Association of emergency department crowding with inpatient outcomes

Who responds to longer wait times? The effects of predicted emergency wait times on the health and volume of patients who present for care

Healthcare is often free at the point-of-care so that price does not deter patients. However, the dis-utility from waiting for care that often occurs could also lead to deterrence. I investigate responses in the volume and types of patients that demand emergency care when predicted waiting times quasi-randomly change. I leverage a discontinuity to compare emergency sites with similar predicted wait times but with different apparent wait times displayed to patients. I use impulse response functions estimated by local projections to estimate effects of predicted wait times on patient demand for care. An additional thirty minutes of predicted wait time results in 15% fewer waiting patients at urgent cares and 2% fewer waiting patients at emergency departments within three hours of display. Patients that stop using emergency care are also triaged as healthier. However, at very high predicted wait times, there are reductions in demand for all patients including sicker patients.

Racial and ethnic disparities in emergency department transfers to public hospitals

OBJECTIVE

To examine racial/ethnic differences in emergency department (ED) transfers to public hospitals and factors explaining these differences.

DATA SOURCES AND STUDY SETTING

ED and inpatient data from the Healthcare Cost and Utilization Project for Florida (2010-2019); American Hospital Association Annual Survey (2009-2018).

STUDY DESIGN

Logistic regression examined race/ethnicity and payer on the likelihood of transfer to a public hospital among transferred ED patients. The base model was controlled for patient and hospital characteristics and year fixed effects. Models II and III added urbanicity and hospital referral region (HRR), respectively. Model IV used hospital fixed effects, which compares patients within the same hospital. Models V and VI stratified Model IV by payer and condition, respectively. Conditions were classified as emergency care sensitive conditions (ECSCs), where transfer is protocolized, and non-ECSCs. We reported marginal effects at the means.

DATA COLLECTION/EXTRACTION METHODS

We examined 1,265,588 adult ED patients transferred from 187 hospitals.

PRINCIPAL FINDINGS

Black patients were more likely to be transferred to public hospitals compared with White patients in all models except ECSC patients within the same initial hospital (except trauma). Black patients were 0.5-1.3 percentage points (pp) more likely to be transferred to public hospitals than White patients in the same hospital with the same payer. In the base model, Hispanic patients were more likely to be transferred to public hospitals compared with White patients, but this difference reversed after controlling for HRR. Hispanic patients were - 0.6 pp to -1.2 pp less likely to be transferred to public hospitals than White patients in the same hospital with the same payer.

CONCLUSIONS

Large population-level differences in whether ED patients of different races/ethnicities were transferred to public hospitals were largely explained by hospital market and the initial hospital, suggesting that they may play a larger role in explaining differences in transfer to public hospitals, compared with other external factors.

Emergency Department Volume, Severity, and Crowding Since the Onset of the Coronavirus Disease 2019 Pandemic

STUDY OBJECTIVE

We describe emergency department (ED) visit volume, illness severity, and crowding metrics from the onset of the coronavirus disease 2019 (COVID-19) pandemic through mid-2022.

METHODS

We tabulated monthly data from 14 million ED visits on ED volumes and measures of illness severity and crowding from March 2020 through August 2022 compared with the same months in 2019 in 111 EDs staffed by a national ED practice group in 18 states.

RESULTS

Average monthly ED volumes fell in the early pandemic, partially recovered in 2022, but remained below 2019 levels (915 per ED in 2019 to 826.6 in 2022 for admitted patients; 3,026.9 to 2,478.5 for discharged patients). The proportion of visits assessed as critical care increased from 7.9% in 2019 to 11.0% in 2022, whereas the number of visits decreased (318,802 to 264,350). Visits billed as 99285 (the highest-acuity Evaluation and Management code for noncritical care visits) increased from 35.4% of visits in 2019 to 40.0% in 2022, whereas the number of visits decreased (1,434,454 to 952,422). Median and median of 90th percentile length of stay for admitted patients rose 32% (5.2 to 6.9 hours) and 47% (11.7 to 17.4 hours) in 2022 versus 2019. Patients leaving without treatment rose 86% (2.9% to 5.4%). For admitted psychiatric patients, the 90th percentile length of stay increased from 20 hours to more than 1 day.

CONCLUSION

ED visit volumes fell early in the pandemic and have only partly recovered. Despite lower volumes, ED crowding has increased. This issue is magnified in psychiatric patients.

History, ECG, Risk Factors (HER) Scoring for Cardiac Risk Stratification in Patients <45 Years of Age Presenting With Chest Pain

Background Chest pain is a common chief complaint of patients presenting to the emergency department. Acute coronary syndrome (ACS) is found to be the etiology of this symptom in a minority of these patient encounters. This study aimed to determine the utility of using the History, ECG, Risk Factors (HER) components of the History, ECG, Age, Risk Factors, Troponin (HEART) score in ruling out 30-day Major Adverse Cardiac Event (MACE), ACS, ventricular tachycardia, and ventricular fibrillation in patients aged less than 45. Additionally, the utility of this score in ruling out a positive troponin was investigated as well. Methodology This is a retrospective chart review study that examined a consecutive cohort of 7,724 patients presenting with chest pain to the 11 emergency departments of a single healthcare system over a two-year period (January 2019 to December 2020). HER scores of 0 to 1 were categorized as negative (-) and scores of two or greater were categorized as positive (+). Sensitivity, specificity, and predictive values were calculated for the relationship between HER score positivity and primary cardiac disease and troponin results. Results Test characteristics of HER scoring for significant primary cardiac disease in patients between 18 and 45 years of age presenting with undifferentiated chest pain were sensitivity of 88.0 (CI = 80.0-94.0), specificity of 72.6 (CI = 71.8-73.8), positive predictive value of 3.1 (CI = 2.4-3.9), and negative predictive value of 99.8 (CI = 99.7-99.9). Furthermore, an HER score >1 was neither sensitive nor specific in predicting a positive troponin (sensitivity = 80, CI = 71.9-86; specificity = 71.3, CI = 70.3-72.3). However, the negative predictive value of an HER score of 0-1 was 99.5 (CI = 99.3-99.7) and the positive predictive value was 4.7 (CI = 3.9-5.7). Conclusions According to this study, when evaluating young patients who are deemed to have a subjectively non-highly suspicious history, who have minimal risk factors, and who have an ECG without significant ST deviation, troponin testing is low yield in the risk stratification of patients under the age of 45 for serious primary cardiac disease.