Unscheduled Return Visits With and Without Admission Post Emergency Department Discharge

Using a clinical narrative-aware pre-trained language model for predicting emergency department patient disposition and unscheduled return visits

The increasing prevalence of overcrowding in Emergency Departments (EDs) threatens the effective delivery of urgent healthcare. Mitigation strategies include the deployment of monitoring systems capable of tracking and managing patient disposition to facilitate appropriate and timely care, which subsequently reduces patient revisits, optimizes resource allocation, and enhances patient outcomes. This study used ∼ 250,000 emergency department visit records from Taipei Medical University-Shuang Ho Hospital to develop a natural language processing model using BlueBERT, a biomedical domain-specific pre-trained language model, to predict patient disposition status and unplanned readmissions. Data preprocessing and the integration of both structured and unstructured data were central to our approach. Compared to other models, BlueBERT outperformed due to its pre-training on a diverse range of medical literature, enabling it to better comprehend the specialized terminology, relationships, and context present in ED data. We found that translating Chinese-English clinical narratives into English and textualizing numerical data into categorical representations significantly improved the prediction of patient disposition (AUROC = 0.9014) and 72-hour unscheduled return visits (AUROC = 0.6475). The study concludes that the BlueBERT-based model demonstrated superior prediction capabilities, surpassing the performance of prior patient disposition predictive models, thus offering promising applications in the realm of ED clinical practice.

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.

Characterization of Emergency Department Quality Assurance Cases Seen Within a Midwestern United States Health System

BACKGROUND

Hospital quality-assurance (QA) processes, including peer-review committees, seek to identify high-risk areas.

PURPOSE

To characterize emergency department (ED) cases sent for QA review.

METHODS

A retrospective observational study was conducted of ED cases sent to a QA committee from November 2018 through July 2022 at three midwestern US hospitals. The QA records analyzed for these cases included the original incident report, case summary, and the committee determinations.

RESULTS

One hundred and forty-seven cases were reviewed by the ED QA Committee. The most frequent referrals came from physicians. Common diagnostic categories included infectious (21%), cardiac (16%), gastrointestinal (11%), and neurologic (10%) concerns. Of the cases, 51% were considered nonpreventable, 33% were potentially preventable, and 9% were preventable. Inpatient boarding in the ED was explicitly implicated as a contributing factor in 6% of case reports.

CONCLUSIONS

Peer physician reporting represent the largest referral source sent for review with the most frequent diagnostic categories, including infectious, cardiac, gastrointestinal, and neurological conditions. Preventable concerns were rare.

IMPLICATIONS

This study provides a better understanding of the referral sources, diagnostic categories, and committee determinations in ED quality concerns. These results can target future investigations into case reporting and patient safety.

Prediction of high-risk emergency department revisits from a machine-learning algorithm: a proof-of-concept study

BACKGROUND

High-risk emergency department (ED) revisit is considered an important quality indicator that may reflect an increase in complications and medical burden. However, because of its multidimensional and highly complex nature, this factor has not been comprehensively investigated. This study aimed to predict high-risk ED revisit with a machine-learning (ML) approach.

METHODS

This 3-year retrospective cohort study assessed adult patients between January 2019 and December 2021 from National Taiwan University Hospital Hsin-Chu Branch with high-risk ED revisit, defined as hospital or intensive care unit admission after ED return within 72 hours. A total of 150 features were preliminarily screened, and 79 were used in the prediction model. Deep learning, random forest, extreme gradient boosting (XGBoost) and stacked ensemble algorithm were used. The stacked ensemble model combined multiple ML models and performed model stacking as a meta-level algorithm. Confusion matrix, accuracy, sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) were used to evaluate performance.

RESULTS

Analysis was performed for 6282 eligible adult patients: 5025 (80.0%) in the training set and 1257 (20.0%) in the testing set. High-risk ED revisit occurred for 971 (19.3%) of training set patients vs 252 (20.1%) in the testing set. Leading predictors of high-risk ED revisit were age, systolic blood pressure and heart rate. The stacked ensemble model showed more favourable prediction performance (AUROC 0.82) than the other models: deep learning (0.69), random forest (0.78) and XGBoost (0.79). Also, the stacked ensemble model achieved favourable accuracy and specificity.

CONCLUSION

The stacked ensemble algorithm exhibited better prediction performance in which the predictions were generated from different ML algorithms to optimally maximise the final set of results. Patients with older age and abnormal systolic blood pressure and heart rate at the index ED visit were vulnerable to high-risk ED revisit. Further studies should be conducted to externally validate the model.

The risk factors of the 72-h unscheduled return visit admission to emergency department in adults below 50 years old

BACKGROUND

An unscheduled return visit (URV) to the emergency department (ED) within 72-h is an indicator of ED performance. An unscheduled return revisit (URV) within 72-h was used to monitor adverse events and medical errors in a hospital quality improvement program. The study explores the potential factors that contribute to URV to the ED within 72-h and the unscheduled return revisit admission (URVA) in adults below 50 years old.

METHODS

The case-control study enrolled 9483 URV patients during 2015-2020 in National Cheng-Kung University Hospital. URVA and URV non-admission (URVNA) patients were analyzed. The Gini impurity index was calculated by decision tree (DT) to split the variables capable of partitioning the groups into URVA and URVNA. Logistic regression is applied to calculate the odds ratio (OR) of candidate variables. The α level was set at 0.05.

RESULTS

Among patients under the age of 50, the percentage of females in URVNA was 55.05%, while in URVA it was 53.25%. Furthermore, the average age of URVA patients was 38.20 ± 8.10, which is higher than the average age of 35.19 ± 8.65 observed in URVNA. The Charlson Comorbidity Index (CCI) of the URVA patients (1.59 ± 1.00) was significantly higher than that of the URVNA patients (1.22 ± 0.64). The diastolic blood pressure (DBP) of the URVA patients was 85.29 ± 16.22, which was lower than that of the URVNA (82.89 ± 17.29). Severe triage of URVA patients is 21.1%, which is higher than the 9.7% of URVNA patients. The decision tree suggests that the factors associated with URVA are "severe triage," "CCI higher than 2," "DBP less than 86.5 mmHg," and "age older than 34 years". These risk factors were verified by logistic regression and the OR of CCI was 2.42 (1.50-3.90), the OR of age was 1.84 (1.50-2.27), the OR of DBP less than 86.5 was 0.71 (0.58-0.86), and the OR of severe triage was 2.35 (1.83-3.03).

CONCLUSIONS

The results provide physicians with a reference for discharging patients and could help ED physicians reduce the cognitive burden associated with the diagnostic errors and stress.

The impact of COVID-19 pandemic on revisits to emergency department

AIM

This study presents the impact of COVID-19 on revisits to the emergency department comparing revisit rates and characteristics between the pre-COVID-19 and COVID-19 periods.

METHODS

This multi-center retrospective study included patients over 18 years of age who visited emergency departments during the pre-COVID-19 period and the COVID-19 pandemic. The revisit rates were analyzed according to five age groups; 18-34, 35-49, 50-64, 65-79, and ≥ 80 years, and three revisit time intervals; 3, 9, and 30 days. Also, we compared the diagnosis and disposition at revisit between the study periods.

RESULTS

The revisit rates increased with age in both study periods and the revisit rates among all age groups were higher in the COVID-19 period. The proportion of infectious and respiratory diseases decreased during the COVID-19 period. The ICU admission rate and mortality at the revisit among patients aged ≥ 80 years were lower in the COVID-19 period than in the pre-COVID-19 period.

CONCLUSION

The revisit rates increased with age in both study periods and there were several changes in the diagnosis and disposition at the revisit in the COVID-19 period.

Predictors of 72-h unscheduled return visits with admission in patients presenting to the emergency department with abdominal pain

BACKGROUND

Unscheduled return visits (URVs) to the emergency department (ED) constitute a crucial indicator of patient care quality.

OBJECTIVE

We aimed to analyze the clinical characteristics of patients who visited the ED with abdominal pain and to identify the risk of URVs with admission (URVAs) from URVs without admission (URVNAs).

METHODS

This retrospective study included adult patients who visited the ED of Taipei Medical University Hospital because of abdominal pain and revisited in 72 h over a 5-year period (January 1, 2014, to December 31, 2018). Multivariable logistic regression analysis was employed to identify risk factors for URVAs and receiver operating characteristic (ROC) curve analysis was performed to determine the efficacy of variables predicting URVAs and the optimal cut-off points for the variables. In addition, a classification and regression tree (CART)-based scoring system was used for predicting risk of URVA.

RESULTS

Of 702 eligible patients with URVs related to abdominal pain, 249 had URVAs (35.5%). In multivariable analysis, risk factors for URVAs during the index visit included execution of laboratory tests (yes vs no: adjusted odds ratio [AOR], 4.32; 95% CI 2.99-6.23), older age (≥ 40 vs < 40 years: AOR, 2.10; 95% CI 1.10-1.34), Level 1-2 triage scores (Levels 1-2 vs Levels 3-5: AOR, 2.30; 95% CI 1.26-4.19), and use of ≥ 2 analgesics (≥ 2 vs < 2: AOR, 2.90; 95% CI 1.58-5.30). ROC curve analysis results revealed the combination of these 4 above variables resulted in acceptable performance (area under curve: 0.716). The above 4 variables were used in the CART model to evaluate URVA propensity.

CONCLUSIONS

Elder patients with abdominal pain who needed laboratory workup, had Level 1-2 triage scores, and received ≥ 2 doses of analgesics during their index visits to the ED had higher risk of URVAs.

Reducing 48-h emergency department revisits and subsequent admissions: a retrospective study of increased emergency medicine resident floor coverage

BACKGROUND

Early unexpected hospital admission after emergency department (ED) discharge is an important topic regarding effective preventive measures. Reducing avoidable return visits can improve ED effectiveness and emergency care. This study evaluated the effects of an increase in the number of physicians and the 24-h coverage of emergency physicians on 48-h ED revisits with subsequent hospital admission. The characteristics and risk factors of the patients were also investigated.

RESULTS

This was a retrospective analysis performed 2 years before and 2 years after the implementation of an intervention in a tertiary care hospital in Thailand. The medical records of adult patients who revisited the ED within 48 h for related complaints were reviewed. The effect of the intervention was analyzed, and a prediction model was developed based on logistic regression. After implementing the intervention, the hospital admission rate at the second ED visit decreased from 44.5 to 41.1%; no significant difference was found (95% confidence interval (CI) - 5.05 to 11.78). Patients who required hospital admission had a significantly higher comorbidity score, more ED visits, and more hospitalizations within the past 12 months. A significantly higher hospital admission rate was also observed among patients older than 60 years, those who had an initial infectious diagnosis, and those who had a higher triage severity level (ESI II) at their first visit. The odds ratio (OR) showed lower odds of hospital admission at the second visit in the postintervention period; this difference was not significant (OR 0.87; 95% CI 0.61 to 1.23).

CONCLUSION

Our intervention did not significantly decrease the incidence of admission at an ED revisit. However, some factors identified in this study seem to have some benefits and might be helpful for preventing errors and constructing a standard discharge care plan for patients with these risk factors.

Pediatric Return Visits to the Emergency Department: The Time to Return Curve

OBJECTIVE

Although 72-hour return visits are a frequently reported metric for pediatric patients discharged from the emergency department (ED), the basis for this metric is not established. Our objective was to statistically derive a cutoff time point for the characterization of pediatric return visits.

METHODS

We performed a retrospective cohort study using data of patients discharged from any of 44 pediatric EDs. We selected the first encounter per patient from January 1 to December 31, 2019, as the index encounter and included the first return visit within 30 days. We constructed a cumulative hazard curve to characterize the timing of return visits and constructed a multivariable adaptive regression spline model to identify a hinge point in return visit presentations. We identified the association between admission for early return visits and admission for late return visits using generalized linear mixed modeling.

RESULTS

Of 1,986,778 index ED discharges, 193,605 (9.7%) ED return visits were included. A double-exponential decay model demonstrated superior fit compared with a single exponential model ( P < 0.0001). Multivariable adaptive regression spline modeling identified a hinge at 7 days. When comparing proportions of return visits leading to hospitalization between early (23.8%) and late (15.1%) return visits, early visits (≤7 days) had higher adjusted odds of hospital admission (adjusted odds ratio, 1.73; 95% confidence interval, 1.69-1.77) relative to late return visits (>7 days). Findings were similar in sensitivity analyses within age subgroups, Census region, and in which the diagnosis (using the Diagnosis and Grouping System) was the same between the index and return visit. Among return visits that occurred within 7 days of the index visit, 46.3% had the same diagnosis grouping in both visits.

CONCLUSIONS

An empirically derived 7-day cutoff may be more appropriate for characterization of pediatric return visits to the ED. Encounters after this period had lower adjusted odds of admission.

A Comparison of Emergency Department Revisit Rates of Pediatric Patients between Pre-COVID-19 and COVID-19 Periods

Unscheduled revisits to emergency departments (EDs) are important because they indicate the quality of emergency care. However, the characteristics of pediatric patients visiting EDs changed during the coronavirus disease (COVID-19) pandemic, and these changes may have affected their revisit patterns. Therefore, we aimed to compare the ED revisit patterns of pediatric patients between the pre-COVID-19 and COVID-19 periods. This retrospective multicenter study included patients aged below 18 years who visited the ED in the pre-COVID-19 and COVID-19 periods. ED revisit rates were analyzed using five age groups and three visit-revisit intervals. In the pre-COVID-19 period, the revisit rates decreased with increasing age. In the COVID-19 period, the revisit rates were the lowest for the group aged 4–6 years, and the rates increased for those aged ≥7 years. In conclusion, there were changes in the patterns of revisit rates of pediatric patients according to age between the pre-COVID-19 and COVID-19 periods. Therefore, it is necessary to identify the reasons for revisits according to age and establish strategies to reduce the revisit rates of pediatric patients.

Patterns in emergency department unscheduled return visits during the COVID-19 pandemic

Introduction

Fear surrounding nosocomial infections, expanded telehealth, and decreases in ED (emergency department) utilization altered the way patients sought emergency care during the COVID pandemic. This study aims to evaluate COVID-19's impact on the frequency and characteristics of unscheduled return visits (URVs) to the adult and pediatric ED.

Methods

In this retrospective cohort study, the electronic medical record was used to identify ≤9-day URVs at a tertiary adult and pediatric ED from 4/16/19–2/29/20 (control) and 4/16/20–2/28/21 (COVID). The primary outcome, proportion of total ED visits made up by URVs, and secondary outcomes, patient characteristics (age), illness acuity (emergency severity index (ESI)), disposition, and mortality were compared between the cohorts. Pediatric and adult data were analyzed separately. A sub-analysis was performed to exclude patients with suspected respiratory infections.

Results

For adults, n = 4265, there was no significant difference between the proportion of ED census made up by URVs (4.56% (control) vs 4.76% (COVID), p = 0.17), mean patient age (46.33 (control) vs 46.18 (COVID), p = 0.80), ESI acuity (2.95 (control) vs 2.95 (COVID), p = 0.83), disposition (admission 0.32% (control) vs 0.39% (COVID), p = 0.69), and mortality (0.23% (control) and 0.49% (COVID), p = 0.15). When excluding possible respiratory infections comparisons remained insignificant.

For pediatrics, n = 1214, there was a significant difference in the proportion of ED census made up by URVs (4.83% (control) to 3.55% (COVID), p < 0.01), age (5.52 (control) vs 6.43 (COVID), p = 0.01), and ESI acuity (3.31 (control) vs 3.17 (COVID), p < 0.01). There was no difference in disposition (admission 0.12% (control) vs 0% (COVID), p = 1). When excluding possible respiratory infections acuity (p = 0.03) remained significant.

Conclusion

In the adult population, COVID did not significantly alter any of our outcomes. For pediatric patients, a decrease in the proportion of URVs and increase in acuity during COVID suggests that patients may have had other means of accessing care, avoided the ED, received more adequate care at initial presentation, or represented when more acutely ill.

Evaluation of Unscheduled Return Visits to the Pediatric Emergency Department and Risk Factors for Admission After Return Visit

OBJECTIVE

Unscheduled return visits to the emergency department (unscheduled RTED) increase both the workload and overcrowding in the emergency department. The aim in the present study is to identify the patient groups that require more careful and closer follow-up to reduce the rates of unscheduled RTED and hospital admissions after a return visit.

METHODS

Among the patients admitted to the emergency department of our hospital between 2016 and 2017, those who made an unscheduled RTED within 72 hours after their first visit to the emergency department were evaluated retrospectively.

RESULTS

Of the 137,787 eligible children, 3294 (2.8%) made unscheduled RTEDs within 72 hours. The median age was 28 months, and 1848 (57.6%) were male patients. The admission rate at the return visit was significantly higher among children younger than 2 years, in the patients presenting with respiratory complaints and severe acute conditions, and in those who presented to the emergency department for the first time during the department's busiest hours. The risk of admission upon a return visit to the emergency department was 2.7 times higher in the male sex, 5.4 times higher in children younger than 2 years, 5.9 times higher in patients with respiratory complaints, 4.9 times higher in patients with gastrointestinal tract complaints, and 27,000 times higher in patients with severe acute conditions.

CONCLUSIONS

Unscheduled RTED and hospitalization rates can be reduced with more careful evaluation of young children, patients with respiratory and gastrointestinal complaints and those who apply during emergency department busiest hours.

Effects of Maryland's global budget revenue model on emergency department utilization and revisits

BACKGROUND

In 2014, Maryland (MD) implemented a "global budget revenue" (GBR) program that prospectively sets hospital budgets. This program introduced incentives for hospitals to tightly control volume and meet budget targets. We examine GBR's effects on emergency department (ED) visits, admissions, and returns.

METHODS

We performed an interrupted time-series analysis with difference-in-differences comparisons using 2012 to 2015 Healthcare Cost Utilization and Project data from MD, New York (NY), and New Jersey (NJ). We examined GBR's effects on ED visits/1,000 population, admissions from the ED, and ED returns at 72 h and 9 days. We also examined rates of admission, intensive care unit (ICU) stay, and in-hospital mortality among returns. To evaluate racial/ethnic and payer outcome disparities among ED returns, we performed a triple differences analysis.

RESULTS

ED visits decreased with GBR adoption in MD relative to NY and NJ, by five and six visits/1,000 population, respectively. ED admissions declined relative to NY and NJ, by 0.6% and 1.8%, respectively. There was also a post-GBR decline in ED returns by 0.7%. Admissions among returns declined by 2%, while ICU and in-hospital mortality among returns remained relatively stable. ED return outcomes varied by racial/ethnic and payer group. Non-Hispanic Whites and non-Hispanic Blacks experienced a similar decline in returns, while returns remained unchanged among Hispanics/Latinos, widening the disparity gap. Payer group disparities between privately insured and Medicare, Medicaid, and uninsured individuals improved, with the disparity reduction most pronounced among the uninsured.

CONCLUSIONS

GBR adoption was associated with lower ED utilization and admissions. ED returns and admissions among returns also decreased, while mortality and ICU stays among returns remained stable, suggesting that GBR has not led to adverse patient outcomes from fewer admissions. However, changes in ED return disparities varied by subgroup, indicating that improvements in care transitions may be uneven across patient populations.

90-Day Return Visit to the Emergency Department After an Initial Neurosurgical Evaluation

OBJECTIVE

This study evaluated emergency department (ED) neurosurgical reevaluation rates and their causes. Identifying the most significant reasons that make patients return to the ED for a neurosurgical reevaluation can help implement changes to reduce the economic and medical burden of patient turnover.

METHODS

All patients undergoing neurosurgical reevaluation at our institution's ED after an initial neurosurgical evaluation were enrolled in a prospective 3-month longitudinal registry. Inclusion criteria were all adult patients 21 years of age or older previously evaluated by neurosurgery at our institution's ED who return within 90 days for a neurosurgical reevaluation.

RESULTS

We found an overall 90-day ED neurosurgical return visit rate of 2.1%. During the study, 34 patients returned to the ED for a neurosurgical reevaluation. Patients returned for a neurosurgical reevaluation at a median of 23.5 days after the initial neurosurgery evaluation. The principal causes for a return visit were altered mental status, headache, and wound infections. Among the returning patients, 59% required hospitalization and 50% required an operation.

CONCLUSIONS

To our knowledge, this is the first study to prospectively collect data to estimate the 90-day ED return visit rate for a neurosurgical reevaluation following an initial ED neurosurgical evaluation. Some patients still use the ED to get continued care of their condition despite having access to their primary care physician. Better communication, social worker coordination, and prompt follow-up appointments at the neurosurgical outpatient clinic may reduce return visits.

Risk Factors for Early Return Visits to the Emergency Department in Patients Presenting with Nonspecific Abdominal Pain and the Use of Computed Tomography Scan

Over a quarter of patients presenting with abdominal pain at emergency departments (EDs) are diagnosed with nonspecific abdominal pain (NSAP) at discharge. This study investigated the risk factors associated with return ED visits in Taiwanese patients with NSAP after discharge. We divided patients into two groups: the study group comprising patients with ED revisits after the index ED visit, and the control group comprising patients without revisits. During the study period, 10,341 patients discharged with the impression of NSAP after ED management. A regression analysis found that older age (OR [95%CI]: 1.007 [1.003–1.011], p = 0.004), male sex (OR [95%CI]: 1.307 [1.036–1.650], p = 0.024), and use of NSAIDs (OR [95%CI]: 1.563 [1.219–2.003], p < 0.001) and opioids (OR [95%CI]: 2.213 [1.643–2.930], p < 0.001) during the index visit were associated with increased return ED visits. Computed tomography (CT) scans (OR [95%CI]: 0.605 [0.390–0.937], p = 0.021) were associated with decreased ED returns, especially for those who were older than 60, who had an underlying disease, or who required pain control during the index ED visit.

A Scoping Review of Emergency Department Discharge Risk Stratification

INTRODUCTION

Although emergency department (ED) discharge presents patient-safety challenges and opportunities, the ways in which EDs address discharge risk in the general ED population remains disparate and largely uncharacterized. In this study our goal was to conduct a review of how EDs identify and target patients at increased risk at time of discharge.

METHODS

We conducted a literature search to explore how EDs assess patient risk upon discharge, including a review of PubMed and gray literature. After independently screening articles for inclusion, we recorded study characteristics including outcome measures, patient risk factors, and tool descriptions. Based on this review and discussion among collaborators, major themes were identified.

RESULTS

PubMed search yielded 384 potentially eligible articles. After title and abstract review, we screened 235 for potential inclusion. After full text and reference review, supplemented by Google Scholar and gray literature reviews, we included 30 articles for full review. Three major themes were elucidated: 1) Multiple studies include retrospective risk assessment, whereas the use of point-of-care risk assessment tools appears limited; 2) of the point-of-care tools that exist, inputs and outcome measures varied, and few were applicable to the general ED population; and 3) while many studies describe initiatives to improve the discharge process, few describe assessment of post-discharge resource needs.

CONCLUSION

Numerous studies describe factors associated with an increased risk of readmission and adverse events after ED discharge, but few describe point-of-care tools used by physicians for the general ED population. Future work is needed to investigate standardized tools that assess ED discharge risk and patients' needs upon ED discharge.

Predicting Unscheduled Emergency Department Return Visits Among Older Adults: Population-Based Retrospective Study

Background

Unscheduled emergency department return visits (EDRVs) are key indicators for monitoring the quality of emergency medical care. A high return rate implies that the medical services provided by the emergency department (ED) failed to achieve the expected results of accurate diagnosis and effective treatment. Older adults are more susceptible to diseases and comorbidities than younger adults, and they exhibit unique and complex clinical characteristics that increase the difficulty of clinical diagnosis and treatment. Older adults also use more emergency medical resources than people in other age groups. Many studies have reviewed the causes of EDRVs among general ED patients; however, few have focused on older adults, although this is the age group with the highest rate of EDRVs.

Objective

This aim of this study is to establish a model for predicting unscheduled EDRVs within a 72-hour period among patients aged 65 years and older. In addition, we aim to investigate the effects of the influencing factors on their unscheduled EDRVs.

Methods

We used stratified and randomized data from Taiwan’s National Health Insurance Research Database and applied data mining techniques to construct a prediction model consisting of patient, disease, hospital, and physician characteristics. Records of ED visits by patients aged 65 years and older from 1996 to 2010 in the National Health Insurance Research Database were selected, and the final sample size was 49,252 records.

Results

The decision tree of the prediction model achieved an acceptable overall accuracy of 76.80%. Economic status, chronic illness, and length of stay in the ED were the top three variables influencing unscheduled EDRVs. Those who stayed in the ED overnight or longer on their first visit were less likely to return. This study confirms the results of prior studies, which found that economically underprivileged older adults with chronic illness and comorbidities were more likely to return to the ED.

Conclusions

Medical institutions can use our prediction model as a reference to improve medical management and clinical services by understanding the reasons for 72-hour unscheduled EDRVs in older adult patients. A possible solution is to create mechanisms that incorporate our prediction model and develop a support system with customized medical education for older patients and their family members before discharge. Meanwhile, a reasonably longer length of stay in the ED may help evaluate treatments and guide prognosis for older adult patients, and it may further reduce the rate of their unscheduled EDRVs.

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.

In-Hospital Outcomes in Patients Admitted to the Intensive Care Unit after a Return Visit to the Emergency Department

Background: Intensive care unit (ICU) admission following a short-term emergency department (ED) revisit has been considered a particularly undesirable outcome among return-visit patients, although their in-hospital prognosis has not been discussed. We aimed to compare clinical outcomes between adult patients admitted to the ICU after unscheduled ED revisits and those admitted during index ED visits. Method: This retrospective study was conducted at two tertiary medical centers in Taiwan from 1 January 2016 to 31 December 2017. All adult non-trauma patients admitted to the ICU directly via the ED during the study period were included and divided into two comparison groups: patients admitted to the ICU during index ED visits and those admitted to the ICU during return ED visits. The outcomes of interest included in-hospital mortality, mechanical ventilation (MV) support, profound shock, hospital length of stay (HLOS), and total medical cost. Results: Altogether, 12,075 patients with a mean (standard deviation) age of 64.6 (15.7) years were included. Among these, 5.3% were admitted to the ICU following a return ED visit within 14 days and 3.1% were admitted following a return ED visit within 7 days. After adjusting for confounding factors for multivariate regression analysis, ICU admission following an ED revisit within 14 days was not associated with an increased mortality rate (adjusted odds ratio (aOR): 1.08, 95% confidence interval (CI): 0.89 to 1.32), MV support (aOR: 1.06, 95% CI: 0.89 to 1.26), profound shock (aOR: 0.99, 95% CI: 0.84 to 1.18), prolonged HLOS (difference: 0.04 days, 95% CI: −1.02 to 1.09), and increased total medical cost (difference: USD 361, 95% CI: −303 to 1025). Similar results were observed after the regression analysis in patients that had a 7-day return visit. Conclusion: ICU admission following a return ED visit was not associated with major in-hospital outcomes including mortality, MV support, shock, increased HLOS, or medical cost. Although ICU admissions following ED revisits are considered serious adverse events, they may not indicate poor prognosis in ED practice.

Risk factors of admission in 72-h return visits to emergency department

Objective:

Return visit to emergency department (ED) is a common phenomenon and has been a clinical indicator of quality of care in ED. Most of previous articles focused on the characteristics of the patients returning within 72 h after ED discharge, while those on subsequent admission are numbered. This study's purpose is to identify risk factors for admission among 72-h return visit in the ED adult population.

Materials and Methods:

This retrospective cohort study was conducted at a medical center in Eastern Taiwan. The study period was from January 1, 2013, to December 31, 2013. We excluded patients who left against medical advice or without being seen, who was admitted or transferred at the index ED visit, whose medical records were incomplete, and whose age was below 18 years old. Significant variables were selected based on univariate analysis and later entered into multivariate logistic regression analysis to identify risk factors for 72-h return admission.

Results:

We identified 1575 eligible visits, and there were 1,119 visits entering into the final analysis. Male gender (odds ratio [OR] = 1.44), ambulance-transport at return visit (OR = 3.68), senior staff (OR = 1.52), work-up (OR = 3.03), and longer length of stay (LOS) were associated with higher risks of admission among ED 72-h return visits. Age, comorbidity, mode of transport at index visit, consultation, triage, type of illness, outpatient department visit between ED visits, and interval between index and return visits were not significantly associated with return admission.

Conclusion:

Gender, mode of transportation, staff experience, check-up, and LOS are associated with ED return admission.

Prompt Outpatient Care For Older Adults Discharged From The Emergency Department Reduces Recidivism

INTRODUCTION

Older adults present unique challenges to both emergency clinicians and health systems. These challenges are especially evident with respect to discharge after an emergency department (ED) visit as older adults are at risk for short-term, negative outcomes including repeat ED visits. The aim of this study was to evaluate characteristics and risk factors associated with repeat ED utilization by older adults.

METHODS

ED visits among participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study between 2003-2016 were examined using linked Medicare claims data to identify such visits and resulting disposition. Multilevel proportional hazards models examined associations of age, comorbidity status, race, gender, Medicaid dual eligibility status, social support characteristics (living alone or caregiver support), and use of ambulatory primary and subspecialty care with repeat ED utilization.

RESULTS

Older adults discharged from the ED seen by a primary care provider (hazard ratio [HR] = 0.93, confidence interval [CI], 0.87-0.98, p = 0.01) or subspecialist (HR = 0.91, CI 0.86-0.97, P <0.01) after the ED visit were less likely to return to the ED within 30 days compared to those who did not have such post-ED ambulatory visits. Additionally, comorbidity (HR =1.14, 95% CI, 1.13-1.16, P <0.01) and dual eligibility for Medicare and Medicaid (HR = 1.34, 95% CI, 1.20-1.50, p<0.01) were associated with return to the ED within 30 days. Those who were older (HR = 1.10, 95% CI, 1.05-1.15), had more comorbidities (HR = 1.17, 95% CI 1.15-1.18), Black (HR = 1.23, 95% CI, 1.14-1.33,P <0.01), and dually eligible (HR =1.23, 95% CI, 1.14-1.33, P <0.01) were more likely to return within 31-90 days after their initial presentation. The association of outpatient visits with repeat ED visits was no longer seen beyond 30 days. Patients without a caregiver or who lived alone were no more likely to return to the ED in the time periods evaluated in our study.

CONCLUSION

Both primary care and subspecialty care visits among older adults who are seen in the ED and discharged are associated with less frequent repeat ED visits within 30 days.

Virtual Urgent Care Quality and Safety in the Time of Coronavirus

Background

Telemedicine use rapidly increased during the COVID-19 pandemic. This study assessed quality aspects of rapid expansion of a virtual urgent care (VUC) telehealth system and the effects of a secondary telephonic screening initiative during the pandemic.

Methods

A retrospective cohort analysis was performed in a single health care network of VUC patients from March 1, 2020, through April 20, 2020. Researchers abstracted demographic data, comorbidities, VUC return visits, emergency department (ED) referrals and ED visits, dispositions, intubations, and deaths. The team also reviewed incomplete visits. For comparison, the study evaluated outcomes of non-admission dispositions from the ED: return visits with and without admission and deaths. We separately analyzed the effects of enhanced callback system targeting higher-risk patients with COVID-like illness during the last two weeks of the study period.

Results

A total of 18,278 unique adult patients completed 22,413 VUC visits. Separately, 718 patient-scheduled visits were incomplete; the majority were no-shows. The study found that 50.9% of all patients and 74.1% of patients aged 60 years or older had comorbidities. Of VUC visits, 6.8% had a subsequent VUC encounter within 72 hours; 1.8% had a subsequent ED visit. Of patients with enhanced follow-up, 4.3% were referred for ED evaluation. Mortality was 0.20% overall; 0.21% initially and 0.16% with enhanced follow-up (p = 0.59). Males and black patients were significantly overrepresented in decedents.

Conclusion

Appropriately deployed VUC services can provide a pragmatic strategy to care for large numbers of patients. Ongoing surveillance of operational, technical, and clinical factors is critical for patient quality and safety with this modality.

Emergency Department "Bounce-Back" Rates as a Function of Emergency Medicine Training Year

Introduction: Since the 1990s, the emergency department (ED) unscheduled return visit (URV), or “bounce-back,” has been used as a quality of care measurement. During that time, resident training was also scrutinized and uncovered a need for closer resident supervision, especially of second-year residents. Over the years, bounce-backs have continued to be analyzed with vigor, but research on residency training and supervision has lagged with few studies concurrently investigating residency supervision and bounce-backs. Other literature on resident supervision suggests that with adequate attending supervision, resident performance is equivalent to attending performance. With that in mind, it was hypothesized that resident bounce-back rates will be equivalent to attending bounce-back rates, and there will be no change among residency years. The primary objective of this study was to determine the rate at which patients are seen as a bounce-back visit within 72 hours of their initial visit to a community hospital ED during the study time frame. The secondary aims were to evaluate if the ED bounce-back rate is impacted by training level (residents or attending) and to describe bounce-back patient characteristics, including primary complaint/disease, age, comorbidities and issues with compliance.

Methods: A retrospective chart review of 1000 charts was conducted from September 2015 to September 2017. Charts were randomly selected by the Quality & Patient Safety (QPS) team and, after applying inclusion/exclusion criteria, 732 charts were analysed. Inclusion criteria included age ≥ 18 years, patients treated by an Emergency Medicine (EM) resident during their initial visit and patients with a “discharge” disposition. Exclusion criteria included patients seen as a scheduled return visit (e.g., two-day return for blood pregnancy recheck, wound check, etc.). Demographics, initial visit variables, comorbidities and bounce-back data were collected based on electronic record query or chart review. Data was analysed using means, standard deviations, medians and ranges for continuous variables. Logistic regression modelling techniques were used to examine factors that affect whether the patient had a bounce-back visit.

Results: The rate of URVs within 72 hours of the patient's initial visit was 4.65%. PGY1 and PGY2's bounce-back rate was 3.8% and 3.6%, respectively, and PGY3 and PGY4's bounce-back rate was 5.7% and 5.6%, respectively (p-value=.63). There was no statistically significant change among residency years. Most bounce-back characteristics analysed including primary complaint, age, and comorbidities demonstrated no statistical significance in the increased rate of bounce-back except for patients with a history of tobacco abuse, alcohol abuse and chronic pain. Current smokers were 6.5 times more likely to bounce back than former smokers (odds ratio=6.485, 95% confidence interval = 2.089 to 20.133, p-value=0.0012) and those with chronic pain were 2.5 times more likely to bounce back than those without chronic pain (odds ratio=2.518, 95% confidence interval =1.029 to 6.164, p=0.0431).

Conclusion: EM residency training year does not increase the frequency of bounce-backs in a community hospital ED. Finally, patients with substance abuse and chronic pain were more likely to bounce back.

A multicenter mixed-effects model for inference and prediction of 72-h return visits to the emergency department for adult patients with trauma-related diagnoses

Objective

Emergency department (ED) return visits within 72 h may be a sign of poor quality of care and entail unnecessary use of healthcare resources. In this study, we compare the performance of two leading statistical and machine learning classification algorithms, and we use the best performing approach to identify novel risk factors of ED return visits.

Methods

We analyzed 3.2 million ED encounters with at least one diagnosis under “injury, poisoning and certain other consequences of external causes” and “external causes of morbidity.” These encounters included patients 18 years or older from across 128 emergency room facilities in the USA. For each encounter, we calculated the 72-h ED return status and retrieved 57 features from demographics, diagnoses, procedures, and medications administered during the process of administration of medical care. We implemented a mixed-effects model to assess the effects of the covariates while accounting for the hierarchical structure of the data. Additionally, we investigated the predictive accuracy of the extreme gradient boosting tree ensemble approach and compared the performance of the two methods.

Results

The mixed-effects model indicates that certain blunt force and non-blunt trauma inflates the risk of a return visit. Notably, patients with trauma to the head and patients with burns and corrosions have elevated risks. This is in addition to 11 other classes of both blunt force and non-blunt force traumas. In addition, prior healthcare resource utilization, patients who have had one or more prior return visits within the last 6 months, prior ED visits, and the number of hospitalizations within the 6 months are associated with increased risk of returning to the ED after discharge. On the one hand, the area under the receiver characteristic curve (AUROC) of the mixed-effects model was 0.710 (0.707, 0.712). On the other hand, the gradient boosting tree ensemble had a lower AUROC of 0.698 CI (0.696, 0.700) on the independent test model.

Conclusions

The proposed mixed-effects model achieved the highest known AUC and resulted in the identification of novel risk factors. The model outperformed one of the leading machine learning ensemble classifiers, the extreme gradient boosting tree in terms of model performance. The risk factors we identified can assist emergency departments to decrease the number of unplanned return visits within 72 h.

Physician-related factors associated with unscheduled revisits to the emergency department and admission to the intensive care unit within 72 h

Investigation of physician-related causes of unscheduled revisits to the emergency department (ED) within 72 h with subsequent admission to the intensive care unit (ICU) is an important parameter of emergency care quality. Between 2012 and 2017, medical records of all adult patients who visited the ED and returned within 72 h with subsequent ICU admission were retrospectively reviewed by three experienced emergency physicians. Study parameters were categorized into "input" (Patient characteristics), "throughput" (Time spent on first ED visit and seniority of emergency physicians, and "output" (Charlson Comorbidity Index). Of the 147 patients reviewed for the causes of ICU admission, 35 were physician-related (23.8%). Eight belonged to more urgent categories, whereas the majority (n = 27) were less urgent. Patients who spent less time on their first ED visits before discharge (< 2 h) were significantly associated with physician-related causes of ICU admission, whereas there was no significant difference in other "input," "throughput," and "output" parameters between the "physician-related" and "non-physician-related" groups. Short initial management time was associated with physician-related causes of ICU admission in patients with initial less urgent presentations, highlighting failure of the conventional triage system to identify potentially life-threatening conditions and possibility of misjudgement because of the patients' apparently minor initial presentations.

[Epidemiology, initial diagnosis, and therapy of unexplained abdominal pain in the emergency department]

BACKGROUND

Abdominal pain is one of the most common symptoms of patients who present to the emergency department (ED). The aim of this study was to collect current epidemiological data, the frequency of these findings, and the measures that derived from them.

METHODS

We performed a retrospective analysis in the period between January 1 and June 30, 2016, including all patients who presented to the ED of the Caritas Hospital St. Josef in Regensburg (teaching hospital with an academic urology and gynecology department, about 32,000 patients in the ED per year) and were categorized as "abdominal pain in adults" using the Manchester Triage System (MTS).

RESULTS

The study population consisted of 1417 patients (9.8% of all ED patients). The admission rate was 48.2%. Vomiting and fever as concomitant symptoms made hospitalization more likely (p = 0.00). Almost half of the patients had nonspecific abdominal pain (28.2%), gynecological causes (13.2%), or suspected acute appendicitis (6.7%). In all, 10% of patients received an abdominal CT investigation; 73% of the patients presented in the time from 08:00-20:00 h, and more frequently on weekdays (74.2%). Of these patients, 6.4% returned after discharge because of persisting or worsening symptoms. Finally, 58.6% of outpatients and 77.5% of inpatients received further treatment recommendations for new pharmacologic therapy (e.g., analgesics, proton pump inhibitors, antibiotics).

CONCLUSION

A variety of epidemiological data of our collective could be analyzed, which should be transferable to many other German EDs. The MTS shows a high reliability in terms of conversion rate in abdominal pain; despite comprehensive emergency diagnostics, a relevant proportion of complaints remain unclear.

Influence of Overcrowding in the Emergency Department on Return Visit within 72 Hours

This study was conducted to determine whether overcrowding in the emergency department (ED) affects the occurrence of a return visit (RV) within 72 h. The crowding indicator of index visit was the average number of total patients, patients under observation, and boarding patients during the first 1 and 4 h from ED arrival time and the last 1 h before ED departure. Logistic regression analysis was conducted to determine whether each indicator affects the occurrence of RV and post-RV admission. Of the 87,360 discharged patients, 3743 (4.3%) returned to the ED within 72 h. Of the crowding indicators pertaining to total patients, the last 1 h significantly affected decrease in RV (p = 0.0046). Boarding patients were found to increase RV occurrence during the first 1 h (p = 0.0146) and 4 h (p = 0.0326). Crowding indicators that increased the likelihood of admission post-RV were total number of patients during the first 1 h (p = 0.0166) and 4 h (p = 0.0335) and evaluating patients during the first 1 h (p = 0.0059). Overcrowding in the ED increased the incidence of RV and likelihood of post-RV admission. However, overcrowding at the time of ED departure was related to reduced RV.

Geriatric Emergency Department Innovations: The Impact of Transitional Care Nurses on 30-day Readmissions for Older Adults

OBJECTIVES

Transitional care nurse (TCN) care has been associated with decreased hospitalizations for older adults in the emergency department (ED). The objective of this study was to evaluate the association between TCN care and readmission for geriatric patients who visit the ED within 30 days of a prior hospital discharge.

METHODS

We studied a prospective cohort of ED patients aged 65 and older with an ED visit within 30 days of inpatient discharge. Patients with an Emergency Severity Index of 1 or prior TCN contact were excluded. Entropy balancing and logistic regression were used to estimate the average incremental effect of the TCN intervention on risk of admission during the index ED visit and within 30 days of prior discharge.

RESULTS

Of 6,838 visits, 608 included TCN care. TCN patients had lower risk of readmission during the index ED visit at Mount Sinai Medical Center (MSMC), -10.1 percentage points (95% confidence interval [CI] = -18.5 to -2.7), and Northwestern Memorial Hospital (NMH), -17.3 percentage points (95% CI = -23.1 to -11.5), but not St. Joseph's Regional Medical Center (SJRMC), -2.5 percentage points (95% CI = -10.5 to 5.5). TCN patients had fewer readmissions within 30 days of prior hospital discharge at NMH, -16.2 percentage points (95% CI = -22.0 to -10.3), but not at MSMC, -5.6 percentage points (95% CI = -13.1 to 1.8), or at SJRMC, 0.5 percentage points (95% CI = -7.2 to 8.2).

CONCLUSIONS

Transitional care nurse care in the ED after a prior hospitalization was associated with decreased readmission of older adults during the index ED visit at two of three hospitals, with sustained reduction for the entire 30-day readmission window at one hospital. TCN interventions in the ED may decrease readmissions for geriatric patients in the ED; however, these results may be dependent on implementation of the program and availability of ED, hospital, and local resources for older adults.

Characteristics and determinants of high-risk unscheduled return visits to the emergency department

Background

High-risk unscheduled return visits (HRURVs), defined as return visits within 72 hours that require admission or die in the emergency department (ED) on representation, are a key quality metric in the ED. The objective of this study was to determine the incidence and describe the characteristics and predictors of HRURVs to the ED.

Methods

Case–control study, conducted between 1 November 2014 and 31 October 2015. Cases included all HRURVs over the age of 18 that presented to the ED. Controls were selected from patients who were discharged from the ED during the study period and did not return in the next 72 hours. Controls were matched to cases based on gender, age (±5 years) and date of presentation.

Results

Out of 38 886 ED visits during the study period, 271 are HRURVs, giving an incidence of HRURV of 0.70% (95% CI 0.62% to 0.78%). Our final analysis includes 270 HRURV cases and 270 controls, with an in-ED mortality rate of 0.7%, intensive care unit admission of 11.1% and need for surgical intervention of 22.2%. After adjusting for other factors, HRURV cases are more likely to be discharged with a diagnosis related to digestive system or infectious disease (OR 1.64, 95% CI 1.02 to 2.65 and OR 2.81, 95% CI 1.05 to 7.51, respectively). Furthermore, presentation to the ED during off-hours is a significant predictor of HRURV (OR 1.64, 95% CI 1.11 to 2.43) as is the presence of a handover during the patient visit (OR 1.68, 95% CI 1.02 to 2.75).

Conclusion

HRURV is an important key quality outcome metric that reflects a subgroup of ED patients with specific characteristics and predictors. Efforts to reduce this HRURV rate should focus on interventions targeting patients discharged with digestive system, kidney and urinary tract and infectious diseases diagnosis as well as exploring the role of handover tools in reducing HRURVs.

Predicting 72-hour and 9-day return to the emergency department using machine learning

OBJECTIVES

To predict 72-h and 9-day emergency department (ED) return by using gradient boosting on an expansive set of clinical variables from the electronic health record.

METHODS

This retrospective study included all adult discharges from a level 1 trauma center ED and a community hospital ED covering the period of March 2013 to July 2017. A total of 1500 variables were extracted for each visit, and samples split randomly into training, validation, and test sets (80%, 10%, and 10%). Gradient boosting models were fit on 3 selections of the data: administrative data (demographics, prior hospital usage, and comorbidity categories), data available at triage, and the full set of data available at discharge. A logistic regression (LR) model built on administrative data was used for baseline comparison. Finally, the top 20 most informative variables identified from the full gradient boosting models were used to build a reduced model for each outcome.

RESULTS

A total of 330 631 discharges were available for analysis, with 29 058 discharges (8.8%) resulting in 72-h return and 52 748 discharges (16.0%) resulting in 9-day return to either ED. LR models using administrative data yielded test AUCs of 0.69 (95% confidence interval [CI] 0.68-0.70) and 0.71(95% CI 0.70-0.72), while gradient boosting models using administrative data yielded test AUCs of 0.73 (95% CI 0.72-0.74) and 0.74 (95% CI 0.73-0.74) for 72-h and 9-day return, respectively. Gradient boosting models using variables available at triage yielded test AUCs of 0.75 (95% CI 0.74-0.76) and 0.75 (95% CI 0.74-0.75), while those using the full set of variables yielded test AUCs of 0.76 (95% CI 0.75-0.77) and 0.75 (95% CI 0.75-0.76). Reduced models using the top 20 variables yielded test AUCs of 0.73 (95% CI 0.71-0.74) and 0.73 (95% CI 0.72-0.74).

DISCUSSION AND CONCLUSION

Gradient boosting models leveraging clinical data are superior to LR models built on administrative data at predicting 72-h and 9-day returns.

Large observational study on risks predicting emergency department return visits and associated disposition deviations

Objective

A common emergency department (ED) patient care outcome metric is 72-hour ED return visits (EDRVs). Risks predictive of EDRV vary in different studies. However, risk differences associated with related versus unrelated EDRV and subsequent EDRV disposition deviations (EDRVDD) are rarely addressed. We aim to compare the potential risk patterns predictive of related and unrelated EDRV and further determine those potential risks predictive of EDRVDD.

Methods

We conducted a large retrospective observational study from September 1, 2015 through June 30, 2016. ED Patient demographic characteristics and clinical metrics were compared among patients of 1) related; 2) unrelated; and 3) no EDRVs. EDRVDD was defined as obvious disposition differences between initial ED visit and return visits. A multivariate multinomial logistic regression was performed to determine the independent risks predictive of EDRV and EDRVDD after adjusting for all confounders.

Results

A total of 63,990 patients were enrolled; 4.65% were considered related EDRV, and 1.80% were unrelated. The top risks predictive of EDRV were homeless, patient left without being seen, eloped, or left against medical advice. The top risks predictive of EDRVDD were geriatric and whether patients had primary care physicians regardless as to whether patient returns were related or unrelated to their initial ED visits.

Conclusion

Over 6% of patients experienced ED return visits within 72 hours. Though risks predicting such revisits were multifactorial, similar risks were identified not only for ED return visits, but also for return ED visit disposition deviations.

Usefulness of bounce-back admission in monitoring the quality of practice in the emergency department

Background: Recently, unscheduled readmissions after discharge from the emergency department (ED) (bounce-back admissions, BBAs) have been monitored as a hospital performance measure in countries other than Japan. It has been suggested that BBAs may be caused by errors in diagnoses or treatments.

Purpose: This retrospective cohort study aimed to evaluate BBAs and improve the quality of medical care in the ED of Showa University Hospital by analyzing the data of adult patients (≥18 years) with index visits to the ED of Showa University Hospital between June 2011 and May 2013 (n=15,069).

Patients and methods: Patients were registered and followed up for unscheduled admissions to this hospital within 7 days. In order to understand the reasons for BBAs, individual diagnoses upon BBA were compared to the corresponding diagnoses upon discharge.

Results: Among the 11,669 discharged patients, 180 patients were admitted within 3 days after discharge (3-day BBAs), and 257 were admitted within 7 days after discharge (7-day BBAs). The main diagnoses upon admission (BBA) were pneumonia or exacerbation of chronic obstructive pulmonary disease (COPD) or asthma (n=40, 16%), cholecystitis or cholangitis (n=21, 8.2%), and urinary tract infection (n=16, 6.2%). Among the 7-day BBA cases, 117 patients had similar and 110 patients had different diagnoses upon discharge and admission; in the remaining 30 cases, the results could not be ascertained owing to incomplete diagnostic data. In the cases of pneumonia, exacerbation of COPD or asthma, and colitis or enterocolitis, there was a significantly higher “similar” diagnoses than “different”, while the reverse was true for cases of stroke, ileus or bowel obstruction, and meningitis. These results were shared with the ED staff, and similar surveillances were periodically conducted. The frequency of admission within 7 days after discharge continuously declined from 2013 to 2016.

Conclusion: Analyzing the discharge and admission diagnoses may help ED staff to understand the reasons for common errors in order to follow the plan-do-check-act cycle of medical care in the ED.

Repeat Emergency Department Visits for Individuals With Intellectual and Developmental Disabilities and Psychiatric Disorders

Although individuals with intellectual and developmental disabilities (IDD) and psychiatric concerns are more likely than others to visit hospital emergency departments (EDs), the frequency of their returns to the ED within a short time is unknown. In this population-based study we examined the likelihood of this group returning to the ED within 30 days of discharge and described these visits for individuals with IDD + psychiatric disorders (n = 3,275), and persons with IDD only (n = 1,944) compared to persons with psychiatric disorders only (n = 41,532). Individuals with IDD + psychiatric disorders, and individuals with IDD alone were more likely to make 30-day repeat ED visits. Improving hospital care and postdischarge community linkages may reduce 30-day returns to the ED among adults with IDD.

Incidence, characteristics and outcomes of patients that return to Emergency Departments. An integrative review

BACKGROUND

Unplanned return visits account for up to 5% of Emergency Department presentations in Australia and have been associated with adverse events and increased costs. A large number of studies examine the incidence, characteristics and outcomes of unplanned return visits but few studies examine the reasons for return from a patient perspective. The objective of this integrative review was to determine the incidence, characteristics, outcomes and reasons for unplanned return visits to Emergency Departments.

METHOD

An integrative literature review design was employed to conduct a structured search of the literature using the databases CINAHL, MEDLINE, PubMed, ProQuest and EMBASE (inception to June 2018). Results were screened using predefined criteria and final studies collated and appraised using a quality assessment tool.

RESULTS

Fifty-two primary research articles were included in the review. The timeframe used to capture unplanned return visits varied and the incidence ranged between 0.07% and 33%. The majority of patients who return unplanned to the Emergency Department are subsequently discharged (51% and 90%) without an adverse event.

CONCLUSION

There is no consensus on the timeframe employed to classify unplanned return visits to the Emergency Department and the commonly used 72h lacks evidence. Routine statewide data linkage to capture return visits to other facilities is needed to ensure accurate data about this vulnerable patient group. Further research that focuses on patient and clinician perspectives is required to facilitate the development of local strategies to reduce the incidence of avoidable unplanned return visits.

Reduced hospitalization rates are not associated with increased mortality or readmission rates in an emergency department in Israel

BACKGROUND AND AIM

In 2011 the Israeli Ministry of Health (MOH) instructed hospitals to limit occupancy in the internal medicine wards to 120%, which was followed by a nationwide reduction in hospitalization rates. We examined how readmission and mortality rates changed in the five years following the changes in occupancy rates and hospitalization rates.

METHODS

All visits to the Tel Aviv Medical Center internal Emergency Medicine Department (ED) in 2010, 2014 and 2016 were captured, with exclusion of visits by patients below 16 of age and patients with incomplete or faulty data. The main outcomes were one-week readmission rates and one-month death rates. The secondary outcomes were admission rate, ED visit length & admission-delay time (minutes), and rates of admission-delayed patients.

RESULTS

After exclusion, a total of 168,891 internal medicine ED patients were included in the analysis. Mean age was 58.0 and 49% were males. During the relevant period (2010-2016), total medical ED visits increased by 11% - 53,327, 56,588 and 59,066 in 2010, 2014 and 2016 respectively. Hospitalization rates decreased from 46% in 2010 to 35% in 2015 (p < 0.001), with the most prominent reduction in the elderly population. One-week readmission rates were 6.5, 6.4 and 6.7% in 2010, 2014 and 2016 respectively (p = 0.347 and p = 0.21). One-month mortality was similar in 2010 and 2014 (4.4 and 4.5%, p = 0.388) and lower in 2016 (4.1%, p = 0.048 compared with 2010). Average ED visit length increased from 184 min in 2010 to 238 and 262 min in 2014 & 2016 (p < 0.001 for both) and average delay time to ward admission increased from 97 min in 2010 to 179 and 240 in 2014 & 2016 (p < 0.001 for both). In 2010 24% of the admitted patients were delayed in the ED more than 2 h, numbers that increased to 53% in 2014 and 66% in 2016 (p < 0.001 for both).

CONCLUSION

Following the 2011 MOH's decision to establish a 120% occupancy limit for internal medicine wards along with natural growth in population volume, significant changes were noted in the work of a large, presumably representative emergency department in Israel. Although a steady increase in total ED visits along with a steady reduction in hospitalization rates were observed, the readmission and mortality rates remained low. The increase in the average length of ED visits and in the delay from ED admission to a ward reflects higher burden on the ED. The study was not able to establish a causal connection between the MOH directive and the subsequent changes in ED activity. Nonetheless, the study has significant potential implications for policy makers, including the presence of senior ED physicians during afterhours, creation of short-stay diagnostic units and proper adjustments in ED size and personnel.

Predictors of Admission in Adult Unscheduled Return Visits to the Emergency Department

Introduction

The 72-hour unscheduled return visit (URV) of an emergency department (ED) patient is often used as a key performance indicator in emergency medicine. We sought to determine if URVs with admission to hospital (URVA) represent a distinct subgroup compared to unscheduled return visits with no admission (URVNA).

Methods

We performed a retrospective cohort study of all 72-hour URVs in adults across 10 EDs in the Edmonton Zone (EZ) over a one-year period (January 1, 2015 - December 31, 2015) using ED information-system data. URVA and URVNA populations were compared, and a multivariable analysis identified predictors of URVA.

Results

Analysis of 40,870 total URV records, including 3,363 URVAs, revealed predictors of URVA on the index visit including older age (>65 yrs, odds ratio [OR] 3.6), higher disease acuity (Canadian Emergency Department Triage and Acuity Scale [CTAS] 2, OR 2.6), gastrointestinal presenting complaint (OR 2.2), presenting to a referral hospital (OR 1.4), fewer annual ED visits (<4 visits, OR 2.0), and more hours spent in the ED (>12 hours, OR 2.0). A decrease in CTAS score (increase in disease acuity) upon return visit also increased the risk of admission (-1 CTAS level, OR 2.6). ED crowding at the index visit, as indicated by occupancy level, was not a predictor.

Conclusion

We demonstrate that URVA patients comprise a distinct subgroup of 72-hour URV patients. Risk factors for URVA are present at the index visit suggesting that patients at high risk for URVA may be identifiable prior to admission.

Unscheduled early revisit to emergency department

Background:

Unscheduled revisits to the emergency department may present a considerable additional workload.

Objectives:

This study investigated the risk factors contributing to adverse event during unscheduled early revisit to Emergency Department Hospital Universiti Sains Malaysia.

Methods:

A retrospective cohort study was conducted from January 2014 to January 2015 to character the nature of unscheduled early revisits to Emergency Department Hospital Universiti Sains Malaysia. It included all patients 18 years old and above, revisited emergency department within 9 days post discharge from emergency department.

Results:

Data were collected from 492 case records. The rate of emergency department unplanned revisits within 9 days of previous emergency department discharge was 0.66% for the study period. Risk factors for revisit included advance age, pre-existing co-morbidities, duration spent during first emergency department visit and health care system–related error. The independent predictors of morbidity were diabetes mellitus (odds ratio, 2.07; 95% confidential interval, 1.08–3.96), respiratory disease (odds ratio, 2.42; 95% confidential interval, 1.18–4.98), gastrointestinal disease (odds ratio, 5.93; 95% confidential interval: 1.29, 27.35), nervous system disease (odds ratio, 4.65; 95% confidential interval: 1.27, 17.02), duration spent more than 6 h during first emergency department visit (odds ratio, 3.05; 95% confidential interval: 1.53, 6.07), and medical error leading to admission (odds ratio, 8.85; 95% confidential interval: 4.43, 17.67). The overall mortality rate was 0.2% (1/492).

Conclusion:

Emergency department physicians need to be extra vigilant when managing patients with risk factors, particularly the modifiable risk factors, to curb emergency department revisit.

Risk Factors Associated With Emergency Department Return Visits Following Trauma System Discharge

OBJECTIVES

Little evidence exists in the pediatric trauma literature regarding what factors are associated with re-presentation to the hospital for patients discharged from the emergency department (ED).

METHODS

This was a retrospective cohort study of trauma system activations at a pediatric trauma center from June 30, 2007, through June 30, 2013, who were subsequently discharged from the ED or after a brief inpatient stay. Returns within 30 days were reviewed. χ, Student t test, and univariate logistical regression were used to compare predictive factors for those returning and not.

RESULTS

One thousand eight hundred sixty-three patient encounters were included in the cohort. Seventy-two patients (3.9%) had at least 1 return visit that was related to the original trauma activation. Age, sex, language, race/ethnicity, ED length of stay, arrival mode, level of trauma activation, and transfer from an outside hospital did not vary significantly between the groups. Patients with public insurance were almost 2 times more likely to return compared with those with private insurance (odds ratio, 1.92; 95% confidence interval, 1.11-3.35). Income by zip code was associated with the risk of a return visit, with patients in neighborhoods at less than the 50th percentile income twice as likely to return to the ED (odds ratio, 2.15; 95% confidence interval, 1.30-3.54).

CONCLUSIONS

Patients with public insurance and those from low-income neighborhoods were significantly more likely to return to the ED after trauma system activation. These data can be used to target interventions to decrease returns in high-risk trauma patients.

Factors Affecting Unscheduled Return Visits to the Emergency Department among Minor Head Injury Patients

Study Objectives

Differences between returning and non-returning minor head injury (MHI) emergency department (ED) patients, between the characteristics of the first visit and revisit, and between admitted and nonadmitted returning patients were investigated.

Methods

This was a retrospective study. All discharged ED patients with ICD-9 codes 850.0 to 850.9, 920, and 959.01 in 2013 were enrolled. Patients' demographic data, vital signs, Glasgow Coma Scale, ED diagnosis, length of stay, triage levels, ED examinations performed, and comorbidities were recorded for analysis.

Results

A total of 2,815 patients were enrolled. Of 57 (2%) patients who revisited the ED, 47 (82%) were discharged from the ED and ten (18%) were admitted to the hospital. Patients who returned to the ED were older, and they exhibited more comorbidities. Those who presented with vomiting, triage level of 1 or 2, and GCS score of <15 and who received more blood tests during their first visit were more likely to be admitted when they returned to the ED.

Conclusions

Discharging MHI patients who are older or exhibit comorbidities only when symptoms and concerns are relieved completely, providing clear discharge instructions, and arranging timely clinical follow-ups may help reduce such patients' return rate.

Factors associated with hospital admission after an emergency department treat and release visit for older adults with injuries

INTRODUCTION

Emergency Department (ED) visits for injury often precede hospital admissions in older adults, but risk factors for these admissions are poorly characterized. We sought to determine the incidence and risk factors for hospitalization shortly following discharge home from an ED visit for traumatic injury in older adults. We hypothesized higher risk for admission in those with increased age, discharged home after falls, with increased comorbidity burden, and who live in poor neighborhoods.

METHODS

We identified all community-dwelling patients ≥65years old treated and released for traumatic injury at non-federal EDs in Florida using the 2011 State Inpatient Database and State ED Database of the Agency for Healthcare Research and Quality. Outcome measures were hospitalization within 9 and 30days of discharge from the ED. Multivariable logistic regression was used to establish independent risk factors for hospital admission.

RESULTS

Of 163,851 index ED injury visits, 6298 (3.8%) resulted in inpatient admissions within 9days and 12,938 (7.9%) within 30days. Factors associated with increased odds of admission within 9days included: each additional comorbidity, ≥moderate injury to abdomen or pelvis/extremities, and median neighborhood income<$39,000. Additional factors associated with increased odds of admission within 30days included: lack of private insurance supplement and median neighborhood income<$48,000.

CONCLUSION

Among older adults treated and discharged from the ED for an injury, those who have high comorbidity burdens, have abdominal or orthopedic injuries, and live in poor neighborhoods are at increased risk of hospitalization within 9 or 30days of ED discharge.

Why seek a second consultation at an emergency centre? A qualitative study

BACKGROUND

The inappropriate use of emergency centres (ECs) is an expanding problem globally. The high attendance of non-urgent return presentations to ECs is recognised as part of the problem, placing an unnecessary demand on limited staff and resources. Of unscheduled returns 34% of cases had no change to diagnosis or treatment with the conclusion that 80% of re-attendance could be attributed to deficiencies in the initial consultation. This study aimed to evaluate the reasons why patients sought an early second consultation for the same complaint at a hospital EC in South Africa, by exploring the patient's experience and shortcomings in the first consultation.

METHOD

A qualitative study was conducted using in-depth, semi-structured interviews with 20 purposively selected participants who presented to a rural regional provincial hospital's EC within 7 days of a prior consultation for the same complaint. Verbatim transcripts were analysed using the framework method.

RESULTS

The main reasons for a second consultation were symptom related factors and the need for diagnostic certainty. The major themes around patient experience of the initial consultation were shortcomings in effective evaluation and management of pain, diagnostic uncertainty including poor examination, poor explanation, uncertain access and follow-up and societal encouragement to utilise a hospital EC.

CONCLUSION

Further interventions should explore pain as a presenting symptom of the illness experience, and promote competence in addressing physical and psychological causative factors within a patient-centred approach for all health staff, especially in primary care services.

Sentinel visits in emergency department patients with diabetes mellitus as a warning sign for hyperglycemic emergencies

Objectives

Patients with poorly controlled diabetes mellitus may have a sentinel emergency department (ED) visit for a precipitating condition prior to presenting for a hyperglycemic emergency, such as diabetic ketoacidosis (DKA) or hyperosmolar hyperglycemic state (HHS). This study’s objective was to describe the epidemiology and outcomes of patients with a sentinel ED visit prior to their hyperglycemic emergency visit.

Methods

This was a 1-year health records review of patients≥18 years old presenting to one of four tertiary care EDs with a discharge diagnosis of hyperglycemia, DKA, or HHS. Trained research personnel collected data on patient characteristics, management, disposition, and determined whether patients came to the ED within the 14 days prior to their hyperglycemia visit. Descriptive statistics were used to summarize the data.

Results

Of 833 visits for hyperglycemia, 142 (17.0%; 95% CI: 14.5% to 19.6%) had a sentinel ED presentation within the preceding 14 days. Mean (SD) age was 50.5 (19.0) years and 54.4% were male; 104 (73.2%) were discharged from this initial visit, and 98/104 (94.2%) were discharged either without their glucose checked or with an elevated blood glucose (>11.0 mmol/L). Of the sentinel visits, 93 (65.5%) were for hyperglycemia and 22 (15.5%) for infection. Upon returning to the ED, 61/142 (43.0%) were admitted for severe hyperglycemia, DKA, or HHS.

Conclusion

In this unique ED-based study, diabetic patients with a sentinel ED visit often returned and required subsequent admission for hyperglycemia. Clinicians should be vigilant in checking blood glucose and provide clear discharge instructions for follow-up and glucose management to prevent further hyperglycemic emergencies from occurring.

Risk factors for recurrent emergency department visits for hyperglycemia in patients with diabetes mellitus

Background

Patients with poorly controlled diabetes mellitus may present repeatedly to the emergency department (ED) for management and treatment of hyperglycemic episodes, including diabetic ketoacidosis and hyperosmolar hyperglycemic state. The objective of this study was to identify risk factors that predict unplanned recurrent ED visits for hyperglycemia in patients with diabetes within 30 days of initial presentation.

Methods

We conducted a 1-year health records review of patients ≥18 years presenting to one of four tertiary care EDs with a discharge diagnosis of hyperglycemia, diabetic ketoacidosis, or hyperosmolar hyperglycemic state. Trained research personnel collected data on patient characteristics and determined if patients had an unplanned recurrent ED visit for hyperglycemia within 30 days of their initial presentation. Multivariate logistic regression models using generalized estimating equations to account for patients with multiple visits determined predictor variables independently associated with recurrent ED visits for hyperglycemia within 30 days.

Results

There were 833 ED visits for hyperglycemia in the 1-year period. 54.6% were male and mean (SD) age was 48.8 (19.5). Of all visitors, 156 (18.7%) had a recurrent ED visit for hyperglycemia within 30 days. Factors independently associated with recurrent hyperglycemia visits included a previous hyperglycemia visit in the past month (odds ratio [OR] 3.5, 95% confidence interval [CI] 2.1–5.8), age <25 years (OR 2.6, 95% CI 1.5–4.7), glucose >20 mmol/L (OR 2.2, 95% CI 1.3–3.7), having a family physician (OR 2.2, 95% CI 1.0–4.6), and being on insulin (OR 1.9, 95% CI 1.1–3.1). Having a systolic blood pressure between 90–150 mmHg (OR 0.53, 95% CI 0.30–0.93) and heart rate >110 bpm (OR 0.41, 95% CI 0.23–0.72) were protective factors independently associated with not having a recurrent hyperglycemia visit.

Conclusions

This unique ED-based study reports five risk factors and two protective factors associated with recurrent ED visits for hyperglycemia within 30 days in patients with diabetes. These risk factors should be considered by clinicians when making management, prognostic, and disposition decisions for diabetic patients who present with hyperglycemia.

Electronic supplementary material

The online version of this article (doi:10.1186/s12245-017-0150-y) contains supplementary material, which is available to authorized users.

Unscheduled return visits to a pediatric emergency department

BACKGROUND AND OBJECTIVE

Return visits (RVs) to a pediatric emergency department (ED) within a short period after discharge have an influence on overcrowding of the ED and reveal some weaknesses of the health care system. The aim of this study was to determine the rate of RVs and factors related to RVs to the pediatric ED in Lithuania.

MATERIALS AND METHODS

A retrospective study in an urban, tertiary-level teaching hospital was carried out. Electronic medical records of all patients (n=44097) visiting the ED of this hospital between 1 January and 31 December 2013 were analyzed. Demographic and clinical characteristics of patients who return to the ED within 72h and those who had not visited the ED were compared. Factors associated with RVs were determined by multivariable logistic regression.

RESULTS

Of the overall ED population, 33889 patients were discharged home after the initial assessment. A total of 1015 patients returned to the ED within 72h, giving a RV rate of 3.0%. Being a 0-7-year old, visiting the ED during weekdays, having a GP referral, receiving of laboratory tests and ultrasound on the initial visit were associated with greater likelihoods of returning to the ED. Patients who arrived to the ED from 8:01a.m. to 4:00p.m. and underwent radiological test were less likely to return to the ED within 72h. Diseases such as gastrointestinal disorders or respiratory tract/earth-nose-throat (ENT) diseases and symptoms such as fever or pain were significantly associated with returning to the ED. The initial diagnosis corresponded to the diagnosis made on the second visit for only 44.1% of the patients, and the highest rate of the congruity in diagnosis was for injuries/poisoning, surgical pathologies (77.2%) and respiratory tract diseases (76.9%).

CONCLUSIONS

RVs accounted for only a small proportion of visits to the ED. RVs were more prevalent among younger patients and patients with a GP referral as well as performed more often after discharging from the ED in the evening and at night.

Which unscheduled return visits indicate a quality-of-care issue?

BACKGROUND

The rate of unscheduled return visits is often used as a quality-of-care indicator in EDs, although its validity is not yet fully established. Our aim was to identify the characteristics of return visits that may be attributed to problems in quality of care.

METHODS

Retrospective paired review of medical charts in a random sample of return visits during the 72 hours following discharge from the ED in three hospitals of Andalusia, Spain in 2013. Charts were reviewed by senior medical physicians to determine which return visits reflected quality-of-care problems. Time frame for return visit, index and return visit acuity, disposition and diagnosis were compared with determine which variables were associated with a quality problem. Sensitivity and specificity for each variable to indicate a quality problem were determined.

RESULTS

We studied the causes of 895 return visits, finding that 65 (7.3%) were due to inadequate quality of care in the index visit. Potentially avoidable return visits were more common in more severely ill patients, in those with greater severity in the return than in the index visit and in patients hospitalised after the return. The combination of this three variables presented sensitivity 66% and specificity 68% in identification of quality-related returns.

CONCLUSIONS

The overall level of return visits cannot be considered a valid indicator of quality of care. However, certain specific variables, including the level of severity of the patient's condition or the discharge destination following the return visits, could be considered valid in this respect.