Return visits to the emergency department

doi:10.1016/0736-4679(87)90138-7

The Journal of Emergency Medicine

Volume 5, Issue 5, September–October 1987, Pages 359-362

https://doi.org/10.1016/0736-4679(87)90138-7 Get rights and content

Abstract

A persistent problem for emergency physicians is the patient who returns unscheduled to the emergency department with a problem that either has not improved or has worsened. The purpose of this study was to evaluate the frequency of revisits and the nature of the problems. All patients returning within 72 hours of their initial visit were entered into the study. The charts were evaluated for classification of problem, unavoidable v avoidable returns, and errors in medical care or patient education. Of the 64,336 patients seen during the study, 255 returned within 72 hours. Eighty-three (32.5%) of the returns were found to be avoidable with better patient education or medical care on the initial visit. The revisit population is a high-risk group of patients who should be approached carefully by emergency physicians.

References (2)

J.T. Rogers
Risk Management in the Emergency Department
A.C.E.P. Illinois
Quality Assessment in the Emergency Department
(1984)

Cited by (113)

Patterns in emergency department unscheduled return visits during the COVID-19 pandemic
2022, American Journal of Emergency Medicine
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.
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.
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.
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.
Discharge in Pandemic: Suspected Covid-19 patients returning to the Emergency Department within 72 hours for admission
2021, American Journal of Emergency Medicine
Citation Excerpt :
Additionally, timeframes longer than 72 h may also serve as appropriate cutoffs for reviewing ED return admissions [42]. However, the decision to rely on 72-h return was made based on its established use as a healthcare quality metric for patient recidivism [43-46]. Additional limitations pertain to the extent to which the cohort prepared here adequately captures suspected Covid-19 cases.
Coronavirus disease 2019 (Covid-19) has led to unprecedented healthcare demand. This study seeks to characterize Emergency Department (ED) discharges suspected of Covid-19 that are admitted within 72 h.
We abstracted all adult discharges with suspected Covid-19 from five New York City EDs between March 2nd and April 15th. Those admitted within 72 h were then compared against those who were not using descriptive and regression analysis of background and clinical characteristics.
Discharged ED patients returning within 72 h were more often admitted if suspected of Covid-19 (32.9% vs 12.1%, p < .0001). Of 7433 suspected Covid-19 discharges, the 139 (1.9%) admitted within 72 h were older (55.4 vs. 45.6 years, OR 1.03) and more often male (1.32) or with a history of obstructive lung disease (2.77) or diabetes (1.58) than those who were not admitted (p < .05). Additional associations included non-English preference, cancer, heart failure, hypertension, renal disease, ambulance arrival, higher triage acuity, longer ED stay or time from symptom onset, fever, tachycardia, dyspnea, gastrointestinal symptoms, x-ray abnormalities, and decreased platelets and lymphocytes (p < .05 for all). On 72-h return, 91 (65.5%) subjects required oxygen, and 7 (5.0%) required mechanical ventilation in the ED. Twenty-two (15.8%) of the study group have since died.
Several factors emerge as associated with 72-h ED return admission in subjects suspected of Covid-19. These should be considered when assessing discharge risk in clinical practice.
Improving Quality of Care Through a Mandatory Provincial Audit Program: Ontario's Emergency Department Return Visit Quality Program
2021, Annals of Emergency Medicine
The Emergency Department Return Visit Quality Program was launched in Ontario, Canada, to promote a culture of quality. It mandates the province’s largest-volume emergency departments (EDs) to audit charts of patients who had a return visit leading to hospital admission, including some of their 72-hour all-cause return visits with admission and all of their 7-day ones with sentinel diagnoses (ie, acute myocardial infarction, subarachnoid hemorrhage, and pediatric sepsis), and submit their findings to a governmental agency. This provides an opportunity to identify possible adverse events and quality issues, which hospitals can then address through quality improvement initiatives. A group of emergency physicians with quality improvement expertise analyzed the submitted audits and accompanying narrative templates, using a general inductive approach to develop a novel classification of recurrent quality themes. Since the Return Visit Quality Program launched in 2016, 125,698 return visits with admission have been identified, representing 0.93% of the 86 participating EDs’ 13,559,664 visits. Overall, participating hospitals have conducted 12,852 detailed chart audits, uncovering 3,010 (23.4%) adverse events/quality issues and undertaking hundreds of quality improvement provincewide projects as a result. The inductive analysis revealed 11 recurrent themes, classified into 3 groupings: patient characteristics (ie, patient risk profile and elder care), ED team actions or processes (ie, physician cognitive lapses, documentation, handover/communication between providers, radiology, vital signs, and high-risk medications or medication interactions), and health care system issues (ie, discharge planning/community follow-up, left against medical advice/left without being seen, and imaging/testing availability). The Return Visit Quality Program is the largest mandatory audit program for EDs and provides a novel approach to identify local adverse events/quality issues to target for improved patient safety and quality of care. It provides a blueprint for health system leaders to enable clinicians to develop an approach to organizational quality, as well as for teams to construct an audit system that yields defined issues amenable to improvement.
A Nested Mixed Effects Multicenter Model Examining the Risk Factors for Pediatric Trauma Return Visits Within 72 h
2021, Journal of Surgical Research
Return visits within 72 h are an important metric in evaluating the performance of emergency rooms. This has not been well studied in the pediatric trauma population. We sought to determine novel risk factors for return visits to the emergency department (ED) after trauma that may assist in identifying patients most at risk of revisit.
We used the Cerner Health Facts Database to retrieve data from 34 EDs across the United States that care for pediatric trauma patients aged <15 y. The data consist of 610,845 patients and 816,571 ED encounters. We retrieved variables encompassing demographics, payor, current and past health care resource utilization, trauma diagnoses, other diagnoses/comorbidities, medications, and surgical procedures. We built a nested mixed effects logistic regression model to provide statistical inference on the return visits.
Traumas resulting from burns and corrosion, injuries to the shoulder and arms, injuries to the hip and legs, and trauma to the head and neck are all associated with increased odds of returning to the ED. Patients suffering from poisoning relating to drugs and other biological substances and patients with trauma to multiple body regions have reduced odds of returning to the ED. Longer ED length of stay and prior health care utilization (ED or inpatient) are associated with increased odds of a return visit. The sex of the patient and payor had a statistically significant effect on the risk of a return visit to the ED within 72 h of discharge.
Certain traumas expose patients to an increased risk for return visits to the ED and, as a result, provide opportunity for improved quality of care. Targeted interventions that include education, observation holds, or a decision to hospitalize instead of discharge home may help improve patient outcomes and decrease the rate of ED returns.
III (Prognostic and Epidemiology).
Data mining techniques utilizing latent class models to evaluate emergency department revisits
2020, Journal of Biomedical Informatics
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.
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.
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.
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(.
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.
Application of the Informatics Stack framework to describe a population-level emergency department return visit continuous quality improvement program
2020, International Journal of Medical Informatics
Citation Excerpt :
Triggers are clinical events that may indicate the possibility of an adverse event having occurred [16], and can be used to investigate initial ED visits for potential QI opportunities [17]. Globally, previous ED return visit research has often focused on one ED [17–24]. More recently, research has characterized larger populations including a study across several hospitals [25], across 6 U.S. states [26], and utilizing a large HIE across 31 sites [27].
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.
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.
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.
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.

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^†: This work was done during Dr Lerman's senior year of Medical School at the University of Michigan.

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Original contributionReturn visits to the emergency department

Abstract

Risk Management in the Emergency Department

Quality Assessment in the Emergency Department

Original contribution
Return visits to the emergency department