A conceptual framework for improved analyses of 72-hour return cases

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.

Characteristics of patients who return unplanned to the ED, and factors that contribute to their decision to return: Integrated results from an explanatory sequential mixed methods inquiry

AIM

To identify common characteristics of patients who return to the ED unplanned and factors that may contribute to their decision to return.

BACKGROUND

Return visits to the Emergency Department (ED) have been associated with adverse events and deficits in initial care provided. There is increasing evidence to suggest that many return visits may be preventable.

METHODS

The results of primary quantitative measures (QUAN) followed by qualitative measures (qual) were integrated to build on and explain the quantitative data found in the initial phase of the research.

RESULTS

Integration of results produced three new findings. 1) Most return visits occurred beyond 48 hrs because patients intentionally delayed going back to the ED despite their persisting symptoms; 2) Clinical urgency and deterioration were rarely evident in patients who made return visits in patients and 3) Ineffective communication between the clinician and the patient at discharge may have contributed to patients making the decision to return to the ED.

CONCLUSION

The decision to return unplanned to the ED is not an immediate response for most patients, and several potentially avoidable factors may influence their decision-making process. Future research should focus on strategies which contribute to the avoidance of unplanned return visits.

Strategies to Measure and Improve Emergency Department Performance: A Review

Emergency Departments (EDs) globally face escalating challenges such as overcrowding, resource limitations, and increased patient demand. This study aims to identify and analyze strategies to enhance the structural performance of EDs, with a focus on reducing overcrowding, optimizing resource allocation, and improving patient outcomes. Through a comprehensive review of the literature and observational studies, the research highlights the effectiveness of various approaches, including triage optimization, dynamic staffing, technological integration, and strategic resource management. Key findings indicate that tailored strategies, such as implementing advanced triage protocols and leveraging telemedicine, can significantly reduce wait times and enhance patient throughput. Furthermore, evidence suggests that dynamic staffing models and the integration of cutting-edge diagnostic tools contribute to operational efficiency and improved quality of care. These strategies, when combined, offer a multifaceted solution to the complex challenges faced by EDs, promising better patient care and satisfaction. The study underscores the need for a comprehensive approach, incorporating both organizational and technological innovations, to address the evolving needs of emergency healthcare.

Emergency department performance assessment using administrative data: A managerial framework

Administrative data play an important role in performance monitoring of healthcare providers. Nonetheless, little attention has been given so far to the emergency department (ED) evaluation. In addition, most of existing research focuses on a single core ED function, such as treatment or triage, thus providing a limited picture of performance. The goal of this study is to harness the value of routinely produced records proposing a framework for multidimensional performance evaluation of EDs able to support internal decision stakeholders in managing operations. Starting with the overview of administrative data, and the definition of the desired framework's characteristics from the perspective of decision stakeholders, a review of the academic literature on ED performance measures and indicators is conducted. A performance measurement framework is designed using 224 ED performance metrics (measures and indicators) satisfying established selection criteria. Real-world feedback on the framework is obtained through expert interviews. Metrics in the proposed ED performance measurement framework are arranged along three dimensions: performance (quality of care, time-efficiency, throughput), analysis unit (physician, disease etc.), and time-period (quarter, year, etc.). The framework has been judged as "clear and intuitive", "useful for planning", able to "reveal inefficiencies in care process" and "transform existing data into decision support information" by the key ED decision stakeholders of a teaching hospital. Administrative data can be a new cornerstone for health care operation management. A framework of ED-specific indicators based on administrative data enables multi-dimensional performance assessment in a timely and cost-effective manner, an essential requirement for nowadays resource-constrained hospitals. Moreover, such a framework can support different stakeholders' decision making as it allows the creation of a customized metrics sets for performance analysis with the desired granularity.

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

Introduction

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

Methods

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

Results

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

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

Conclusion

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

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

A Framework for Quality Assurance of Pediatric Revisits to the Emergency Department

BACKGROUND

Emergency department return visits significantly impact medical costs and patient flow. A comprehensive approach to understanding these patients is required to identify deficits in care, system level inefficiencies, and improve diagnosis specific management protocols. We aimed to identify factors needed to successfully analyze return visits to explore root causes leading to unplanned returns and inform system-level improvements.

METHODS

A multidisciplinary committee collaborated to develop a quality review process for return visits within 72 hours to our pediatric emergency department that were then subsequently admitted to the hospital. The committee developed methodology and a web-based tool for chart review and analysis.

RESULTS

Of 197,076 ED visits (159,164 discharged at initial visit), 5390 (3.4%) patients were discharged and represented to the ED within 72 hours and 1658 (1.0%) of those resulted in admission. Using defined criteria, approximately one third (n = 564) of revisits with admission were identified for chart review. Reason for revisit included natural progression of disease (67.6%), new condition or problem (11.2%), diagnostic error (6.9%), and scheduled or planned readmissions (3.5%). All diagnostic errors had not been previously identified by ED leadership. Of the reviewed cases, most were not preventable (84.0%); however, a number of system-level actions resulted from discussion of the potentially preventable revisits.

CONCLUSIONS

Seventy-two-hour ED revisits were efficiently and systematically categorized with determination of root causes and preventability. This process resulted in shared provider-level feedback, identifying trends in revisits, and implementation of system-level actions, therefore, encouraging other institutions to adopt a similar process.

[Return rate to the Primary Care Emergency Service for elderly patients over 65 years old and their assistance requirements]

OBJECTIVE

To determine the unexpected return rate to the Primary Care Emergency Service of elderly patients over 65 years old within the following 72h of a previous visit, as well as to determine the clinical and assistance requirements of these patients.

PROCEDURE

Retrospective and observational epidemiologic study.

LOCATION

Cotolino's Primary Care Emergency Service in Cantabria, Spain.

PARTICIPANTS

1940 elderly patients over 65 years old were included. These patients returned to the Primary Care Emergency Service in 2016.

MAIN DATA FOR THE STUDY

The dependent variable was the return rate to the Primary Care Emergency Service. The independent variables were socio-demographic characteristics, health details and medical assistance information. All data was collected from the Primary Care Emergency Service Management Office database. All variables were analysed applying Pearson's chi-squared test and Fisher's exact test, with statistical significance P≤.05.

RESULTS

The rate of unexpected return was 2.3%. The average age was 77.4 years old (standard deviation (SD): 8.4), of which the 37.6% were male. The most frequent range of age was from 75 to 84 years old, with males being the predominant group. A history of polymedication was detected in 54.4% of the cases, as well as a medium cardiovascular risk within this group. Nursing professionals attended the 42.2% of these return cases (P<.001). Patients with dysnea (P=.015), scheduled care or scheduled injection returned with a higher frequency (P<.001). It was as well noticed a higher frequency of return for subsequent attention during the months of December and January (P<.001).

CONCLUSIONS

The rate of unexpected return is low. The main causes why elderly patients returned to the service requiring urgent assistance were issues categorised as unspecific general health indicators and/or respiratory system illnesses. Our proposal is to develop specific protocols combining the work from both Geriatrics and Gerontology professionals, in order to improve the support to this group of population at every Primary Care Emergency Service.

Qualitative evaluation of a mandatory provincial programme auditing emergency department return visits

OBJECTIVE

The objective of this qualitative study was to evaluate the perceived impact and value of the Return Visit Quality Programme (RVQP), a mandatory province-wide emergency department audit programme.

DESIGN

We employed an interpretive descriptive qualitative approach with maximum variation sampling to ensure diverse representation across several geographical and institutional factors. RVQP programme leads were invited to participate in semistructured interviews and snowball sampling was used to reach non-lead physicians to capture the perspectives of those working within the programme.

SETTING

In Ontario's RVQP, participating emergency departments must audit their return visits resulting in admission to identify issues that can be addressed through quality improvement initiatives.

PARTICIPANTS

Between June and August 2018, we interviewed 32 participants (local programme leads and non-lead physicians) from 23 out of the 86 participating centres.

RESULTS

Participants' perceived impact and value of the programme was associated with the existence (or absence) and nature of the local quality improvement culture, the implementation approach of the programme within their emergency departments, and key aspects of the programme pertaining to medicolegal concerns and resource availability.

CONCLUSIONS

This study of an innovative, large-scale programme aimed at promoting continuous quality improvement in emergency departments showed that while its perceived impact has been meaningful, there are key structural and operational elements that support and hinder this aim. Healthcare leaders should consider these findings when looking to implement large-scale audit or quality improvement programmes.

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.

Improving Quality of Care Through a Mandatory Provincial Audit Program: Ontario's Emergency Department Return Visit Quality Program

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.

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.

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.

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.

Status of Emergency Department Seventy-Two Hour Return Visits Among Homeless Patients

Background

We aim to externally validate the status of emergency department (ED) appropriate utilization and 72-h ED returns among homeless patients.

Methods

This is a retrospective single-center observational study. Patients were divided into two groups (homeless versus non-homeless). Patients' general characteristics, clinical variables, ED appropriate utilization, and ED return disposition deviations were compared and analyzed separately.

Results

Study enrolled a total of 63,990 ED visits. Homeless patients comprised 9.3% (5,926) of visits. Higher ED 72-h returns occurred among homeless patients in comparison to the non-homeless patients (17% versus 5%, P < 0.001). Rate of significant ED disposition deviations (e.g., admission, triage to operation room, or death) on return visits were lower in homeless patients when compared to non-homeless patient populations (15% versus 23%, P < 0.001).

Conclusions

Though ED return rate was higher among homeless patients, return visit case management seems appropriate, indicating that 72-h ED returns might not be an optimal healthcare quality measurement for homeless patients.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Incidence of emergency department presentations for traumatic brain injury in Indigenous and non-Indigenous residents aged 15-64 over the 9-year period 2007-2015 in North Queensland, Australia

Background

Traumatic brain injury (TBI) is a leading cause of disability worldwide. Previous studies have shown that males have a higher incidence than females, and Indigenous populations have a higher rate than non-Indigenous. To date, no study has compared the incidence rate of TBI between Indigenous and non-Indigenous Australians for any cause. Here we add to this rather sparse literature.

Methods

Retrospective analysis of data from North Queensland Emergency Departments between 2007 and 2015 using Australian Bureau of Statistics population estimates for North Queensland residents aged 15–64 years as denominator data. Outcome measures include incidence rate ratios (IRR) for TBI presentations by Indigenous status, age, sex, year of presentation, remoteness, and socio-economic indicator.

Results

Overall incidence of TBI presentations per 100,000 population was 97.8. Indigenous people had an incidence of 166.4 compared to an incidence in the non-Indigenous population of 86.3, providing an IRR of 1.93 (95% CI 1.77–2.10; p < 0.001). Males were 2.29 (95% CI 2.12–2.48; p < 0.001) times more likely to present than females. Incidence increased with year of presentation only in the Indigenous male population.

Conclusions

The greater burden of ED presentations for TBI in the Indigenous compared with the non-Indigenous population is of concern. Importantly, the need to provide quality services and support to people living with TBI in remote and very remote areas, and the major role of the new National Disability Insurance Scheme is discussed.

Return Visit Admissions May Not Indicate Quality of Emergency Department Care for Children

OBJECTIVE

The objective was to test the hypothesis that in-hospital outcomes are worse among children admitted during a return ED visit than among those admitted during an index ED visit.

METHODS

This was a retrospective analysis of ED visits by children age 0 to 17 to hospitals in Florida and New York in 2013. Children hospitalized during an ED return visit within 7 days were classified as "ED return admissions" (discharged at ED index visit and admitted at return visit) or "readmissions" (admission at both ED index and return visits). In-hospital outcomes for ED return admissions and readmissions were compared to "index admissions without return admission" (admitted at ED index visit without 7-day return visit admission).

RESULTS

Among 1,886,053 index ED visits to 321 hospitals, 75,437 were index admissions without return admission, 7,561 were ED return admissions, and 1,333 were readmissions. ED return admissions had lower intensive care unit admission rates (11.0% vs. 13.6%; adjusted odds ratio = 0.78; 95% confidence interval [CI] = 0.71 to 0.85), longer length of stay (3.51 days vs. 3.38 days; difference = 0.13 days; incidence rate ratio = 1.04; 95% CI = 1.02 to 1.07), but no difference in mean hospital costs (($7,138 vs. $7,331; difference = -$193; 95% CI = -$479 to $93) compared to index admissions without return admission.

CONCLUSIONS

Compared with children who experienced index admissions without return admission, children who are initially discharged from the ED who then have a return visit admission had lower severity and similar cost, suggesting that ED return visit admissions do not involve worse outcomes than do index admissions.

Identifying discordance between senior physicians and trainees on the root cause of ED revisits

OBJECTIVE

Analysis of 72-hour ED revisits is a common emergency medicine quality assurance (QA) practice. Our aim was to compare the perceived root cause for 72-hour ED revisits between senior physicians (attendings) and trainees. We proposed that discordance in perception of why the revisit occurred would guide improvements in 72-hour revisits QA and elucidate innovative educational opportunities.

METHODS

Questionnaire-based observational study conducted in an urban academic paediatric ED. Treating attendings and trainees independently completed questionnaires on revisit cases. The primary outcome was the revisit's perceived root cause, dichotomised into 'potential medical deficiency' or 'not potential medical deficiency'. Discordance between provider pairs was measured, stratified by revisit disposition.

RESULTS

During the study period, 31 630 patients were treated in the ED, 559 returned within 72 hours and 218 met inclusion criteria for paired analysis. The proportion of cases assigned 'potential medical deficiency' by the attending and trainee was 13% and 9%, respectively. Discordance in the dichotomised root cause between attendings and trainees was 17% (38/218, 95% CI 12% to 22%). Revisit cases requiring admission revealed attending-trainee discordance of 25% (23/92, 95% CI 16% to 34%).

CONCLUSIONS

Attendings and trainees frequently disagree on whether a potential medical deficiency was the root cause for an ED revisit, with more disagreement noted for cases requiring admission. These findings support the premise that there may be opportunities to improve 72-hour revisits QA systems through trainee integration. Finally, reuniting attending-trainee pairs around revisit cases may be a novel educational opportunity.

Characteristics of patients who made a return visit within 72 hours to the emergency department of a Singapore tertiary hospital

INTRODUCTION

72-hour emergency department (ED) reattendance is a widely-used quality indicator for quality of care and patient safety. It is generally assumed that patients who return within 72 hours of ED discharge (72-hour re-attendees) received inadequate treatment or evaluation. The current literature also suggests considerable variation in probable causes of 72-hour ED reattendances internationally. This study aimed to understand the characteristics of these patients at the ED of a Singapore tertiary hospital.

METHODS

We conducted a retrospective cohort study on all ED visits between 1 January 2013 and 31 December 2013. 72-hour re-attendees were compared against non-re-attendees based on patient demographics, mode of arrival, patient acuity category status (i.e. P1/P2/P3/P4), seniority ranking of doctor-in-charge and medical diagnoses. Multivariate analysis using the generalised linear model was conducted on variables associated with 72-hour ED re-attendance.

RESULTS

Among 104,751 unique patients, 3,065 (2.93%) were in the 72-hour re-attendees group. Multivariate analysis showed that the following risk factors were associated with higher risk of returning within 72 hours: male gender, older age, arrival by ambulance, triaged as P2, diagnoses of heart problems, abdominal pain or viral infection (all p < 0.001), and Chinese ethnicity (p = 0.006). There was no significant difference in the seniority ranking of the doctor-in-charge between both groups (p = 0.419).

CONCLUSION

Several patient and event factors were associated with higher risk of being a 72-hour re-attendee. This study forms the basis for hypothesis generation and further studies to explore reasons behind reattendances so that interventions can be developed to target high-risk groups.

Geography, Not Health System Affiliations, Determines Patients' Revisits to the Emergency Department

OBJECTIVES

To determine how frequently patients revisit the emergency department after an initial encounter, and to describe revisit capture rates for the same hospital, health system, and geographic region.

DATA SOURCES/STUDY SETTING

Florida state data from January 1, 2010, to June 30, 2011, from the Healthcare Cost and Utilization Project.

STUDY DESIGN

This is a retrospective cohort study of emergency department return visits among Florida adults over an 18-month period. We evaluated pairs of index and 30-day return emergency department visits and compared capture rates for hospital, health system, and geographic units.

DATA COLLECTION/EXTRACTION METHODS

Data were obtained from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project and the American Hospital Association Annual Survey Database.

PRINCIPAL FINDINGS

Among 9,416,212 emergency department visits, 22.6 percent (2,124,441) were associated with a 30-day return. Seventy percent (1,477,772) of 30-day returns occurred to the same hospital. The 30-day return capture rates were highest within the same geographic area: county-level capture at 92 percent (IQR=86-96 percent) versus health system capture at 75 percent (IQR = 68-81 percent).

CONCLUSIONS

Acute care utilization patterns are often independent of health system boundaries. Current population-based health care models that attribute patients to a single provider or health system may be strengthened by considering geographic patterns of acute care utilization.

The asthma prediction rule to decrease hospitalizations for children with asthma

PURPOSE OF REVIEW

The aim of the present review was to discuss the challenges around clinical decision-making for hospitalization of children with acute asthma exacerbations and the development, internal validation, and future potential of the asthma prediction rule (APR) to provide meaningful clinical decision-support that might decrease unnecessary hospitalizations.

RECENT FINDINGS

The APR was developed and internally validated using predictor variables available before treatment in the emergency department, and performed well to predict 'need-for-hospitalization.' Oxygen saturation on room air and expiratory phase prolongation were most strongly associated with need-for-hospitalization.

SUMMARY

Research on prediction rules in pediatric asthma is rare. We developed and internally validated the APR using clinically intuitive predictor variables that are available at the bedside. Before incorporation into electronic decision-support the APR must undergo external validation and an impact analysis to determine if use of this tool will change clinician behavior and improve patient outcomes.

Increased Identification of Emergency Department 72-hour Returns Using Multihospital Health Information Exchange

OBJECTIVES

Emergency departments (EDs) commonly analyze cases of patients returning within 72 hours of initial ED discharge as potential opportunities for quality improvement. In this study, we tested the use of a health information exchange (HIE) to improve identification of 72-hour return visits compared to individual hospitals' site-specific data.

METHODS

We collected deidentified patient data over a 5-year study period from Healthix, an HIE in the New York metropolitan area. We measured site-specific 72-hour ED returns and compared these data to those obtained from a regional 31-site HIE (Healthix) and to those from a smaller, antecedent 11-site HIE. Although only ED visits were counted as index visits, either ED or inpatient revisits within 72 hours of the index visit were considered as early returns.

RESULTS

A total of 12,669,657 patient encounters were analyzed across the 31 HIE EDs, including 6,352,829 encounters from the antecedent 11-site HIE. Site-specific 72-hour return visit rates ranged from 1.1% to 15.2% (median = 5.8%) among the individual 31 sites. When the larger HIE was used to identify return visits to any site, individual EDs had a 72-hour return frequency of 1.8% to 15.5% (median = 6.8%). HIE increased the identification ability of 72-hour ED return analyses by a mean of 11.16% (95% confidence interval = 11.10% to 11.22%) compared with site-specific (no HIE) analyses.

CONCLUSION

This analysis demonstrates incremental improvements in our ability to identify early ED returns using increasing levels of HIE data aggregation. Although intuitive, this has not been previously described using HIE. ED quality measurement and patient safety efforts may be aided by using HIE in 72-hour return analyses.