to develop a quicker triage model using data from a large cohort of unselected ED patients and evaluate if this new model is non-inferior to an existing triage model in a prospective randomized trial.

METHODS

The Copenhagen Triage Algorithm (CTA) study is a prospective two-center, cluster-randomized, cross-over, non-inferiority trial comparing CTA to the Danish Emergency Process Triage (DEPT). We include patients ≥16 years (n = 50.000) admitted to the ED in two large acute hospitals. Centers are randomly assigned to perform either CTA or DEPT triage first and then use the other triage model in the last time period. The CTA stratifies patients into 5 acuity levels in two steps. First, a scoring chart based on vital values is used to classify patients in an immediate category. Second, a clinical assessment by the ED nurse can alter the result suggested by the score up to two categories up or one down. The primary end-point is 30-day mortality and secondary end-points are length of stay, time to treatment, admission to intensive care unit, and readmission within 30 days.

DISCUSSION

If proven non-inferior to standard DEPT triage, CTA will be a faster and simpler triage model that is still able to detect the critically ill. Simplifying triage will lessen the burden for the ED staff and possibly allow faster treatment.

TRIAL REGISTRATION

Clinicaltrials.gov: NCT02698319 , registered 24. of February 2016, retrospectively registered.

One-two-triage: validation and reliability of a novel triage system for low-resource settings

Objectives

To validate and assess reliability of a novel triage system, one-two-triage (OTT), that can be applied by inexperienced providers in low-resource settings.

Methods

This study was a two-phase prospective, comparative study conducted at three hospitals. Phase I assessed criterion validity of OTT on all patients arriving at an American university hospital by comparing agreement among three methods of triage: OTT, Emergency Severity Index (ESI) and physician-defined acuity (the gold standard). Agreement was reported in normalised and raw-weighted Cohen κ using two different scales for weighting, Expert-weighted and triage-weighted κ. Phase II tested reliability, reported in Fleiss κ, of OTT using standardised cases among three groups of providers at an urban and rural Cambodian hospital and the American university hospital.

Results

Normalised for prevalence of patients in each category, OTT and ESI performed similarly well for expert-weighted κ (OTT κ=0.58, 95% CI 0.52 to 0.65; ESI κ=0.47, 95% CI 0.40 to 0.53) and triage-weighted κ (κ=0.54, 95% CI 0.48 to 0.61; ESI κ=0.57, 95% CI 0.51 to 0.64). Without normalising, agreement with gold standard was less for both systems but performance of OTT and ESI remained similar, expert-weighted (OTT κ=0.57, 95% CI 0.52 to 0.62; ESI κ=0.6, 95% CI 0.58 to 0.66) and triage-weighted (OTT κ=0.31, 95% CI 0.25 to 0.38; ESI κ=0.41, 95% CI 0.35 to 0.4). In the reliability phase, all triagers showed fair inter-rater agreement, Fleiss κ (κ=0.308).

Conclusions

OTT can be reliably applied and performs as well as ESI compared with gold standard, but requires fewer resources and less experience.

Distribution and predictors of emergency department charges: the case of a tertiary hospital in Lebanon

Background

As health care costs continue to increase worldwide, health care systems, and more specifically hospitals are facing continuous pressure to operate more efficiently. One service within the hospital sector whose cost structure has been modestly investigated is the Emergency Department (ED). The study aims to report on the distribution of ED resource use, as expressed in charges, and to determine predictors of/contributors to total ED charges at a major tertiary hospital in Lebanon.

Methods

The study used data extracted from the ED discharge database for visits between July 31, 2012 and July 31, 2014. Patient visit bills were reported under six major categories: solutions, pharmacy, laboratory, physicians, facility, and radiology. Characteristics of ED visits were summarized according to patient gender, age, acuity score, and disposition. Univariate and multivariate analyses were conducted with total charges as the dependent variable.

Results

Findings revealed that the professional fee (40.9 %) followed by facility fee (26.1 %) accounted for the majority of the ED charges. While greater than 80 % of visit charges went to physician and facility fee for low acuity cases, these contributed to only 52 and 54 % of the high acuity presentations where ancillary services and solutions’ contribution to the total charges increased. The total charges for males were $14 higher than females; age was a predictor of higher charges with total charges of patients greater than 60 years of age being around $113 higher than ages 0–18 after controlling for all other variables.

Conclusion

Understanding the components and determinants of ED charges is essential to developing cost-containment interventions. Institutional modeling of charging patterns can be used to offer price estimates to ED patients who request this information and ultimately help create market competition to drive down costs.

Ethnic Disparities in Emergency Severity Index Scores among U.S. Veteran's Affairs Emergency Department Patients

BACKGROUND

The goal of these analyses was to determine whether there were systematic differences in Emergency Severity Index (ESI) scores, which are intended to determine priority of treatment and anticipate resource needs, across categories of race and ethnicity, after accounting for patient-presenting vital signs and examiner characteristics, and whether these differences varied among male and female Veterans Affairs (VA) ED patients.

METHODS AND FINDINGS

We used a large national database of electronic medical records of ED patients from twenty-two U.S. Department of Veterans Affairs ED stations to determine whether ESI assignments differ systematically by race or ethnicity. Multi-level, random effects linear modeling was used to control for demographic characteristics and patient's vital signs (heart rate, respiratory rate, and pain level), as well as age, gender, and experience of triage nurses. The dataset included 129,991 VA patients presenting for emergency care between 2008 and 2012 (91% males; 61% non-Hispanic White, 28% Black, 7% Hispanic, 2% Asian, <1% American Indian/Alaska Native, 1% mixed ethnicity) and 774 nurses for a total of 359,642 patient/examiner encounters. Approximately 13% of the variance in ESI scores was due to patient characteristics and 21% was due to the nurse characteristics. After controlling for characteristics of nurses and patients, Black patients were assigned less urgent ESI scores than White patients, and this effect was more prominent for Black males compared with Black females. A similar interaction was found for Hispanic males. It remains unclear how these results may generalize to EDs and patient populations outside of the U.S. VA Health Care system.

CONCLUSIONS

The findings suggest the possibility that subgroups of VA patients receive different ESI ratings in triage, which may have cascading, downstream consequences for patient treatment quality, satisfaction with care, and trust in the health equity of emergency care.

Outcomes for emergency severity index triage implementation in the emergency department

INTRODUCTION

Hospital triage scale in emergency departments needs to be valid and reliable. Lack of sufficient data exists on triage scale rigor in emergency departments of Iran. This study aimed to determine the impact of the emergency severity index (ESI) triage scale in the emergency department.

MATERIALS AND METHODS

A single-center study was conducted. Proportion of triage categories allocated to high-risk patients admitted to high-acuity departments was examined in observational period in June 2012 and May 2013. True triage score was reported based on patients` paper- based scenario questionnaire. Interrater reliability was assessed using unweighted kappa. Concordance among experts, nurses and physicians was examined. The Chi-square test and Kappa statistics was used for statistical analysis.

RESULTS

Triage decisions regarding high-risk patients before and after implementation period are independent from each other (χ2= 22.254; df=1; p<0.05) and more high-risk patients were recognized after implementation of the ESI. Overall agreement and concordance were (79%) and (κ=0.54) among nurses; (71%) and (κ=0.45) among physicians, (85%) and (κ=0.81) among experts, respectively. Correct triage decisions among clinicians were increased after implementation of the ESI.

CONCLUSION

The ESI as valid and reliable tool improving desirable outcomes` in the emergency department has been recommended but it may not reveal optimal outcomes in developing countries comparing to what have been achieved in the developed countries. In addition, patient influx in ESI level II could create considerable controversy with clinicians.

Does active dissemination of evidence result in faster knowledge transfer than passive diffusion?: An analysis of trends of the management of pediatric asthma and croup in US emergency departments from 1995 to 2009

OBJECTIVE

This study aimed to compare knowledge transfer (KT) in the emergency department (ED) management of pediatric asthma and croup by measuring trends in corticosteroid use for both conditions in EDs.

METHODS

A retrospective, cross-sectional study of the National Hospital Ambulatory Medical Care Survey data between 1995 and 2009 of corticosteroid use at ED visits for asthma or croup was conducted. Odds ratios (OR) were calculated using logistic regression. Trends over time were compared using an interaction term between disease and year and were adjusted for all other covariates in the model. We included children aged 2 to 18 years with asthma who received albuterol and were triaged emergent/urgent. Children aged between 3 months to 6 years with croup were included. The main outcome measure was the administration of corticosteroids in the ED or as a prescription at the ED visit.

RESULTS

The corticosteroid use in asthma visits increased from 44% to 67% and from 32% to 56% for croup. After adjusting for patient and hospital factors, this trend was significant both for asthma (OR, 1.07; 95% confidence interval [CI], 1.04-1.10) and croup (OR, 1.07; 95% CI, 1.03-1.12). There was no statistical difference between the 2 trends (P = 0.69). Hospital location in a metropolitan statistical area was associated with increased corticosteroid use in asthma (OR, 1.76; 95% CI, 1.10-2.82). Factors including sex, ethnicity, insurance, or region of the country were not significantly associated with corticosteroid use.

CONCLUSIONS

During a 15-year period, knowledge transfer by passive diffusion or active guideline dissemination resulted in similar trends of corticosteroid use for the management of pediatric asthma and croup.

Dynamic patient grouping and prioritization: a new approach to emergency department flow improvement

The demand on emergency departments (ED) is variable and ever increasing, often leaving them overcrowded. Many hospitals are utilizing triage algorithms to rapidly sort and classify patients based on the severity of their injury or illness, however, most current triage methods are prone to over- or under-triage. In this paper, the group technology (GT) concept is applied to the triage process to develop a dynamic grouping and prioritization (DGP) algorithm. This algorithm identifies most appropriate patient groups and prioritizes them according to patient- and system-related information. Discrete event simulation (DES) has been implemented to investigate the impact of the DGP algorithm on the performance measures of the ED system. The impact was studied in comparison with the currently used triage algorithm, i.e., emergency severity index (ESI). The DGP algorithm outperforms the ESI algorithm by shortening patients' average length of stay (LOS), average time to bed (TTB), time in emergency room, and lowering the percentage of tardy patients and their associated risk in the system.

Malnutrition among cognitively intact, noncritically ill older adults in the emergency department

STUDY OBJECTIVE

We estimate the prevalence of malnutrition among older patients presenting to an emergency department (ED) in the southeastern United States and identify subgroups at increased risk.

METHODS

We conducted a cross-sectional study with random time block sampling of cognitively intact patients aged 65 years and older. Nutrition was assessed with the Mini Nutritional Assessment Short-Form (0 to 14 scale), with malnutrition defined as a score of 7 or less and at risk for malnutrition defined as a score of 8 to 11. The presence of depressive symptoms was defined as a Center for Epidemiological Studies Depression-10 score of 4 or more (0 to 10 scale).

RESULTS

Among 138 older adults, 16% (95% confidence interval [CI] 11% to 23%) were malnourished and 60% (95% CI 52% to 68%) were either malnourished or at risk for malnutrition. Seventeen of the 22 malnourished patients (77%) denied previously receiving a diagnosis of malnutrition. The prevalence of malnutrition was not appreciably different between men and women, across levels of patient education, or between those living in urban and rural areas. However, the prevalence of malnutrition was higher among patients with depressive symptoms (52%), those residing in assisted living (44%), those with difficulty eating (38%), and those reporting difficulty buying groceries (33%).

CONCLUSION

Among a random sample of cognitively intact older ED patients, more than half were malnourished or at risk for malnutrition, and the majority of malnourished patients had not previously received a diagnosis. Higher rates of malnutrition among individuals with depression, difficulty eating, and difficulty buying groceries suggest the need to explore multifaceted interventions.

A flexible simulation platform to quantify and manage emergency department crowding

BACKGROUND

Hospital-based Emergency Departments are struggling to provide timely care to a steadily increasing number of unscheduled ED visits. Dwindling compensation and rising ED closures dictate that meeting this challenge demands greater operational efficiency.

METHODS

Using techniques from operations research theory, as well as a novel event-driven algorithm for processing priority queues, we developed a flexible simulation platform for hospital-based EDs. We tuned the parameters of the system to mimic U.S. nationally average and average academic hospital-based ED performance metrics and are able to assess a variety of patient flow outcomes including patient door-to-event times, propensity to leave without being seen, ED occupancy level, and dynamic staffing and resource use.

RESULTS

The causes of ED crowding are variable and require site-specific solutions. For example, in a nationally average ED environment, provider availability is a surprising, but persistent bottleneck in patient flow. As a result, resources expended in reducing boarding times may not have the expected impact on patient throughput. On the other hand, reallocating resources into alternate care pathways can dramatically expedite care for lower acuity patients without delaying care for higher acuity patients. In an average academic ED environment, bed availability is the primary bottleneck in patient flow. Consequently, adjustments to provider scheduling have a limited effect on the timeliness of care delivery, while shorter boarding times significantly reduce crowding. An online version of the simulation platform is available at http://spark.rstudio.com/klopiano/EDsimulation/.

CONCLUSION

In building this robust simulation framework, we have created a novel decision-support tool that ED and hospital managers can use to quantify the impact of proposed changes to patient flow prior to implementation.

Evaluating implementation of the emergency severity index in a Belgian hospital

INTRODUCTION

Triage aims to categorize patients based on their clinical need and the available departmental resources. To accomplish this goal, one needs to ensure that the implemented triage system is reliable and that staff use it correctly. Therefore this study assessed the ability of Belgium nurses to apply the Emergency Severity Index (ESI), version 4, to hypothetical case scenarios after an educational intervention.

METHODS

An ESI educational intervention was implemented in accordance with the ESI manual. Using paper case scenarios, nurses' interrater agreement was assessed by comparing triage nurse ESI levels with the reference answers noted in the implementation manual. Interrater agreement was measured by the percentage of agreement and Cohen's κ coefficient using different weighting schemes.

RESULTS

Overall, 77.5% of the scenario cases were coded according the ESI guidelines, resulting in a good interrater agreement (κ = 0.72, linear weighted κ = 0.84, quadratic weighted κ = 0.92, and triage-weighted scheme = 0.79). Interrater agreement varied when evaluating each ESI level separately. Undertriage was more common than overtriage. The highest misclassification range (37.8%) occurred in ESI level 2 scenarios, with 99.2% of the misclassifications being undertriaged.

DISCUSSION

Implementation of the ESI into a novel setting guided by a locally developed training program resulted in suboptimal interrater agreement. Existing weighted κ schemes overestimated the interrater agreement between the triage nurse-assigned ESI level and the reference standard. By providing an aggregated measure of agreement, which allows partial agreement, clinically significant misclassification was masked by a misleading "good" interrater agreement.

Gleaning data from disaster: a hospital-based data mining method to study all-hazard triage after a chemical disaster

OBJECTIVE

To describe the methods of evaluating currently available triage models for their efficacy in appropriately triaging the surge of patients after an all-hazards disaster.

DESIGN

A method was developed for evaluating currently available triage models using extracted data from medical records of the victims from the Graniteville chlorine disaster.

SETTING

On January 6, 2005, a freight train carrying three tanker cars of liquid chlorine was inadvertently switched onto an industrial spur in central Graniteville, SC. The train then crashed into a parked locomotive and derailed. This caused one of the chlorine tankers to rupture and immediately release ~60 tons of chlorine. Chlorine gas infiltrated the town with a population of 7,000.

PARTICIPANTS

This research focuses on the victims who received emergency care in South Carolina.

RESULTS

With our data mapping and decision tree logic, the authors were successful in using the available extracted clinical data to estimate triage categories for use in our study.

CONCLUSIONS

The methodology outlined in this article shows the potential use of well-designed secondary analysis methods to improve mass casualty research. The steps are reliable and repeatable and can easily be extended or applied to other disaster datasets.