Predicting Emergency Department "Bouncebacks": A Retrospective Cohort Analysis

Reducing disparities in emergency department outcomes for individuals with limited English proficiency: The nurse work environment

BACKGROUND

Patients with limited English proficiency (LEP) experience worse emergency department (ED) outcomes.

PURPOSE

To evaluate the association between nurses' work environments and ED outcomes among individuals with and without LEP.

METHODS

Cross-sectional study of 1,358,802 patients seen in 64 New Jersey hospital EDs. Nurse work environment was measured by the Practice Environment Scale of the Nursing Work Index. Outcomes included 72-hr ED revisits, and departures against medical advice (AMA).

DISCUSSION

Individuals with LEP experienced higher odds of a 72-hr ED revisit (aOR 1.12, 95% CI 1.04-1.21, p < .001) and lower odds of AMA departure (aOR 0.67, 95% CI, 0.61-0.74, p < .001). An interaction was found between LEP status and the nurse work environment: individuals with LEP experienced lower odds of a 72-hr ED revisit in better vs. poor nurse work environments, compared those without LEP.

CONCLUSION

Disparities in LEP outcomes might be ameliorated by targeted improvements to nurses' work environments.

A Comprehensive Evaluation of Emergency Department Utilization by Patients With Cirrhosis

INTRODUCTION

Emergency department (ED)-based care is required for cirrhosis management, yet the burden of cirrhosis-related ED healthcare utilization is understudied. We aimed to describe ED utilization within a statewide health system and compare the outcomes of high ED use (HEDU) vs non-HEDU in individuals with cirrhosis.

METHODS

We retrospectively reviewed charts of adults with cirrhosis who presented to any of 16 EDs within the Indiana University Health system in 2021. Patient characteristics, features of the initial ED visit, subsequent 90-day healthcare use, and 360-day outcomes were collected. Multivariable logistic regression models were used to identify predictors HEDU status which was defined as ≥2 ED visits within 90 days after the index ED visit.

RESULTS

There were 2,124 eligible patients (mean age 61.3 years, 53% male, and 91% White). Major etiologies of cirrhosis were alcohol (38%), metabolic dysfunction-associated steatohepatitis (27%), and viral hepatitis (21%). Cirrhosis was newly diagnosed in the ED visit for 18.4%. Most common reasons for ED visits were abdominal pain (21%), shortness of breath (19%), and ascites/volume overload (16%). Of the initial ED visits, 20% (n = 424) were potentially avoidable. The overall 90-day mortality was 16%. Within 90 days, there were 366 HEDU (20%). Notable variables independently associated with HEDU were model for end-stage liver disease-sodium (adjusted odds ratio [aOR] 1.044, 95% confidence interval [CI] 1.005-1.085), prior ED encounter (aOR 1.520, 95% CI 1.136-2.034), and avoidable initial ED visit (aOR 1.938, 95% CI 1.014-3.703).

DISCUSSION

Abdominal pain, shortness of breath, and ascites/fluid overload are the common presenting reasons for ED visits for patients with cirrhosis. Patients with cirrhosis presenting to the ED experience a 90-day mortality rate of 16%, and among those who initially visited the ED, 20% were HEDU. We identified several variables independently associated with HEDU. Our observations pave the way for developing interventions to optimize the care of patients with cirrhosis presenting to the ED and to lower repeated ED visits.

Virtual Versus In-Person Follow-up After a Psychiatric Emergency Visit: A Population-Based Cohort Study: Suivi virtuel opposé à en personne après une visite à l'urgence psychiatrique : une étude de cohorte dans la population

OBJECTIVE

With increased utilization of virtual care in mental health, examining its appropriateness in various clinical scenarios is warranted. This study aimed to compare the risk of adverse psychiatric outcomes following virtual versus in-person mental health follow-up care after a psychiatric emergency department (ED) visit.

METHODS

Using population-based health administrative data in Ontario (2021), we identified 28,232 adults discharged from a psychiatric ED visit who had a follow-up mental health visit within 14 days postdischarge. We compared those whose first follow-up visit was virtual (telephone or video) versus in-person on their risk for experiencing either a repeat psychiatric ED visit, psychiatric hospitalization, intentional self-injury, or suicide in the 15-90 days post-ED visit. Cox proportional hazard models generated adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), adjusted for age, income quintile, psychiatric hospitalization, and intentional self-injury in the 2 years prior to ED visit. We stratified by sex and diagnosis at index ED visits based on the International Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) coding.

RESULTS

About 65% (n = 18,354) of first follow-up visits were virtual, while 35% (n = 9,878) were in-person. About 13.9% and 14.6% of the virtual and in-person groups, respectively, experienced the composite outcome, corresponding to incidence rates of 60.9 versus 74.2 per 1000 person-years (aHR 0.95, 95% CI 0.89 to 1.01). Results were similar for individual elements of the composite outcome, when stratifying by sex and index psychiatric diagnosis, when varying exposure (7 days) and outcome periods (60 and 30 days), and comparing "only" virtual versus "any" in-person follow-up during the 14-day follow-up.

CONCLUSIONS AND RELEVANCE

These results support virtual care as a modality to increase access to follow-up after an acute care psychiatric encounter across a wide range of diagnoses. Prospective trials to discern whether this is due to the comparable efficacy of virtual and in-person care, or due solely to appropriate patient selection may be warranted.

Aspiring to clinical significance: Insights from developing and evaluating a machine learning model to predict emergency department return visit admissions

Return visit admissions (RVA), which are instances where patients discharged from the emergency department (ED) rapidly return and require hospital admission, have been associated with quality issues and adverse outcomes. We developed and validated a machine learning model to predict 72-hour RVA using electronic health records (EHR) data. Study data were extracted from EHR data in 2019 from three urban EDs. The development and independent validation datasets included 62,154 patients from two EDs and 73,453 patients from one ED, respectively. Multiple machine learning algorithms were evaluated, including deep significance clustering (DICE), regularized logistic regression (LR), Gradient Boosting Decision Tree, and XGBoost. These machine learning models were also compared against an existing clinical risk score. To support clinical actionability, clinician investigators conducted manual chart reviews of the cases identified by the model. Chart reviews categorized predicted cases across index ED discharge diagnosis and RVA root cause classifications. The best-performing model achieved an AUC of 0.87 in the development site (test set) and 0.75 in the independent validation set. The model, which combined DICE and LR, boosted predictive performance while providing well-defined features. The model was relatively robust to sensitivity analyses regarding performance across age, race, and by varying predictor availability but less robust across diagnostic groups. Clinician examination demonstrated discrete model performance characteristics within clinical subtypes of RVA. This machine learning model demonstrated a strong predictive performance for 72- RVA. Despite the limited clinical actionability potentially due to model complexity, the rarity of the outcome, and variable relevance, the clinical examination offered guidance on further variable inclusion for enhanced predictive accuracy and actionability.

Evaluation of a Structured Review Process for Emergency Department Return Visits with Admission

BACKGROUND

Review of emergency department (ED) revisits with admission allows the identification of improvement opportunities. Applying a health equity lens to revisits may highlight potential disparities in care transitions. Universal definitions or practicable frameworks for these assessments are lacking. The authors aimed to develop a structured methodology for this quality assurance (QA) process, with a layered equity analysis.

METHODS

The authors developed a classification instrument to identify potentially preventable 72-hour returns with admission (PPRA-72), accounting for directed, unrelated, unanticipated, or disease progression returns. A second review team assessed the instrument reliability. A self-reported race/ethnicity (R/E) and language algorithm was developed to minimize uncategorizable data. Disposition distribution, return rates, and PPRA-72 classifications were analyzed for disparities using Pearson chi-square and Fisher's exact tests.

RESULTS

The PPRA-72 rate was 4.8% for 2022 ED return visits requiring admission. Review teams achieved 93% agreement (κ = 0.51) for the binary determination of PPRA-72 vs. nonpreventable returns. There were significant differences between R/E and language in ED dispositions (p < 0.001), with more frequent admissions for the R/E White at the index visit and Other at the 72-hour return visit. Rates of return visits within 72 hours differed significantly by R/E (p < 0.001) but not by language (p = 0.156), with the R/E Black most frequent to have a 72-hour return. There were no differences between R/E (p = 0.446) or language (p = 0.248) in PPRA-72 rates. The initiative led to system improvements through informatics optimizations, triage protocols, provider feedback, and education.

CONCLUSION

The authors developed a review methodology for identifying improvement opportunities across ED 72-hour returns. This QA process enabled the identification of areas of disparity, with the continuous aim to develop next steps in ensuring health equity in care transitions.

Factors Associated with Return Visits by Elders within 72 Hours of Discharge from the Emergency Department

Elders have a higher rate of return visits to the emergency department (ED) than other patients. It is critical to understand the risk factors for return visits to the ED by elders. The aim of this study was to determine the factors associated with return visits to the ED by elders. This study retrospectively reviewed the hospital charts of elders who returned to the ED within 72 h after discharge from ED. The risk factors identified in the Triage Risk Screening Tool were applied in this study. Of the elders discharged from the ED, 8.64% made a return visit to the ED within 72 h. The highest revisit rate occurred within 24 h after discharge. Factors associated with return ED visits within 24 h by elders were difficulty walking and having discharge care needs. The factor associated with ED return visits within 24-48 h was polypharmacy. Difficulty walking, having discharge care needs, and hospitalization within the past 120 days were associated with return visits made within 48-72 h following discharge. Identifying the reasons for return visits to the ED and providing a continuous review of geriatric assessment and discharge planning could reduce unnecessary revisits.

Closing the Gap: The Role of Discharge Nurses in an Emergency Department

INTRODUCTION

Patients discharged from the emergency department may require a follow-up appointment with an outpatient specialty clinic. Referral processes vary by clinic, some requiring faxed referrals, some providing appointments immediately, and others contacting the patients directly. The frequency with which patients are successfully connected with outpatient follow-up services is largely unknown.

METHODS

The ED discharge nurse role was developed to facilitate the navigation of patient follow-up and confirm that patients successfully connect with specialty outpatient clinics. Eight emergency nurses were recruited into this position to study the problem using a quality improvement approach. The ED discharge nurses reviewed referrals, contacted clinics and patients discharged from the emergency department, and intervened when barriers to transition occurred.

RESULTS

The ED discharge nurses were able to determine specific causes and themes of missed appointments experienced by patients. Systemic problems identified include lost faxes, illegible contact information, incomplete referrals, and referral refusals by the clinics without patient notification. Considering the variability of clinic processes outside the emergency department's control, the ED discharge nurse role became crucial in minimizing the risk of lost/unsuccessful follow-up for patients discharged from the emergency department.

DISCUSSION

Implementing the ED discharge nurse role created a contact for outpatient clinic referrals, patient inquiry, and a process to track errors and data to better understand the frequency of missed follow-up. In this quality improvement initiative, the role of the ED discharge nurse addressed the risk of patients falling through the cracks of a complex system.

Shock Index and Characteristics of "Bounce-Back" Patients in the Emergency Department of King Abdullah Medical City (KAMC): A Retrospective Analysis

Background "Bounce back" patients is a term used to refer to patients returning to the emergency department within 72 hours after the first visit. This can be attributed to various factors related to diagnosis, management, or the health care system. Objective This study sought to evaluate the extent of bounce-back patients in the emergency department of King Abdullah Medical City (KAMC), Makkah, Saudi Arabia, and then explore the possible relationship between shock index (SI) and bounce-back patients. Methods This is a retrospective chart review of the electronic system among patients who have returned to the emergency department within 72 hours from the index visit. All records were reviewed from May 2019 to May 2021. Vital signs were collected to calculate the shock index (heart rate/systolic blood pressure). The data were analyzed by SPSS Statistics v.27.0 (IBM Corp., Armonk, NY).  Results A total of (506) responses were analyzed. The median age was 56 years with an IQR of 40-67, and males represented 55.3%. Around three-quarters of the second complaints (76.9%) were related to the index visit. The durations between the visits were as follows: 51.8% within 24 hours, 30.2% within 25-48 hours, and 18% within 49-72 hours. The median and IQR for shock index were 0.67 and 0.59-0.80 respectively, while the median and IQR for reverse shock index were 1.49 and 1.25-1.71 respectively. Diabetes and the duration between the two visits were associated with the complaints (p-value=0.005, p-value=0.011) respectively. Conclusion The majority of bounce-back cases occurred within the first 24 hours in our sample. Hypertension, diabetes, and ischemic heart diseases were the most prevalent comorbidities among the bounce-back patients. The majority of bounce-back patients (76.9%) presented with complaints related to the index visit.

Bias Assessment and Correction in Machine Learning Algorithms: A Use-Case in a Natural Language Processing Algorithm to Identify Hospitalized Patients with Unhealthy Alcohol Use

Unhealthy alcohol use represents a major economic burden and cause of morbidity and mortality in the United States. Implementation of interventions for unhealthy alcohol use depends on the availability and accuracy of screening tools. Our group previously applied methods in natural language processing and machine learning to build a classifier for unhealthy alcohol use. In this study, we sought to evaluate and address bias through the use-case of our classifier. We demonstrated the presence of biased unhealthy alcohol use risk underestimation among Hispanic compared to Non-Hispanic White trauma inpatients, 18- to 44-year-old compared to 45 years and older medical/surgical inpatients, and Non-Hispanic Black compared to Non-Hispanic White medical/surgical inpatients. We further showed that intercept, slope, and concurrent intercept and slope recalibration resulted in minimal or no improvements in bias-indicating metrics within these subgroups. Our results exemplify the importance of integrating bias assessment early into the classifier development pipeline.

Pediatric Emergency Department Return Visits Within 72 Hours: Caregivers' Motives and Analysis of Ethnic and Primary Language Disparities

OBJECTIVES

In the United States, approximately 2.2% to 5% of children discharged from the emergency department (ED) return within 72 hours. There is limited literature examining caregivers' reasons for return to the ED, and none among Hispanics and Spanish-speaking caregivers. We sought to examine why caregivers of pediatric patients return to the ED within 72 hours of a prior ED visit, and assess roles of ethnicity and primary language.

METHODS

A previously validated survey was prospectively administered to caregivers returning to the ED within 72 hours of discharge at a freestanding, tertiary care, children's hospital over a 7-month period. Reasons for return to the ED, previous ED discharge processes, and events since discharge were summarized according to Hispanic ethnicity, and English or Spanish language preference, and compared using the Fisher exact test.

RESULTS

Among 499 caregiver surveys analyzed, caregivers returned mostly because of no symptom improvement (57.5%) and worsening condition (35.5%), with no statistically significant differences between Hispanic/non-Hispanic ethnicity, or English/Spanish preference. Most (85.2%) caregivers recalled reasons to return to the ED. Recall of expected duration until symptom improvement was significantly higher among Hispanic (60.4%) versus non-Hispanic (52.1%) (P = 0.003), and for Spanish- (68.9%) versus English-speaking (54.6%) (P = 0.04), caregivers.

CONCLUSIONS

Most caregivers returned to the ED because their child's condition was not better or had worsened. Ethnicity and language were not associated with variations in reasons for return. Non-Hispanic and English-speaking caregivers were less likely to recall being informed of time to improvement and may require additional intervention.

Fast Neuro: A Care Model to Expedite Access to Neurology Clinic

Objective:

We set out to improve outpatient neurology access while reducing patient volume in the emergency department (ED) for nonemergent neurologic complaints.

Methods:

We created a rapid-access model, UCLA Fast Neuro, for patients referred from affiliated emergency departments to outpatient neurology, enabling appointments within 1 week of referral. Rapid-access appointments were also available to established neurology patients with urgent concerns. Fast Neuro was built to reduce nonemergent neurologic care in the ED, improve outpatient neurology access, and avoid use of inpatient neurology services for nonemergent consults. The volume of referrals and neurology consults from the ED and wait time from referral to appointment were measured. Surveys were conducted at 3 and 6 months to assess satisfaction with the model by all stakeholders.

Results:

From January 2019 through January 2021, 201 patients were referred to outpatient neurology through UCLA Fast Neuro. Wait time for an outpatient neurology appointment was reduced from the prior period by 82.5% (7.0±5.5 days vs 40±4.1 days). The number of nonemergent consults from the ED was reduced by 60% (4.1±1.9/month vs 10.3±1.7/month). Surveys showed wide acceptance of the new model with 92% of attending physicians and advanced practice providers and 89% of residents endorsing that UCLA Fast Neuro patients did not detract from their clinic experience.

Conclusions:

UCLA Fast Neuro improved emergency room throughput, reduced inpatient neurology consults from the ED, and decreased wait times for outpatient neurology appointments without using the inpatient neurology service for nonurgent consults. UCLA Fast Neuro was successful. Exploration of how to scale and implement the model of access more broadly is warranted.

Evaluation of feedback modalities and preferences regarding feedback on decision-making in a pediatric emergency department

OBJECTIVES

To compare pediatric emergency clinicians' attitudes toward three feedback modalities and assess clinicians' case-based feedback preferences.

METHODS

Electronic survey sent to pediatric emergency medicine (PEM) physicians and fellows; general pediatricians; and advanced practice providers (APPs) with nine questions exploring effectiveness and emotional impact of three feedback modalities: case-based feedback, bounce-back notifications, and biannual performance reports. Additional questions used a four-point ordinal agreement response scale and assessed clinicians' attitudes toward case review notification, case-based feedback preferences, and emotional support. Survey responses were compared by feedback modality using Pearson's chi-squared.

RESULTS

Of 165 eligible providers, 93 (56%) responded. Respondents agreed that case-based feedback was timely (81%), actionable (75%), prompted reflection on decision-making (92%), prompted research on current clinical practice (53%), and encouraged practice change (58%). Pediatric Emergency Care Applied Research Network (PECARN) performance reports scored the lowest on all metrics except positive feedback. No more than 40% of providers indicated that any feedback modality provided emotional support. Regarding case-based feedback, 88% of respondents desired email notification before case review and 88% desired feedback after case review. Clinicians prefer receiving feedback from someone with similar or more experience/training. Clinicians receiving feedback desire succinctness, supporting evidence, consistency, and sensitive delivery.

CONCLUSIONS

Case-based feedback scored highest of the three modalities and is perceived to be the most likely to improve decision-making and promote practice change. Most providers did not perceive emotional support from any feedback modality. Emotional safety warrants purposeful attention in feedback delivery. Critical components of case-based feedback include succinctness, supporting evidence, consistency, and sensitive delivery.

Inpatient Outcomes Following a Return Visit to the Emergency Department: A Nationwide Cohort Study

Introduction

Emergency department (ED) revisits are traditionally used to measure potential lapses in emergency care. However, recent studies on in-hospital outcomes following ED revisits have begun to challenge this notion. We aimed to examine inpatient outcomes and resource use among patients who were hospitalized following a return visit to the ED using a national database.

Methods

This was a retrospective cohort study using the National Health Insurance Research Database in Taiwan. One-third of ED visits from 2012–2013 were randomly selected and their subsequent hospitalizations included. We analyzed the inpatient outcomes (mortality and intensive care unit [ICU] admission) and resource use (length of stay [LOS] and costs). Comparisons were made between patients who were hospitalized after a return visit to the ED and those who were hospitalized during the index ED visit.

Results

Of the 3,019,416 index ED visits, 477,326 patients (16%) were directly admitted to the hospital. Among the 2,504,972 patients who were discharged during the index ED visit, 229,059 (9.1%) returned to the ED within three days. Of them, 37,118 (16%) were hospitalized. In multivariable analyses, the inpatient mortality rates and hospital LOS were similar between the two groups. Compared with the direct-admission group, the return-admission group had a lower ICU admission rate (adjusted odds ratio, 0.78; 95% confidence interval [CI], 0.72–0.84), and lower costs (adjusted difference, −5,198 New Taiwan dollars, 95% CI, −6,224 to −4,172).

Conclusion

Patients who were hospitalized after a return visit to the ED had a lower ICU admission rate and lower costs, compared to those who were directly admitted. Our findings suggest that ED revisits do not necessarily translate to poor initial care and that subsequent inpatient outcomes should also be considered for better assessment.

Emergency department bounceback characteristics for patients diagnosed with COVID-19

Background

The global healthcare burden of COVID-19 continues to rise. There is currently limited information regarding the disease progression and the need for hospitalizations in patients who present to the Emergency Department (ED) with minimal or no symptoms.

Objectives

This study identifies bounceback rates and timeframes for patients who return to the ED due to COVID-19 after initial discharge on the date of testing.

Methods

Using the NorthShore University Health System's (NSUHS) Enterprise Data Warehouse (EDW), we conducted a retrospective cohort analysis of patients who were tested positive for COVID-19 and were discharged home on the date of testing. A one-month follow-up period was included to ensure the capture of disease progression.

Results

Of 1883 positive cases with initially mild symptoms, 14.6% returned to the ED for complaints related to COVID-19. 56.9% of the mildly symptomatic bounceback patients were discharged on the return visit while 39.5% were admitted to the floor and 3.6% to the ICU. Of the 1120 positive cases with no initial symptoms, only four returned to the ED (0.26%) and only one patient was admitted. Median initial testing occurred on day 3 (2–5.6) of illness, and median ED bounceback occurred on day 9 (6.3–12.7). Our statistical model was unable to identify risk factors for ED bouncebacks.

Conclusion

COVID-19 patients diagnosed with mild symptoms on initial presentation have a 14.6% rate of bounceback due to progression of illness.