Unplanned emergency department revisits within 72 hours to a secondary teaching referral hospital in Taiwan

Low-Risk Chest Pain Patients: Exploring the Impact of Socioeconomy on Emergency Department Revisits

BACKGROUND

Patients with chest pain and undetectable high-sensitivity cardiac troponin T (hs-cTnT) in the emergency department (ED) have a low short-term risk of cardiovascular events, but the frequency of ED revisits in this group is unknown. This study investigated the associations between disposable income and risk of ED revisits in patients with chest pain and undetectable hs-cTnT.

METHODS

All first visits to 7 EDs in Sweden from 2010 to 2017 by patients with chest pain and hs-cTnT <5 ng/l were included. Incidence rate ratios (IRR) were calculated to estimate the ED revisit risk in relation to disposable income according to data obtained from Swedish government agencies (Statistics Sweden).

RESULTS

Altogether, 61,539 patients with a first ED visit were included, in whom 126,650 revisits occurred. The adjusted 30-day risk of a revisit was 1.3- (IRR 1.32, 95% CI: 1.23-1.42) and 1.5-fold (IRR 1.50, 95% CI: 1.40-1.60), and for any revisit during the follow-up 1.6- (IRR 1.63, 95% CI: 1.59-1.66) and 1.8-fold (IRR 1.78, 95% CI 1.72-1.79), in patients with middle-low and low versus high income, respectively. During a median follow-up of 6.8 years, 1714 (2.8%) deaths occurred, and the adjusted cumulative incidence of major adverse cardiovascular events at 1 and 5 years was only 0.3% (95% CI: 0.2-0.4%) and 1.1% (95% CI: 0.8-1.4%) higher in patients with the lowest versus highest income levels.

CONCLUSIONS

Disposable income level is inversely associated with the risk of ED revisits among patients presenting with chest pain and undetectable hs-cTnT, in whom cardiovascular risks are low.

Extending emergency care beyond discharge: Piloting a virtual after care clinic

Objective

Many unscheduled return visits to the emergency department (ED) stem from insufficient access to outpatient follow-up. We piloted an emergency medicine-staffed, on-demand, virtual after care clinic (VACC) as an alternative for discharged ED patients.

Methods

Prospective cohort study of discharged ED patients who scheduled VACC appointments within 72 hours of index ED visit. We performed descriptive analyses and compared risks of ED return at 72 hours and 30 days between patients who did/did not attend their appointment.

Results

From March to December 2022, 309 patients scheduled VACC appointments and 210 (68%) attended them. Patients who scheduled appointments were young (median 37 years), non-Hispanic white (80%), females (75%) with a primary care physicians (PCP) (90%), and commercial insurance (72%).  Most VACC visits reinforced ED testing and/or treatment (64%) or adjusted medications (26%). VACC attendees were less likely to return to the ED within 72 h (3.3% vs. 13.1%; risk difference 9.3% [95% confidence interval, CI 2.7%‒19.8%]) and 30 days (16.2% vs. 30.3%; risk difference 14.1% [95% CI 3.8%‒24.4%]) compared to those who scheduled but did not attend a VACC appointment. VACC attendance was associated with lower odds of 72-h (adjusted odds ratio [aOR] 0.0; 95% CI 0.0‒0.4) and 30-day (aOR 0.4; 95% CI 0.2‒0.7) return ED visits.

Conclusions

In this pilot study, younger, white, female, commercially insured patients with a PCP preferentially scheduled VACC appointments. Among patients who scheduled VACC appointments, those who attended their appointments were less likely to return to the ED within 72 hours and 30 days than those who did not.

Neutrophil-to-lymphocyte ratio as a predictor for outcomes in patients with short-term emergency department revisits

BACKGROUND

Analysis of short-term emergency department (ED) revisits is a common emergency care quality assurance practice. Previous studies have explored various risk factors of ED revisits; however, laboratory data were usually omitted. This study aimed to evaluate the prognostic significance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), and systemic immune-inflammation index (SII) in predicting outcomes of patients revisiting the ED.

METHODS

This retrospective observational cohort study investigated short-term ED revisit patients. The primary outcome measure was high-risk ED revisit, a composite of in-hospital mortality or intensive care unit (ICU) admission after 72-hour ED revisit. The NLR, PLR, and SII were investigated as potential prognostic predictors of ED revisit outcomes.

RESULTS

A total of 1916 encounters with short-term ED revisit patients were included in the study; among these, 132 (6.9%) encounters, comprising 57 in-hospital mortalities and 95 ICU admissions, were high-risk revisits. High-risk revisit patients had significantly higher NLR, PLR, and SII (11.6 vs 6.6, p < 0.001; 26.2 vs 18.9, p = 0.004; 2209 vs 1486, p = 0.002, respectively). Multiple regression analysis revealed revisit-NLR as an independent factor for predicting poor outcomes post-ED revisits (odds ratio: 1.031, 95% CI: 1.017-1.045, p < 0.001); an optimal cut-off value of 7.9 was proven for predicting high-risk ED revisit.

CONCLUSION

The intensity of the inflammatory response expressed by NLR was an independent predictor for poor outcomes of ED revisits and should be considered when ED revisits occur. Future prediction models for ED revisit outcomes can include revisit-NLR as a potential predictor to reflect the progressive conditions in ED patients.

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.

Development and Internal Validation of a Multivariable Prediction Model to Predict Repeat Attendances in the Pediatric Emergency Department: A Retrospective Cohort Study

OBJECTIVE

Unplanned reattendances to the pediatric emergency department (PED) occur commonly in clinical practice. Multiple factors influence the decision to return to care, and understanding risk factors may allow for better design of clinical services. We developed a clinical prediction model to predict return to the PED within 72 hours from the index visit.

METHODS

We retrospectively reviewed all attendances to the PED of Royal Manchester Children's Hospital between 2009 and 2019. Attendances were excluded if they were admitted to hospital, aged older than 16 years or died in the PED. Variables were collected from Electronic Health Records reflecting triage codes. Data were split temporally into a training (80%) set for model development and a test (20%) set for internal validation. We developed the prediction model using LASSO penalized logistic regression.

RESULTS

A total of 308,573 attendances were included in the study. There were 14,276 (4.63%) returns within 72 hours of index visit. The final model had an area under the receiver operating characteristic curve of 0.64 (95% confidence interval, 0.63-0.65) on temporal validation. The calibration of the model was good, although with some evidence of miscalibration at the high extremes of the risk distribution. After-visit diagnoses codes reflecting a nonspecific problem ("unwell child") were more common in children who went on to reattend.

CONCLUSIONS

We developed and internally validated a clinical prediction model for unplanned reattendance to the PED using routinely collected clinical data, including markers of socioeconomic deprivation. This model allows for easy identification of children at the greatest risk of return to PED.

The association between the workload of emergency physicians and the outcomes of acute myocardial infarction: a population-based study

Acute myocardial infarction (AMI) is the second leading cause of mortality in Taiwan. The correlation between the workload of emergency physicians and the outcome of AMI remains unknown. To determine the effects of the workload of emergency physicians on the outcomes of AMI. We included 17 661 patients (age > 18 years) with STEMI undergoing PCI, who visited the emergency department between 2012 and 2018. We used the logistic regression model with generalized estimating equations (GEEs) to analyze the risk of death within 30 days after emergency department visit, the risk of emergency department revisits within 3 days, and the risk of readmission within 14 days in all subgroups. After covariate adjustment, the risk of mortality within 30 days after visiting the emergency department was significantly higher in the subgroup whose visiting emergency physicians had the highest workload (odds ratio [OR]: 1.39; 95% confidence interval [CI]: 1.12 to 1.72). Furthermore, the risk of revisiting the emergency department within 3 days after discharge from the hospital was significantly higher in the subgroup whose visiting emergency physicians' workload was within the second and third quartiles (OR 1.85; 95% CI 1.18 to 2.89). The workload of emergency physicians appears to be positively correlated with the mortality risk of patients with STEMI undergoing PCI.

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.

24-h PCI model does affect the outcome of STEMI patients: a population-based study

Acute myocardial infarction has been the second leading cause of death in Taiwan. It's a novel issue to evaluate the relationship between the 24-h PCI service model and the outcome of STEMI patients. The objective of this study was to determine the effect of 24-h PCI service model in STEMI patients to improving survival rate. This population-based cohort study included those STEMI patients, older than 18 year-old, who had ever called emergency department from 2012 to 2018. We had two groups of our study participant, one group for STEMI patients with 24-h PCI model and the other group for STEMI patients with non-24-h PCI model. We used the Logistic regression model to analyze the risk of death within 30 days, emergency department (ED) revisits within 3 days, and readmission within 14 days. After the relevant variables were controlled, the risk of death after an ED visit among the patients with STEMI who were sent to hospitals with 24-h PCI services was significantly lower than that among the patients with STEMI who were sent to hospitals without 24-h PCI services (OR 0.85; 95% CI 0.75-0.98). However, the model could not reduce the risk of ER revisits and readmission.

A simplified scoring model for predicting bacteremia in the unscheduled emergency department revisits: The SADFUL score

BACKGROUND

Bacteremia is a severe complication of infectious disease. Patients with a high bacteremia risk in the emergency department (ED) but misidentified would lead to the unscheduled revisits. This study aimed to develop a simplified scoring model to predict bacteremia in patients with unscheduled ED revisits.

METHODS

Adult patients with unscheduled ED revisits within 72 h with a final diagnosis of infectious disease were retrospectively included. The development cohort included patients visiting the ED from January 1, 2019 to December 31, 2021. Internal validation was performed in patients visiting the ED from January 1, 2022 to March 31, 2022. Variables including demographics, pre-comorbidities, triage levels, vital signs, chief complaints, and laboratory data in the index visit were analyzed. Bacteremia was the primary outcome determined by blood culture in either index visits or revisits.

RESULTS

The SADFUL score for predicting bacteremia comprised the following predictors: "S"egmented neutrophil percentage (+3 points), "A"ge > 55 years (+1 point), "D"iabetes mellitus (+1 point), "F"ever (+2 points), "U"pper respiratory tract symptoms (-2 points), and "L"eukopenia (2 points). The area under receiver operating characteristic curve with 95% confidence interval in the development (1802 patients, 190 [11%] with bacteremia) and the validation cohort (134 patients, 17 [13%] with bacteremia) were 0.78 (0.74-0.81) and 0.79 (0.71-0.88), respectively.

CONCLUSIONS

The SADFUL score is a simplified useful tool for predicting bacteremia in patients with unscheduled ED revisits. The scoring model could help ED physicians decrease misidentification of patients at a high risk for bacteremia and potential complications.

Healthcare-associated adverse events and readmission to the emergency departments within seven days after a first consultation

Introduction

The use of emergency hospital service has become increasingly frequent with a rise of approximately 3.6%. in annual emergency department visits. The objective of this study was to describe the reasons for reconsultations to emergency departments and to identify the risk and protective factors of reconsultations linked to healthcare-associated adverse events.

Materials and methods

A retrospective, descriptive, multicenter study was performed in the emergency department of Troyes Hospital and the Sainte Anne Army Training Hospital in Toulon, France from January 1 to December 31, 2019. Patients over 18 years of age who returned to the emergency department for a reconsultation within 7 days were included. Healthcare-associated adverse events in the univariate analysis (p < 0.10) were introduced into a multivariate logistic regression model. Model performance was examined using the Hosmer-Lemeshow test and calculated with c-statistic.

Results

Weekend visits and performing radiology examinations were risk factors linked to healthcare associated adverse events. Biological examinations and the opinion of a specialist were protective factors.

Discussion

Numerous studies have reported that a first consultation occurring on a weekend is a reconsultation risk factor for healthcare-associated adverse events, however, performing radiology examinations were subjected to confusion bias. Patients having radiology examinations due to trauma-related pathologies were more apt for a reconsultation.

Conclusion

Our study supports the need for better emergency departments access to biological examinations and specialist second medical opinions. An appropriate patient to doctor ratio in hospital emergency departments may be necessary at all times.

Frequencies and reasons for unplanned emergency department return visits by older adults: a cohort study

BACKGROUND

As unplanned Emergency Department (ED) return visits (URVs) are associated with adverse health outcomes in older adults, many EDs have initiated post-discharge interventions to reduce URVs. Unfortunately, most interventions fail to reduce URVs, including telephone follow-up after ED discharge, investigated in a recent trial. To understand why these interventions were not effective, we analyzed patient and ED visit characteristics and reasons for URVs within 30 days for patients aged ≥ 70 years.

METHODS

Data was used from a randomized controlled trial, investigating whether telephone follow-up after ED discharge reduced URVs compared to a satisfaction survey call. Only observational data from control group patients were used. Patient and index ED visit characteristics were compared between patients with and without URVs. Two independent researchers determined the reasons for URVs and categorized them into: patient-related, illness-related, new complaints and other reasons. Associations were examined between the number of URVs per patient and the categories of reasons for URVs.

RESULTS

Of the 1659 patients, 222 (13.4%) had at least one URV within 30 days. Male sex, ED visit in the 30 days before the index ED visit, triage category "urgent", longer length of ED stay, urinary tract problems, and dyspnea were associated with URVs. Of the 222 patients with an URV, 31 (14%) returned for patient-related reasons, 95 (43%) for illness-related reasons, 76 (34%) for a new complaint and 20 (9%) for other reasons. URVs of patients who returned ≥ 3 times were mostly illness-related (72%).

CONCLUSION

As the majority of patients had an URV for illness-related reasons or new complaints, these data fuel the discussion as to whether URVs can or should be prevented.

TRIAL REGISTRATION

For this cohort study, we used data from a randomized controlled trial (RCT). This trial was pre-registered in the Netherlands Trial Register with number NTR6815 on the 7^th of November 2017.

ED Revisits Within 72 Hours to a Tertiary Health Care Facility in Dubai: A Descriptive Study

Unplanned emergency department (ED) revisit is one of the major challenges faced by emergency care facilities and reflects their quality of care. It is an important key performance indicator (KPI) for emergency medical care. Often, inadequate medical care by physicians is claimed to be the main cause of unplanned ED revisits, yet this assumption is not well studied in the literature. Thus, this study aimed to identify the causes of unplanned ED revisits within 72 hours from the initial visit to the emergency department which could help in developing an action plan and improve quality of care and patient safety. A retrospective study was conducted in Rashid Hospital Trauma Center, from December 2019 to January 2020, using electronic medical records reviewed by two independent investigators. The reasons for the ED revisits were categorized into the following four domains: illness, physician, patient, and system related. A total of 584 revisits were found which accounted for 1.9% of ED attendance from December 2019 to January 2020. Majority of them were male patients, and 63% of the population had a mean age of 33 years. Majority of the ED revisits were due to illness (54%), followed by patient related (20%), physician related (18%), and system related (8%) factors. Most of the patients were discharged on the second visit. The two most common reasons for revisits in the ED department that were seen within the 72 hours were illness related and patient related, followed by physician related. The cause is mainly rooted in suboptimal discharge plans.

Risk factors associated with 1-week revisit among emergency department patients with alcohol withdrawal

BACKGROUND

Approximately one-quarter of emergency department (ED) visits for alcohol withdrawal result in unscheduled 1-week ED return visits, but it is unclear what patient and clinical factors may impact this outcome METHODS: From January 1, 2015, to December 31, 2018, at three urban EDs in Vancouver, Canada, we studied patients who were discharged with a primary or secondary diagnosis of alcohol withdrawal. We performed a structured chart review to ascertain patient characteristics, ED treatments, and the outcome of an ED return within 1 week of discharge. We used univariable and multivariable Bayesian binomial regression to identify characteristics associated with being in the upper quartile of 1-week ED revisits.

RESULTS

We collected 935 ED visits among 593 unique patients. Median age was 45 years (interquartile range 34 to 55 years) and 71% were male. The risk of a 1-week ED revisit was 15.0% (IQR 12.3; 19.5%). After adjustment, factors independently associated with a high risk for return included any prior ED visit within 30 days, no fixed address, initial blood alcohol level > 45 mmol/L, and initial Clinical Institute Withdrawal Assessment-alcohol revised score > 23. These factors explained 41% of the overall variance in revisits.

CONCLUSION

Among discharged ED patients with alcohol withdrawal, we describe high-risk patient characteristics associated with 1-week ED revisits, and these findings may assist clinicians to facilitate appropriate discharge planning with access to integrated follow-up support.

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.

High-risk Return Visits to United States Emergency Departments, 2010–2018

Introduction: Although factors related to a return visit to the emergency department (ED) have been reported, only a few studies have examined “high-risk” ED revisits with serious adverse outcomes. In this study we aimed to describe the incidence and trend of high-risk ED revisits in United States EDs and to investigate factors associated with these revisits. Methods: We obtained data from the National Hospital Ambulatory Medical Care Survey (NHAMCS), 2010–2018. Adult ED revisits within 72 hours of a previous discharge were identified using a mark on the patient record form. We defined high-risk revisits as revisits with serious adverse outcomes, including intensive care unit admissions, emergency surgery, cardiac catheterization, or cardiopulmonary resuscitation (CPR) during the return visit. We performed analyses using descriptive statistics and multivariable logistic regression, accounting for NHAMCS’s complex survey design. Results: Over the nine-year study period, there were an estimated 37,700,000 revisits, and the proportion of revisits in the entire ED population decreased slightly from 5.1% in 2010 to 4.5% in 2018 (P for trend = 0.02). By contrast, there were an estimated 827,000 high-risk ED revisits, and the proportion of high-risk revisits in the entire ED population remained stable at approximately 0.1%. The mean age of these high-risk revisit patients was 57 years, and 43% were men. Approximately 6% of the patients were intubated, and 13% received CPR. Most of them were hospitalized, and 2% died in the ED. Multivariable analysis showed that older age (65+ years), Hispanic ethnicity, daytime visits, and arrival by ambulance during the revisit were independent predictors of high-risk revisits. Conclusion: High-risk revisits accounted for a relatively small fraction (0.1%) of ED visits. Over the period of the NHAMCS survey between 2010-2018, this fraction remained stable. We identified factors during the return visit that could be used to label high-risk revisits for timely intervention.

Comparison of outcomes in emergency department revisiting patients before and after coronavirus disease 2019 epidemic

BACKGROUND AND IMPORTANCE

The outbreak of COVID-19 challenged the global health system and specifically impacted the emergency departments (EDs). Studying the quality indicators of ED care under COVID-19 has been a necessary task, and ED revisits have been used as an indicator to monitor ED performance.

OBJECTIVES

The study investigated whether discrepancies existed among ED revisiting cases before and after COVID-19 and whether the COVID-19 epidemic was a predictor of poor outcomes of ED revisits.

DESIGN

Retrospective study.

SETTINGS AND PARTICIPANTS

We used electronic health records data from a tertiary medical center. Data of patients with 72-h ED revisit after the COVID-19 epidemic were collected from February 2020 to June 2020 and compared with those of patients before COVID-19, from February 2019 to June 2019.

OUTCOME MEASURES AND ANALYSIS

The investigated outcomes included hospital admission, ICU admission, out-of-hospital cardiac arrest, and subsequent inhospital mortality. Univariate and multivariate logistic regression models were used to identify independent predictors of 72-h ED revisit outcomes.

MAIN RESULTS

In total, 1786 patients were enrolled in our study - 765 in the COVID group and 1021 in the non-COVID group. Compared with the non-COVID group, patients in the COVID group were younger (53.9 vs. 56.1 years old; P = 0.002) and more often female (66.1% vs. 47.3%; P < 0.001) and had less escalation of triage level (11.6% vs. 15.0%; P = 0.041). The hospital admission and inhospital mortality rates in the COVID and non-COVID groups were 33.9% vs. 32.0% and 2.7% vs. 1.5%, respectively. In the logistic regression model, the COVID-19 period was significantly associated with inhospital mortality (adjusted odds ratio, 2.289; 95% confidence interval, 1.059-4.948; P = 0.035).

CONCLUSION

Patients with 72-h ED revisits showed distinct demographic and clinical patterns before and after the COVID-19 epidemic; the COVID-19 period was an independent predictor of increased inhospital mortality.

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.

Safety assessment of a redirection program using an electronic application for low-acuity patients visiting an emergency department

Background

Emergency departments (EDs) are operating at or above capacity, which has negative consequences on patients in terms of quality of care and morbi-mortality. Redirection strategies for low-acuity ED patients to primary care practices are usually based on subjective eligibility criteria that sometimes necessitate formal medical assessment. Literature investigating the effect of those interventions is equivocal. The aim of the present study was to assess the safety of a redirection process using an electronic clinical support system used by the triage nurse without physician assessment.

Methods

A single cohort observational study was performed in the ED of a level 1 academic trauma center. All low-acuity patients redirected to nearby clinics through a clinical decision support system (February–August 2017) were included. This system uses different sets of medical prerequisites to identify patients eligible to redirection. Data on safety and patient experience were collected through phone questionnaires on day 2 and 10 after ED visit. The primary endpoint was the rate of redirected patients returning to any ED for an unexpected visit within 48 h. Secondary endpoints were the incidence of 7-day return visit and satisfaction rates.

Results

A total of 980 redirected low-acuity patients were included over the period: 18 patients (2.8%) returned unexpectedly to an ED within 48 h and 31 patients (4.8%) within 7 days. No hospital admission or death were reported within 7 days following the first ED visit. Among redirected patients, 81% were satisfied with care provided by the clinic staff.

Conclusion

The implementation of a specific electronic-guided decision support redirection protocol appeared to provide safe deferral to nearby clinics for redirected low-acuity patients. EDs are pivotal elements of the healthcare system pathway and redirection process could represent an interesting tool to improve the care to low-acuity patients.

Characteristics of an Unscheduled Emergency Department Revisit Within 72 hours of Discharge

Background

An unscheduled emergency department (ED) revisit is defined as a patient presenting to the ED with the same problem within 72 hours of discharge. The revisits result in overcrowding and compromise the care provided by the ED. We assume that the poor quality of care provided by the ED is the reason for revisiting. However, the circumstances surrounding these revisits are not well-understood. We conducted this study to understand the characteristics associated with the revisits.

Objectives

We aimed to identify the common causes of ED revisits within 72 hours of discharge and determine the outcome of these patients during the revisit.

Methods

We conducted a prospective observational study at a tertiary care center from July 2015 to June 2017, including patients presenting at the ED within 72 hours after their first visit. Our study selected 50 patients using a simple random sampling method and identified the leading causes of revisit as doctor-related, patient-related, and illness-related.

Results

We found that 56% (28/50) of patients returned to the ED for illness-related reasons, 26% (13/50) for doctor-related reasons, and 18% (9/50) for patient-related reasons. In addition, we found that 62% (31/50) of patients who returned to the ED within 72 hours required in-patient admission.

Conclusion

The most common cause of ED revisit was illness-related causes, and more than half of the patients during a revisit required in-patient admission. The modifiable causes of the ED revisit, such as doctor-related and patient-related factors, were discovered in this study. These findings may aid in reducing ED revisits and improving the ED quality.

Return visits to the emergency department: An analysis using group based curve models

Stratification modeling in health services is useful to identify differential patient risk groups, or latent classes. Given the frequency and costs, repeated emergency department (ED) may be an appropriate candidate for risk stratification modeling. We applied a method called group-based trajectory modeling (GBTM) to a sample of 37,416 patients who visited an urban, safety-net ED between 2006 and 2016. Patients had up to 10 ED visits during the study period. Data sources included the hospital's electronic health record (EHR), the state-wide health information exchange system, and area-level social determinants of health factors. Results revealed three distinct trajectory groups. Trajectories with a higher risk of revisit were marked by more patients with behavioral diagnoses, injuries, alcohol & substance abuse, stroke, diabetes, and other factors. The application of advanced computational techniques, like GBTM, provides opportunities for health care organizations to better understand the underlying risks of their large patient populations. Identifying those patients who are likely to be members of high-risk trajectories allows healthcare organizations to stratify patients by level of risk and develop early targeted interventions.

Intravenous antibiotics at the index emergency department visit as an independent risk factor for hospital admission at the return visit within 72 hours

Introduction

Although infection was the most common symptom in patients returning to the ED, whether intravenous antibiotic administration at the index visit could serve as an indicator of patients with infectious diseases at high risk for hospital admission after returning to the ED within a short period of time remains unclear. The study aimed to investigate the potential risk factors for hospital admission in patients returning to the ED within 72 hours with a final diagnosis of infectious diseases.

Material and methods

This retrospective cohort study analyzed return visits to the ED from January to December 2019. Adult patients aged >20 years who had a return visit to the ED within 72 hours with an infectious disease were included herein. In total, 715 eligible patients were classified into the intravenous antibiotics and non-intravenous antibiotics group (reference group). The outcome studied was hospital admission to general ward and intensive care unit (ICU) at the return visits.

Results

Patients receiving intravenous antibiotics at index visits had significantly higher risk—approximately two times—for hospital admission at the return visits than those did not (adjusted odds ratio = 2.47, 95% CI = 1.34–4.57, p = 0.004). For every 10 years increase in age, the likelihood for hospital admission increased by 38%. Other factors included abnormal respiratory rate and high C-reactive protein levels.

Conclusions

Intravenous antibiotic administration at the index visit was an independent risk factor for hospital admission at return visits in patients with an infection disease. Physicians should consider carefully before discharging patients receiving intravenous antibiotics.

Clinician perspectives on reasons for, implications and management of unplanned patient returns to the Emergency Department: A descriptive study

BACKGROUND

Unplanned return visits to the emergency department (ED) have been associated with adverse outcomes and may reflect the quality of care delivered. Several studies speculate the reasons for return and suggest clinician behaviour as potentially influencing a patient's decision to return to the ED. There is little research about this issue from the clinician's perspective, which is necessary to inform future practice improvement.

METHODS

A descriptive cross sectional design was employed to ascertain perspectives on identification and management of return visits occurring within 48 hours of discharge. An electronic survey was distributed to all medical, nursing, and clerical staff at one ED. Descriptive statistics were used for quantitative data and content analysis was performed on textual data. Results were categorised as barriers or facilitators, then mapped to the Theoretical Domains Framework.

RESULTS

A response rate of 59.7% (n=86/144) was achieved. Staff reported increased levels of concern for this patient group but not all staff were aware of the policy for managing return patients (40.7%). Five barriers and three facilitators were identified that mapped to eight influencers of behaviour including knowledge, memory and environmental factors.

CONCLUSION

Overall, staff were aware of return patients but lacked familiarity with policy and processes to identify and commence relevant protocols. Further review of current practice as well as the patient perspective is required before any intervention to improve practice is developed.

Odds of return: a prospective study using provider assessment to predict short-term patient return visits to the emergency department

OBJECTIVE

Previous studies have assessed patient-level characteristics associated with emergency department (ED) return visits, but none have used provider assessment. We prospectively investigate whether clinical providers could accurately predict ED return visits.

METHODS

Prospective cohort study.

SETTING

Single academically affiliated urban county hospital.

PARTICIPANTS

Discharged ED patients over a 14-month period with a provider assessment of the likelihood of patient return within 7 days of ED discharge.

MAIN OUTCOME MEASURES

The primary outcome of interest was a return visit to the ED within 7 days. Additional outcome measures included a return visit within 72 hours and a return visit resulting in admission. We also measured the accuracy of provider gestalt, and provide measures of sensitivity, specificity, predictive values, and likelihood ratios.

RESULTS

Of the 11 922 ED discharges included in this study, providers expected 2116 (17.7%) to result in a return visit within 7 days. Providers were much more likely to perceive a return visit if the patient left against medical advice (OR: 5.97, 95% CI: 4.67 to 7.62), or was homeless (OR: 5.69, 95% CI: 5.14 to 6.29). Patients who actually returned were also more likely to be homeless, English speaking and to have left the ED against medical advice on the initial encounter. The strongest predictor of a return visit at both 72 hours and 7 days in multivariable modelling was provider assessment (OR: 3.77, 95% CI: 3.25 to 4.37; OR: 3.72, 95% CI: 3.29 to 4.21, respectively). Overall sensitivity and specificity of provider gestalt as a measure of patient return within 7 days were 47% and 87%, respectively. The positive and negative likelihood ratios were 3.51 and 0.61, respectively.

CONCLUSIONS

Clinician assessment was the strongest predictor of a return visit in this dataset. Clinician assessment may be used as a way to screen patients during the index visit and enrol them in efforts to decrease return visits.

Impact of diagnostic errors on adverse outcomes: learning from emergency department revisits with repeat CT or MRI

Background

To investigate diagnostic errors and their association with adverse outcomes (AOs) during patient revisits with repeat imaging (RVRIs) in the emergency department (ED).

Results

Diagnostic errors stemming from index imaging studies and AOs within 30 days in 1054 RVRIs (≤ 7 days) from 2005 to 2015 were retrospectively analyzed according to revisit timing (early [≤ 72 h] or late [> 72 h to 7 days] RVRIs). Risk factors for AOs were assessed using multivariable logistic analysis. The AO rate in the diagnostic error group was significantly higher than that in the non-error group (33.3% [77 of 231] vs. 14.8% [122 of 823], p < .001). The AO rate was the highest in early revisits within 72 h if diagnostic errors occurred (36.2%, 54 of 149). The most common diseases associated with diagnostic errors were digestive diseases in the radiologic misdiagnosis category (47.5%, 28 of 59) and neurologic diseases in the delayed radiology reporting time (46.8%, 29 of 62) and clinician error (27.3%, 30 of 110) categories. In the matched set of the AO and non-AO groups, multivariable logistic regression analysis revealed that the following diagnostic errors contributed to AO occurrence: radiologic error (odds ratio [OR] 3.56; p < .001) in total RVRIs, radiologic error (OR 3.70; p = .001) and clinician error (OR 4.82; p = .03) in early RVRIs, and radiologic error (OR 3.36; p = .02) in late RVRIs.

Conclusion

Diagnostic errors in index imaging studies are strongly associated with high AO rates in RVRIs in the ED.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01108-0.

Telephone follow-up to reduce unplanned hospital returns for older emergency department patients: A randomized trial

BACKGROUND/OBJECTIVES

Telephone follow-up calls could optimize the transition from the emergency department (ED) to home for older patients. However, the effects on hospital return rates are not clear. We investigated whether telephone follow-up reduces unplanned hospitalizations and/or unplanned ED return visits within 30 days of ED discharge.

DESIGN

Pragmatic randomized controlled trial with allocation by month; odd months intervention group, even months control group.

SETTING

Two ED locations of a non-academic teaching hospital in The Netherlands.

PARTICIPANTS

Community-dwelling adults aged ≥70 years, discharged home from the ED were randomized to the intervention group (N = 4732) or control group (N = 5104).

INTERVENTION

Intervention group patients: semi-scripted telephone call from an ED nurse within 24 h after discharge to identify post-discharge problems and review discharge instructions. Control group patients: scripted satisfaction survey telephone call.

MEASUREMENTS

Primary outcome: total number of unplanned hospitalizations and/or ED return visits within 30 days of ED discharge.

SECONDARY OUTCOMES

separate numbers of unplanned hospitalizations and ED return visits. Subgroup analysis by age, sex, living condition, and degree of crowding in the ED at discharge.

RESULTS

Overall, 42% were males, and median age was 78 years. In the intervention group, 1516 of 4732 patients (32%) consented, and in the control group 1659 of 5104 (33%) patients. Unplanned 30-day hospitalization and/or ED return visit was found in 16% of intervention group patients and 14% of control group patients (odds ratio 1.16; 95% confidence interval: 0.96-1.42). Also, no statistically significant differences were found in secondary outcome measures. Within the subgroups, the intervention did not have beneficial effects for the intervention group.

CONCLUSION

Telephone follow-up after ED discharge in older patients did not result in reduction of unplanned hospital admissions and/or ED return visits within 30 days. These results raise the question of whether other outcomes could be improved by post-discharge ED telephone follow-up.

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.

Factors associated with a high-risk return visit to the emergency department: a case-crossover study

BACKGROUND AND IMPORTANCE

Although factors related to a return emergency department (ED) visit have been reported, few studies have examined 'high-risk' return ED visits with serious adverse outcomes. Understanding factors associated with high-risk return ED visits may help with early recognition and prevention of these catastrophic events.

OBJECTIVES

We aimed to (1) estimate the incidence of high-risk return ED visits, and (2) to investigate time-varying factors associated with these revisits.

DESIGN

Case-crossover study.

SETTINGS AND PARTICIPANTS

We used electronic clinical warehouse data from a tertiary medical center. We retrieved data from 651 815 ED visits over a 6-year period. Patient demographics and computerized triage information were extracted.

OUTCOME MEASURE AND ANALYSIS

A high-risk return ED visit was defined as a revisit within 72 h of the index visit with ICU admission, receiving emergency surgery, or with in-hospital cardiac arrest during the return ED visit. Time-varying factors associated with a return visit were identified.

MAIN RESULTS

There were 440 281 adult index visits, of which 19 675 (4.5%) return visits occurred within 72 h. Of them, 417 (0.1%) were high-risk revisits. Multivariable analysis showed that time-varying factors associated with an increased risk of high-risk revisits included the following: arrival by ambulance, dyspnea, or chest pain on ED presentation, triage level 1 or 2, acute change in levels of consciousness, tachycardia (>90/min), and high fever (>39°C).

CONCLUSIONS

We found a relatively small fraction of discharges (0.1%) developed serious adverse events during the return ED visits. We identified symptom-based and vital sign-based warning signs that may be used for patient self-monitoring at home, as well as new-onset signs during the return visit to alert healthcare providers for timely management of these high-risk revisits.

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.

Higher Frequency of Undetected Acute Coronary Syndrome in Elderly Patients with Chest Pain Who Visited the Emergency Department: A Large-Cohort Retrospective Study

Background

Acute coronary syndrome (ACS) is a critical disease encountered in the emergency department (ED). Despite the development of diagnostic tools, it may be difficult to diagnose ACS because of atypical symptoms and equivocal test results. We investigated the difference in the rates of revisit and undetected ACS between adult and elderly patients who visited the ED with chest pain.

Method

Data from 11,323 patients who visited the ED with chest pain at university hospitals in Korea were retrospectively analyzed. The cohort was categorized into two age groups: the adult (30–64 years) and elderly (>65 years). Baseline characteristic data (age, sex, vital signs, triage category, etc.) were obtained. We selected patients who revisited the ED within 30 d and investigated whether ACS was diagnosed.

Result

The revisit rate was higher in the elderly (12%) than in the adult group (8.3%). The rate of undetected ACS among the revisited patients was 2.91% (18/7,186) in adults and 6.08% (16/1,998) in elderly patients.

Conclusion

Elderly patients with chest pain had an increased rate of ED revisits and undetected ACS than adult patients. We recommend that old patients should be hospitalized to observe the progression of cardiac complaints or receive short-term follow-up.

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.

Frequency, Causes, and Outcomes of Return Visits to the Emergency Department Within 72 Hours: A Retrospective Observational Study

Background

Emergency departments (EDs) serve as an accessible gateway to healthcare system wherein numerous patients consider it a prime choice for medical complaints. Frequency of ED revisits, causes, and its burden are necessary to assess quality of care provided to patients and identify factors that leads to revisit.

Patients and Methods

Electronic and printed medical records of all patients who revisited ED from January to May 2016 within 72 hours of initial visit were reviewed. Patients’ cause of revisit were classified to three categories: patient-, physician- and system-related factors. Common complaints that require revisits were also collected. Descriptive analysis was performed and categorical variables were represented by the frequency; percentages and continuous variables were presented as median, and range if data did not follow normal distribution.

Results

Of the 79,279 patients who visited ED during the study period, 1.3% (1000) patients revisited within 72 hours; 51.3% (n=513) were males, with a mean age of 31.5 years (SD=17.7 years) where majority (57.1%) had no comorbidity recorded. The most attributed factors for revisit were as follows: patient-related causes 635 patients (63.5%), physician-related factors 167 patients (16.7%), and system-related factors 42 patients (4.2%); 15.6% were found not related to the initial visit. Recurrence of the same complaint was the highest among patient-related factors (80.5%), inadequate management and no improvement of symptoms in 71.3% among the physician-related factors. The most common ED revisit complaint was fever 29.1% (n=291). Outcomes of the revisit were mainly patient discharge 96.7% (n=967), admission 1.2% (n=12) and death in 0.2% (n=2).

Conclusion

Recurrence of the same complaint with no symptoms improvement and suboptimal management of physicians contributed to most of the ED revisits within 72 hours. Encouraging physicians to provide clear instructions in educating patients on discharge regarding disease progression and its red flags as to when a return to ED, might help in reducing revisit rate.

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.

Application of Machine Learning Techniques to Analyze Patient Returns to the Emergency Department

The study of the quality of hospital emergency services is based on analyzing a set of indicators such as the average time of first medical attention, the average time spent in the emergency department, degree of completion of the medical report and others. In this paper, an analysis is presented of one of the quality indicators: the rate of return of patients to the emergency service less than 72 h from their discharge. The objective of the analysis was to know the variables that influence the rate of return and which prediction model is the best. In order to do this, the data of the activity of the emergency service of a hospital of a reference population of 290,000 inhabitants were analyzed, and prediction models were created for the binary objective variable (rate of return to emergencies) using the logistic regression techniques, neural networks, random forest, gradient boosting and assembly models. Each of the models was analyzed and the result shows that the best model is achieved through a neural network with activation function tanh, algorithm levmar and three nodes in the hidden layer. This model obtains the lowest mean squared error (MSE) and the best area under the curve (AUC) with respect to the rest of the models used.

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.

The rate of short-term revisits after diagnosis of non-specific abdominal pain is similar for surgeons and emergency physicians - results from a single tertiary hospital emergency department

Background

Acute abdominal pain can be a diagnostic challenge even for experienced surgeons. Delayed diagnosis can lead to higher morbidity, mortality and increased costs. While readmission rate has been used to evaluate quality of surgical care, studies addressing the issue in emergency departments (ED) are rare. The role of emergency physicians in the care of patients with abdominal pain is increasing in many European countries, including Finland. It is not known whether this has an effect on the number of readmissions.

Here we evaluate whether the increasing role of emergency physicians in examining patients presenting with abdominal pain has affected the rate of short-term revisits among patients with non-specific abdominal pain (NSAP).

Methods

We identified consecutive ED patients receiving a diagnosis of NSAP 1.1. 2015–31.12.2016 in the ED of Tampere University Hospital. Those revisiting the ED within 48 h were selected for further analysis. Data were obtained from electronic medical records. We compared the outcomes of those initially examined by surgeons and by emergency physicians.

Results

During the study period, 173,630 patients visited our ED, of whom 6.1% (n = 10,609) were discharged with a diagnosis of NSAP. Only 3.0% of patients revisited the ED, 0.7% required hospitalization and 0.06% immediate surgery. The short-term revisit rates among those originally examined by surgeons and by emergency physicians were similar, 2.8 and 3.2% respectively (p = 0.193).

Conclusions

The rate of short-term revisits in patients with NSAP was altogether low. The increasing role of emergency physicians in the care of acute abdominal patients did not affect the revisit rate.

"Analysis of readmissions to the emergency department among patients presenting with abdominal pain"

BACKGROUND

Abdominal pain is one of the most common complaints among patients admitted to the Emergency Department (ED). Diagnosis and management of abdominal pain may be a challenge and there are patients who require admission to the ED more than once in a short period of time. Our purpose was to assess the incidence of readmissions among patients treated in the ED due to abdominal pain and to investigate the impact of readmission on the further course of treatment.

METHODS

We conducted a prospective observational study, which included patients admitted to the ED in one academic, teaching hospital presenting with non-traumatic abdominal pain in a three-month period. Analyzed factors included demographic data, details related to first and subsequent visits in the ED and the course of hospitalization.

RESULTS

Overall, 928 patients were included to the study and 101 (10.88%) patients were admitted to the ED more than once during three-month period. Patients visiting ED repeatedly were older (p = 0.03) and more likely to be hospitalized (p < 0.01) compared to single-visit patients. Patients during their subsequent visits spent more time in the ED (p = 0.01), had greater chance to repeat their appointment (p = 0.04), be admitted to the hospital (p < 0.01) and were more likely diagnosed with cholelithiasis (p = 0.03) compared to patients on their initial visit. If admitted to the surgical department they were also more often qualified for surgical procedure than patients on their first visit (p < 0.01). In a group of patients admitted to the surgical department there were no significant differences in rates of conversion, postoperative complications and mortality between subgroups.

CONCLUSIONS

Readmissions among patients presenting with abdominal pain are a common phenomenon with prevalence of 10.88%. They are most commonly associated with cholelithiasis and occur more frequently among older patients, which suggests, that elderly require more attention during ED managements.

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.

The Association Between Emergency Department Revisit and Elderly Patients

BACKGROUND

Emergency department (ED) revisits may be associated with a higher percentage of adverse events and increased costs. Our hospital is a university affiliation hospital accepted regional referral patients, and located in the region in Taiwan with the highest percentage of elderly people. In this study, we attempted to identify whether old age was a risk factor of ED revisit.

METHODS

Patients who visited the ED from July 2011 to June 2016 were included. Factors associated with revisit were collected from medical information database. A total of 239,405 patients were included in our study, with 13,272 having ED revisits within 72 hours. Chi square and independent t test were applied for univariable factors, and a logistic regression model was used for multivariable analysis.

RESULTS

Old age (age ≥ 65 years) was found to be a risk factor for ED revisit (odds ratio [OR]: 1.14; 95% confidence interval [CI]: 1.09-1.19). Diagnosis, pulse rate, diastolic blood pressure, fever, pain management, paracentesis, triage level, registration category, male gender, discharge status, and major illness may have some effect on ED revisit.

CONCLUSIONS

In our patients, old age is a risk factor for ED revisit; however, only a weak association was found.

Efficacy of electroacupuncture on acute abdomen emergency care: study protocol for a randomized controlled trial

BACKGROUND

Acute abdomen is a common disease in the emergency department (ED) and usually results in huge medical expenditure. To relieve abdominal pain effectively and reduce bed occupancy rate in emergency rooms, electroacupuncture is a practical method in the treatment of abdominal pain.

METHODS/DESIGN

Five hundred patients will be randomly and evenly divided into experimental and control groups. Both groups should have their basic information taken and their bilateral acupuncture points ( Hegu (LI 4), Neiguan (PC6), Zusanli (ST 36), Shangjuxu (ST37), Xiajuxu (ST39), Taichong (LR3), and Taibai (SP3)) will be intervened by electroacupuncture or vaccaria Seeds, in this clinical study. Electroacupuncture has been introduced to this experiment as an auxiliary technique. The experimental group will receive real electroacupuncture, but the control group will receive a placebo electroacupuncture in which transcutaneous electrical nerve stimulation will not be turned on. After the intervention, we will evaluate the difference in abdominal pain, the length of stay at the emergent observation ward, and the proportion of revisits with abdominal pain.

DISCUSSION

In Taiwan, medical expenditure is increasing annually because of the higher bed occupancy caused by acute abdominal pain in the hospital. We expect that the combined treatment of electroacupuncture and modern medical treatment will not only reduce bed occupancy and the length of ED stay but also effectively decrease the rate of readmission and revisits by 72 h. By means of electroacupuncture, the spiraling cost of health care can eventually be reduced.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT03199495. Registered on 27 June 2017.

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.

Application of the Informatics Stack framework to describe a population-level emergency department return visit continuous quality improvement program

INTRODUCTION

Population health programs are increasingly reliant on Health Information Technology (HIT). Program HIT architecture description is a necessary step prior to evaluation. Several sociotechnical frameworks have been used previously with HIT programs. The Informatics Stack is a novel framework that provides a thorough description of HIT program architecture. The Emergency Department Return Visit Quality Program (EDRVQP) is a population-level continuous quality improvement (QI) program connecting EDs across Ontario. The objectives of the study were to utilize the Informatics Stack to provide a description of the EDRVQP HIT architecture and to delineate population health program factors that are enablers or barriers.

MATERIALS AND METHODS

The Informatics Stack was used to describe the HIT architecture. A qualitative study was completed with semi-structured interviews of key informants across stakeholder organizations. Emergency departments were selected randomly. Purposive sampling identified key informants. Interviews were conducted until saturation. An inductive qualitative analysis using grounded theory was completed. A literature review of peer-reviewed background literature, and stakeholder organization reports was also conducted.

RESULTS

23 business actors from 15 organizations were interviewed. The EDRVQP architecture description is presented across the Informatics Stack levels. The levels from most comprehensive to most basic are world, organization, perspectives/roles, goals/functions, workflow/behaviour/adoption, information systems, modules, data/information/knowledge/wisdom/algorithms, and technology. Enabling factors were the high rate of electronic health record adoption, legislative mandate for data collection, use of functional data standards, implementation flexibility, leveraging validated algorithms, and leveraging existing local health networks. Barriers were privacy legislation and a high turn-around time.

DISCUSSION

The Informatics Stack provides a robust approach to thoroughly describe the HIT architecture of population health programs prior to program replication. The EDRVQP is a population health program that illustrates the pragmatic use of continuous QI methodology across a population (provincial) level.

Data mining techniques utilizing latent class models to evaluate emergency department revisits

BACKGROUND

The use of machine learning techniques is especially pertinent to the composite and challenging conditions of emergency departments (EDs). Repeat ED visits (i.e. revisits) are an example of potentially inappropriate utilization of resources that can be forecasted by these techniques.

OBJECTIVE

To track the ED revisit risk over time using the hidden Markov model (HMM) as a major latent class model. Given the HMM states, we carried out forecasting of future ED revisits with various data mining models.

METHODS

Information integrated from four distributed sources (e.g. electronic health records and health information exchange) was integrated into four HMMs which capture the relationships between an observed and a hidden progression that shift over time through a series of hidden states in an adult patient population.

RESULTS

Assimilating a pre-analysis of the various patients by applying latent class models and directing them to well-known classifiers functioned well. The performance was significantly better than without utilizing pre-analysis of HMM for all prediction models (classifiers(.

CONCLUSIONS

These findings suggest that one prospective approach to advanced risk prediction is to leverage the longitudinal nature of health care data by exploiting patients' between state variation.

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.

The Effects of Discrete Work Shifts on a Nonterminating Service System

Hospital emergency departments (EDs) provide around-the-clock medical care, and as such are generally modeled as nonterminating queues. However, from the care provider's point of view, ED care is not a never-ending process, but rather occurs in discrete work shifts and may require passing unfinished work to the next care provider at the end of the shift. We use data from a large, academic medical center ED to show that the patients' rate of service completion varies over the course of the physician shift. Further, patients that have experienced a physician handoff have a higher rate of service completion than non-handed off patients. As a result, a patient's expected treatment time is impacted by when in the physician's shift treatment begins. We also show that patients that have been handed off are more likely to revisit the ED within three days, suggesting that patient handoffs lower clinical quality. Lastly, we use simulation to show that shift length and new-patient cutoff rules can be used to reduce handoffs, but at the expense of system throughput.

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.