Emergency Department Patient Volume Research Articles

The 4 S's of Disaster Management Framework: A Case Study of the 2022 Pediatric Tripledemic Response in a Community Hospital

Most children in the United States present to community hospitals for emergency department (ED) care. Those who are acutely ill and require critical care are stabilized and transferred to a tertiary pediatric hospital with intensive care capabilities. During the fall of 2022 "tripledemic," with a marked increase in viral burden, there was a nationwide surge in pediatric ED patient volume. This caused ED crowding and decreased availability of pediatric hospital intensive care beds across the United States. As a result, there was an inability to transfer patients who were critically ill out, and the need for prolonged management increased at the community hospital level. We describe the experience of a Massachusetts community ED during this surge, including the large influx in pediatric patients, the increase in those requiring critical care, and the total number of critical care hours as compared with the same time period (September to December) in 2021. To combat these challenges, the pediatric ED leadership applied a disaster management framework based on the 4 S's of space, staff, stuff, and structure. We worked collaboratively with general emergency medicine leadership, nursing, respiratory therapy, pharmacy, local clinicians, our regional health care coalition, and emergency medical services (EMS) to create and implement the pediatric surge strategy. Here, we present the disaster framework strategy, the interventions employed, and the barriers and facilitators for implementation in our community hospital setting, which could be applied to other community hospital facing similar challenges.

Predicting daily emergency department visits using machine learning could increase accuracy

ObjectiveAdministrators and clinicians alike have attempted to predict emergency department visits for many years. The ability to predict or “forecast” ED visit volume can allow for more efficient resource allocation, including up-staffing or down-staffing, changing OR schedules, and predicting the need for significant resources. The goal of this study is to examine combinations of variables via machine learning to increase prediction accuracy and determine the factors that are most predictive of overall ED visits. As compared to a simple univariate time series model, we hypothesize that machine learning models will predict St. Joseph Mercy Ann Arbor's patient visit load for the emergency department (ED) with higher accuracy than a simple univariate time series model. MethodsUnivariate time series models for daily ED visits, including ARIMA, Exponential Smoothing (ETS), and Facebook Inc.'s prophet algorithm were estimated as a baseline comparison. Machine learning models, including random forests and gradient boosted machines (GBM), were trained using data from 2017 to 2018. After final models were created, they were applied to the 2019 data to determine how well these models predicted actual ED patient volumes in data not utilized during the model fitting process. The accuracy of the machine learning and time series models were assessed based on out-of-sample predictive accuracy, compared using root mean squared error (RMSE). ResultsUsing root mean squared error (RMSE) to assess out-of-sample predictive accuracy of the models, the results showed that the random forest model was the most accurate at predicting daily ED visits in the 2019 test set, followed by the GBM model. These performed only slightly better than the simple exponential smoothing model predictions. The ARIMA model performed poorly in comparison. The day of the week (likely capturing differences between weekdays and weekends) was found to be the most important predictor of patient volumes. Weather-related features such as maximum temperature and SFC pressure appeared to capture some of the seasonality trends related to changes in patient volumes. ConclusionsMachine learning models perform better at predicting daily patient volumes as compared to simple univariate time series models, though not by a substantial amount. Further research can help confirm these limited initial results. Gathering more training data and additional feature engineering could also be beneficial to training the models and potentially improving predictive accuracy.

Impact of COVID-19 Pandemic on Emergency Department Volume and Acuity in Low Incidence Area: Taiwan's Experience in Three Hospitals.

The decrease in emergency department (ED) patient visits during the COVID-19 pandemic was reported by various studies. Our study aimed to investigate whether a similar trend can be observed in a country with a low incidence of COVID-19 as well as the impact caused by the pandemic on ED patients in different triage levels and categories. This multicenter retrospective study collected data from three regional hospitals between March 2019 and December 2020. We evaluated the differences between patient volume, disease severity, and patient composition in ED before and after the COVID-19 pandemic among these hospitals. There was a 23% reduction in ED patient volume in the urban hospital (hospital A) as well as a 16% reduction in suburban hospitals (hospitals B and C) during the pandemic period, respectively. The regression analysis showed a high correlation in the change in monthly patient volume among these hospitals. In terms of severity, there was a 24% reduction in ED visits with high severity levels (Taiwan Triage and Acuity Scale [TTAS] I, II) in hospital A, as well as 16% and 12% in hospitals B and C during the pandemic period, respectively. Similarly, there was a 23% reduction in ED visits with low severity levels (TTAS III, IV, V) in hospital A, as well as 20% and 16% in hospitals B and C during the pandemic period, respectively. In terms of patient types, there was a significant decline in non-traumatic adult patients (19%, 17%, and 10%), and pediatric patients (49%, 50%, and 46%) in hospitals A, B, and C, respectively. Despite the low incidence of COVID-19 in Taiwan, a decrease in total ED visits was still found during the pandemic, especially in non-trauma adult visits and pediatric visits. In addition, ED visits in both high and low severity levels decreased in these regional hospitals.

Integrating Google Trends Search Engine Query Data Into Adult Emergency Department Volume Forecasting: Infodemiology Study.

The search for health information from web-based resources raises opportunities to inform the service operations of health care systems. Google Trends search query data have been used to study public health topics, such as seasonal influenza, suicide, and prescription drug abuse; however, there is a paucity of literature using Google Trends data to improve emergency department patient-volume forecasting. We assessed the ability of Google Trends search query data to improve the performance of adult emergency department daily volume prediction models. Google Trends search query data related to chief complaints and health care facilities were collected from Chicago, Illinois (July 2015 to June 2017). We calculated correlations between Google Trends search query data and emergency department daily patient volumes from a tertiary care adult hospital in Chicago. A baseline multiple linear regression model of emergency department daily volume with traditional predictors was augmented with Google Trends search query data; model performance was measured using mean absolute error and mean absolute percentage error. There were substantial correlations between emergency department daily volume and Google Trends "hospital" (r=0.54), combined terms (r=0.50), and "Northwestern Memorial Hospital" (r=0.34) search query data. The final Google Trends data-augmented model included the predictors Combined 3-day moving average and Hospital 3-day moving average and performed better (mean absolute percentage error 6.42%) than the final baseline model (mean absolute percentage error 6.67%)-an improvement of 3.1%. The incorporation of Google Trends search query data into an adult tertiary care hospital emergency department daily volume prediction model modestly improved model performance. Further development of advanced models with comprehensive search query terms and complementary data sources may improve prediction performance and could be an avenue for further research.

A retrospective multistate analysis: Do regional football games impact emergency department patient volume?

ObjectiveWe sought to assess the effect of National Football League (NFL) games played by a regional sports team, the New England Patriots, on emergency department (ED) patient volume.MethodsWe conducted a multicenter, retrospective chart review at the following 3 tertiary centers in New England from 2012 to 2019: Beth Israel Deaconess Medical Center, Boston, MA; Dartmouth Hitchcock Medical Center, Lebanon, NH; and Maine Medical Center, Portland, ME.ResultsWithin the NFL season, we observed a 2.6% overall decrease (−10.4 patients) in average total daily volume across the study sites on Sundays when Patriots games were played compared with Sundays when games were not played (P = 0.07; 95% confidence interval [CI], −22.37 to 1.62). We observed a 4.3% reduction (−19.0 patients) in average total daily volume across the study sites on Mondays during which Patriots games were played compared with Mondays without games (P = 0.15; 95% CI, −43.51 to 5.47). Subanalyses on the 5‐hour period corresponding with each Patriots game showed reductions in mean patient volume per hour. Although our primary and subanalyses showed reductions in patient volume during Patriots games, these results were not statistically significant.ConclusionsOur data support prior studies that showed a minimal impact of major sporting events on ED patient volume at tertiary centers. These results add to the limited data on this topic and can inform administrators whether staffing adjustments are necessary during similar types of sporting events.

69 Impact of the COVID-19 Pandemic on Workplace Violence at an Academic Emergency Department

Violence in the emergency department (ED) is a common and longstanding threat to staff. The COVID-19 pandemic brought unique challenges; however, it remains unclear what effect the pandemic had on violence in health care. The objective of this study was to identify the impact of the pandemic on workplace violence at an academic emergency department in the Midwest. The hospital referral region (HRR) COVID-19 case rate per 100,000 people was obtained from March through December 2020. Monthly incidents of ED violence were obtained from the Office of Security and included both physical assault and verbal threats where security officers were notified to respond. These incidents were combined with monthly reports of violent flags added to patient charts within the electronic medical record. Overlapping data from both sources were counted only once. Monthly ED patient volume was obtained to calculate a rate of violent incidents per 1,000 ED visits. Two anonymous surveys were sent to all multidisciplinary ED staff both pre/early-pandemic (April 2020) and mid/late-pandemic (December 2020) and surveyed respondents regarding the incidence of verbal abuse and physical assault experienced over the prior 6-months (November 2019-April 2020 and July 2020-December 2020). Chi-squared tests and Fisher’s exact tests were used for comparison. The study was deemed exempt by the Mayo Clinic Institutional Review Board. There was a positive association between the HRR rate and rate of violent ED incidents (r = 0.24; Figure 1). There was also an increase in overall violent workplace incidents per ED volume during the pandemic compared to the months leading up to it. A total of 259 responses were received for the initial pre/early-pandemic survey and 259 responses received for the mid/late-pandemic survey. The reported level of safety perceived by staff remained the same, as did the overall percentage of respondents indicating any verbal abuse or physical assault in the prior 6-months. The frequency of verbal abuse experienced by staff did increase during the pandemic, with 6.2% of respondents pre/early-pandemic indicating verbal abuse by patients or their visitors every day or two, compared to 10.8% mid/late-pandemic (p = .029). Despite our findings of a positive association between the COVID-19 case rate and rate of violent ED incidents, the percentage of our survey respondents indicating verbal abuse or physical assault experienced in a 6-month time period remained unchanged between the pre/early-pandemic and mid/late-pandemic periods, as did staff perception of workplace safety. This difference in documented and self-reported/perceived violence may be attributable to staff prioritizing other personal safety concerns throughout the pandemic. This positive association could be due to significant fear and stress experienced by the general public, or worsening substance abuse or mental health state during the pandemic.

Analysis of pediatric emergency department patient volume trends during the COVID-19 pandemic.

During the early period of the COVID-19 pandemic there was a substantial decrease in pediatric emergency department (PED) visitation. The intent of this study is to report PED utilization during the COVID-19 pandemic in an urban pediatric referral center located close to the epicenter in the northeastern US.A retrospective analysis of medical records of patients visiting the PED at Robert Wood Johnson University Hospital (RWJUH) was performed. Data included: daily census, admission rate, Emergency Severity Index, and ICD-10 diagnosis codes for the period of February through July, 2018 to 2020.By the week of March 26th, visits had decreased by 70% compared to the average of the previous 2 years. This census nadir lasted for 6 weeks. At 5 weeks postnadir the average daily census recovered to levels 40% lower than prior year norms and remained at that level during subsequent months. The greatest decreases were seen in low-acuity visits. Visits for behavioral health and fractures decreased by approximately 50% and 70%, respectively, but recovered to prior year norms by June and July of 2020. Visits for asthma exacerbation decreased by as much as 87% and remained at record lows for the remainder of the study period.A substantial and persistent decrease in PED visitation was experienced during the COVID-19 pandemic. Whereas visits for behavioral health and fractures have recovered to prior year norms, visits for asthma exacerbation remain at record lows. Further research is needed to ascertain the causes of these changes, including patient perceptions of the PED.

Changes in Emergency Department Patient Volume and Acuity Associated with Early Stages of the COVID-19 Pandemic in a Unique Environment.

Hospitals and emergency departments (EDs) faced profound uncertainty during the COVID-19 pandemic. Early concerns regarding demand far exceeding capacity were balanced by anecdotal reports of decreased patient visits, including those for specific high-acuity conditions. This study sought to identify changes in ED volume and acuity, within a specific managed care environment, associated with the onset of the pandemic. Data from patient visits to 2 San Diego, California, EDs-within an integrated health-care system-were extracted from the electronic health record. Daily patient visits, hospital admissions from the ED, Emergency Severity Index scores, and mode of arrival were compared between two 28-day periods, with the 28 days following a "stay at home" order issued by the governor of California and a control period of the same dates in 2019. These EDs observed a significant decrease in daily visits (42% compared to the previous year) associated with the pandemic. An increased rate of hospital admissions (16.6%-21.6%) was suggestive of an overall increase in acuity; however, changes in the distribution of Emergency Severity Index scores were less pronounced. The overall number of admissions declined significantly. Although overall ambulance traffic decreased, the proportion of patients arriving by ambulance was unchanged. Patient volume in 2 EDs dropped significantly in association with a statewide response to the COVID-19 pandemic. There was also a shift in acuity as measured by the proportion of patients admitted to the hospital, but overall admissions declined, suggesting sicker patients also did not seek care.

Brief Report: The Impact of COVID-19 on Emergency Department Overdose Diagnoses and County Overdose Deaths.

Background and ObjectivesWe sought to understand the impact of COVID‐19 on emergency department (ED) overdoses and county coroner verified overdose deaths.MethodsElectronic medical health record and county coroner data were gathered and comparisons were made between three 16‐week time periods. In the three time periods, 873 individuals had an overdose diagnosis in the ED and 440 individuals in the county died of drug overdose.ResultsWhile total ED patient volume decreased substantially, the number of ED overdose patients increased between March 6 and June 25, 2020. Furthermore, during this same period, coroner data revealed an increase in overdose deaths.Conclusion and Scientific SignificanceThis preliminary evidence provides a key insight into the impact of COVID‐19 on both overdose presentations to the ED and county overdose deaths. These results emphasize the critical need for increasing vigilance to prevent overdose by continuously developing and optimizing both accessible and quality treatment as we navigate through this pandemic and its ongoing effects on persons with substance use disorder. (Am J Addict 2021;00:00–00)

The cost of waiting: Association of ED boarding with hospitalization costs.

Emergency Department (ED) boarding, the practice of holding patients in the ED after they have been admitted to the hospital due to unavailability of inpatient beds, is common and contributes to the public health crisis of ED crowding. Prior work has documented the harms of ED boarding on access and quality of care. Limited studies examine the relationship between ED boarding and an equally important domain of quality-the cost of care. This study evaluates the relationship between ED boarding, ED characteristics and risk-adjusted hospitalization costs utilizing national publicly-reported measures. We conducted a cross-sectional analysis of two 2018 Centers for Medicare and Medicaid Services (CMS) Hospital Compare datasets: 1) Medicare Hospital Spending per Patient and 2) Timely and Effective Care. We constructed a hospital-level multivariate linear regression analysis to examine the association between ED boarding and Medicare spending per beneficiary (MSPB), adjusting for ED length of stay, door to diagnostic evaluation time, and ED patient volume. A total of 2903 hospitals were included in the analysis. ED boarding was significantly correlated with MSPB (r=0.1774; p-value: <0.0001). In multivariate regression, ED boarding was also positively associated with MSPB (Beta: 0.00015; p<0.0001) after adjustment for other hospital level crowding indicators. We found a strong relationship between measures of ED crowding, including ED boarding, and risk-adjusted hospital spending. Future work should elucidate the mediators of this relationship. Policymakers and administrators should consider the financial harms of ED boarding when devising strategies to improve hospital care access and flow.

Prediction of emergency department volume and severity during a novel virus pandemic: Experience from the COVID-19 pandemic.

BackgroundDuring a novel virus pandemic, predicting emergency department (ED) volume is crucial for arranging the limited medical resources of hospitals for balancing the daily patient- and epidemic-related tasks in EDs. The goal of the current study was to detect specific patterns of change in ED volume and severity during a pandemic which would help to arrange medical staff and utilize facilities and resources in EDs in advance in the event of a future pandemic.MethodsThis was a retrospective study of the patients who visited our ED between November 1, 2019 and April 30, 2020. We evaluated the change in ED patient volume and complexity of patients in our medical record system. Patient volume and severity during various periods were identified and compared with data from the past 3 years and the period that SARS occurred.ResultsA reduction in ED volume was evident. The reduction began during the early epidemic period and increased rapidly during the peak period of the epidemic with the reduction continuing during the late epidemic period. No significant difference existed in the percentages of triage levels 1 and 2 between the periods. The admission rate, length of stay in the ED, and average number of patients with out-of-hospital cardiac arrest increased during the epidemic periods.ConclusionA significant reduction in ED volume during the COVID-19 pandemic was noted and a predictable pattern was found. This specific change in pattern in the ED volume may be useful for performing adjustments in EDs in the future during a novel virus pandemic. The severity of patients visiting the ED during epidemic periods was inconclusive.

Influence of emergency department patient volumes on CT utilization rate of the physician in triage.

Physician in triage (PIT) has been used as a potential solution to emergency department (ED) overcrowding and to decrease ED length of stay (LOS). This study examined the relationship between computerized tomography (CT) utilization of PIT and ED patient volumes. We hypothesized that despite the pressure on PIT to improve throughput on the busiest days, they will continue to utilize CT at the same rate. This retrospective chart review evaluated CT ordering patterns of PIT on patients with abdominal pain who presented to the ED over a 6-year period. CT utilization rate was calculated on days with the lowest 5% (LD5) and highest 5% (HD5) volumes based on average yearly volume. CT positive and negative rates were correlated with volume using Chi square analysis. Odds ratio and confidence intervals were calculated for the magnitude of effect difference. We found no statistically significant difference in CT utilization rate on HD5 vs LD5 (p=0.833). There was a statistically significant increase in the rate of negative CT scans on HD5 (p=0.046) which represented a 17% relative difference. LOS was longer on HD5 (p=0.013) and when a CT scan was ordered (p<0.001). No difference was found in the rate at which the PIT ordered CT scans on high volume vs low volume days. The rate of CT scans without clinically relevant findings did increase slightly on high volume days. LOS was longer on high volume days and when a CT was ordered.

The Metrics of Acute Care Reentry and Emergency Department Visits by Recently Discharged Inpatients.

Research on acute care reentry by recently discharged inpatients has generally focused on hospital readmissions, with less attention given to presentations to the emergency department (ED). This omission results in underestimation of the extent of reentry and its impact on ED patient volumes and flow. This project involved an analysis of administrative data to examine the rate of ED presentations by recently discharged inpatients using 3 time metrics-within 0-3 days, 0-7 days, and 0-30 days of discharge. Descriptive-correlational analyses were conducted to examine the rates of reentry and ability to predict ED presentations using patient demographic (age and sex) and clinical profile (length of hospital stay and day of presentation). Approximately 12% of hospital discharges to home involved patients who presented to the ED within 30 days, and almost half occurred within the first week. Results of multivariable analyses suggest that the influences of ED presentations differ depending on the time metric examined. Emergency department presentations within 3 and 7 days of discharge compared with 30 days were not predicted by patient age or sex but were more likely to involve those with shorter hospital stays. A weekend presentation was also more likely among case patients presenting within 3 days of discharge. Only about one third of ED presentations resulted in readmission. Emergency department presentations are an important component of acute care reentry. Establishment of a common reentry metric for ED presentations would facilitate efforts to determine the impact of these events. Emergency nurses working in advanced practice roles are ideally positioned to assume a leadership role in addressing the needs of recently discharged inpatients who present to the ED. By reviewing these cases and collaborating with the inpatient unit staff, it may be possible to identify strategies for augmenting discharge planning and the provision of transitional care.

The Impact of Heat Waves on Emergency Department Visits in Roanoke, Virginia

The Impact of Heat Waves on Emergency Department Visits in Roanoke, Virginia

Swamped: Emergency Department Crowding and Patient Mortality

U.S. emergency departments are experiencing extreme levels of crowding. This study estimates the impact of emergency department crowding on patient mortality. Identification relies on the abrupt crowding shocks felt by “old” emergency departments at the time a new emergency department opens nearby. Using death records linked to hospital administrative records, I find that a 10% alleviation of emergency department patient volume significantly lowers the average patient’s chance of mortality. Improvements appear to be realized both inside the hospital and after the patient has left.

Provider-Level and Hospital-Level Factors and Process Measures of Quality Care Delivered in Pediatric Emergency Departments.

Differences in the quality of emergency department (ED) care are often attributed to nonclinical factors such as variations in the structure, systems, and processes of care. Few studies have examined these associations among children. We aimed to determine whether process measures of quality of care delivered to patients receiving care in children's hospital EDs were associated with physician-level or hospital-level factors. We included children (<18 years old) who presented to any of the 12 EDs participating in the Pediatric Emergency Care Applied Research Network (PECARN) between January 2011 and December 2011. We measured quality of care from medical record reviews using a previously validated implicit review instrument with a summary score ranging from 5 to 35, and examined associations between process measures of quality and physician- and hospital-level factors using a mixed-effects linear regression model adjusted for patient case-mix, with hospital site as a random effect. Among the 620 ED encounters reviewed, we did not find process measures of quality to be associated with any physician-level factors such as physician sex, years since medical school graduation, or physician training. We found, however, that process measures of quality were positively associated with delivery at freestanding children's hospitals (1.96 points higher in quality compared to nonfreestanding status, 95% confidence interval: 0.49, 3.43) and negatively associated with higher annual ED patient volume (-0.03 points per thousand patients, 95% confidence interval: -0.05, -0.01). Process measures of quality of care delivered to children were higher among patients treated at freestanding children's hospitals but lower among patients treated at higher volume EDs.

206 Social Factors That Influence Frequent Utilization of the Emergency Department for Adults Presenting to an Urban Emergency Department With Suicidal Ideation

Patients who frequently utilize the emergency department (ED) are a group of interest due to their disproportionate use as ED patient volume increases. The aim of this study is to investigate factors associated with frequent utilization of the ED for those patients with suicidal ideation (SI).

Performance of triage systems in emergency care: a systematic review and meta-analysis

ObjectiveTo assess and compare the performance of triage systems for identifying high and low-urgency patients in the emergency department (ED).DesignSystematic review and meta-analysis.Data sourcesEMBASE, Medline OvidSP, Cochrane central, Web of...

LO75: The impact of snowfall on patient attendance at an urban academic emergency department

Introduction: Accurate forecasting of emergency department (ED) patient visits can inform better resource matching. Calendar variables such as day of week and time of day are routinely used as predictors of ED volume. Further improvement in forecasting will likely come from dynamic variables. The effect of snowfall on ED volumes in colder climates remains poorly understood. We sought to determine whether accounting for snowfall improves ED patient volume forecasting. Our secondary objective was to characterize the magnitude of effect of snowfall on ED volume. Methods: This was a retrospective observational study using historical patient volume data and local snowfall records from April 1st, 2011 to March 31st, 2018 (2,542 days) at a single urban ED. We fit a series of four generalized linear models: a baseline model which included calendar variables and three different snowfall models which contained the variables in the baseline model plus an indicator variable for modelling snowfall. Each snowfall model had a different daily threshold for its indicator variable: any snowfall ( &amp;gt;0cm), moderate snowfall ( &amp;gt; = 1 cm), or high snowfall ( &amp;gt; = 5 cm). We modeled daily ED volume as the dependent variable using a Poisson distribution. To evaluate model fit, we examined the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) in each of the four models. In both cases, a lower number indicates better model fit. Incident rate ratios were calculated to determine the effect of snowfall. We used the delta method to calculate confidence intervals. Results: A total of 2542 days were used to develop the model. All three snowfall models demonstrated improved model fit compared to the baseline model with lower AIC and BIC values. The best fitting model included a binary variable for moderate snowfall ( &amp;gt; = 1cm/day). This model showed a statistically significant decrease in ED volume of 2.65% (95% CI: 1.23% -4.00%) on snowfall days, representing 5.4 (95% CI: 2.5 -8.2) patients per day at our hospital with an average daily volume of 205 patients. Conclusion: The addition of a snowfall variable results in improved forecasting model performance in ED volume forecasting with optimal threshold set at 1 cm of snow in our setting. Snowfall is associated with a modest, but statistically significant reduction in ED volume.

Forecasting Hospital Emergency Department Patient Volume Using Internet Search Data

We present an efficient and scalable system to predict emergency department (ED) patient volume in hospitals using publicly available Google Trends search data. Search volume data are retrieved for a selected set of context-relevant query keywords with refinements, on which a series of correlation analyses are performed, and a multiple regression predictive model is constructed. We also develop a software suite to enable convenient access to data visualization and prediction capabilities by medical and administrative staff. A preliminary demonstration of the method and software is presented with data from a large public hospital as a form of validation. This paper enables informed resource and manpower allocation in hospitals and thus improved ability to respond to patient influx surges, and importantly, can serve as a key mitigation measure against worsening ED congestion problems that plague hospitals.