Age before acuity: the drivers of demand for emergency department services in the Greater Sydney Area

Modelled economic evaluation of a virtual emergency department in Victoria

OBJECTIVE

Virtual ED (VED) can potentially alleviate ED overcrowding which has been a public health challenge. The aim of the present study was to conduct a return-on-investment analysis of a VED programme developed in response to changing healthcare needs in Australia.

METHODS

An economic model was developed based on initial patient outcome data to assess the healthcare costs, potential costs saved and return on investment (ROI) from the VED. The VED programme operating as part of Alfred Health Emergency Services. The participants were the first 188 patients accessing the Alfred Health VED. VED is the delivery of emergency assessment and management of specific patients virtually via audio-visual teleconferencing. ROI ratios that compare cost savings with intervention costs.

RESULTS

The mean total operational cost of VED for 79 days for 188 patients was A$344 117 (95% uncertainty interval [UI] $296 800-$392 088). The VED led to a potential A$286 779 (95% UI $241 688-$330 568) healthcare cost saving from reductions in emergency visits and A$97 569 (95% UI $74 233-$123 117) cost saving in ambulance services. The ROI ratio was estimated at 1.12 (95% UI 0.96-1.32).

CONCLUSIONS

The VED was cost neutral in a conservatively modelled scenario but promising if any hospital admission could be saved. Ongoing research examining a larger cohort with community follow up is required to confirm this promising result.

A Machine Learning Approach for Monitoring and Classifying Healthcare Data-A Case of Emergency Department of KSA Hospitals

The Emergency Departments (EDs), in hospitals located in a few important areas in Saudi Arabia, experience a heavy inflow of patients due to viral illnesses, pandemics, and even on a few special occasions events such as Hajj or Umrah, when pilgrims travel from one region to another with severe disease conditions. Apart from the EDs, it is critical to monitor the movements of patients from EDs to other wards inside the hospital or in the region. This is to track the spread of viral illnesses that require more attention. In this scenario, Machine Learning (ML) algorithms can be used to classify the data into many classes and track the target audience. The current research article presents a Machine Learning-based Medical Data Monitoring and Classification Model for the EDs of the KSA hospitals and is named MLMDMC-ED technique. The most important aim of the proposed MLMDMC-ED technique is to monitor and track the patient's visits to the EDs, the treatment given to them based on the Canadian Emergency Department Triage and Acuity Scale (CTAS), and their Length Of Stay (LOS) in the hospital, based on their treatment requirements. A patient's clinical history is crucial in terms of making decisions during health emergencies or pandemics. So, the data should be processed so that it can be classified and visualized in different formats using the ML technique. The current research work aims at extracting the textual features from the patients' data using the metaheuristic Non-Defeatable Genetic Algorithm II (NSGA II). The data, collected from the hospitals, are classified using the Graph Convolutional Network (GCN) model. Grey Wolf Optimizer (GWO) is exploited for fine-tuning the parameters to optimize the performance of the GCN model. The proposed MLMDMC-ED technique was experimentally validated on the healthcare data and the outcomes indicated the improvements of the MLMDMC-ED technique over other models with a maximum accuracy of 91.87%.

Understanding patient preferences for emergency care for lower triage acuity presentations during GP hours: a qualitative study in Australia

BACKGROUND

Low acuity presentations to Australian emergency departments drive long wait times, higher costs and may be better treated in primary care settings. This study sought to understand factors leading these patients to present to emergency departments.

METHODS

Semi-structured interviews were carried out with patients at two tertiary emergency departments in Sydney during general practitioner opening hours. Nvivo was used to code the interviews and a thematic analysis was carried out to capture the main themes from the interviews.

RESULTS

Forty-four interviews were included in the analysis across the two sites. They represented a diverse population in terms of ethnicity, education and socioeconomic background. Patient preferences for emergency care were organised into four main themes: (i) patients were referred (either by another health service, work, friend, or family), (ii) emergency department factors (convenience of investigations and severity of symptoms requiring emergency care), (iii) GP factors (does not have a GP, cannot find an appointment with a GP or has previously had a negative experience with a GP) and (iv) personal factors such as their connection to the hospital.

CONCLUSION

Multiple factors led patients to seek ED care for low acuity presentations during GP hours. Some of these factors could be addressed to meet patient needs in the community, however this is currently not the case. Addressing these factors to improve access to GP clinics and the availability of services outside the hospital setting could reduce ED presentations and likely improve patient experience.

Characteristics of Patients Who Visited Emergency Department: A Nationwide Population-Based Study in South Korea (2016-2018)

The utilization of the emergency department (ED) has been continuously increasing and has become a burden for ED resources. The aim of this study was to describe the characteristics, outcomes, common diagnoses, and disease classifications of patients who were referred to the ED. This nationwide epidemiologic study examined the data from adult patients (>18 years) who visited EDs from 1 January 2016 to 31 December 2018. Most EDs in Korea provide data from ED patients to the National Emergency Medical Center (NEMC). The disposition of ED patients was classified as discharge, admission, death, and re-transfer. From 2016 to 2018, the proportion of referred patients out of the total ED visits increased from 7.3% to 7.8%. The referred patients were older (61.1 vs. 50.5 years), had worse vital signs, longer ED lengths of stay (409.1 vs. 153.3 min), and higher admission (62.3 vs. 16.9%) and re-transfer rates (4.4 vs. 1.9%) than the direct-visit patients. Among the referred patients in the 3 years, 62.3% were hospitalized, and the most common disease classification was “disease of the digestive system” (19.8%). The most common diagnosis was pneumonia (6.0%), followed by urinary tract infection, gastrointestinal bleeding, and hepatobiliary infection. The number of patients referred to EDs is increasing, and more than 60% of referred patients are hospitalized. Detailed characteristics of these patients will be helpful for improving ED management and the distribution of medical resources.

A Novel Deep Learning-Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study

Background

Emergency department (ED) crowding has resulted in delayed patient treatment and has become a universal health care problem. Although a triage system, such as the 5-level emergency severity index, somewhat improves the process of ED treatment, it still heavily relies on the nurse’s subjective judgment and triages too many patients to emergency severity index level 3 in current practice. Hence, a system that can help clinicians accurately triage a patient’s condition is imperative.

Objective

This study aims to develop a deep learning–based triage system using patients’ ED electronic medical records to predict clinical outcomes after ED treatments.

Methods

We conducted a retrospective study using data from an open data set from the National Hospital Ambulatory Medical Care Survey from 2012 to 2016 and data from a local data set from the National Taiwan University Hospital from 2009 to 2015. In this study, we transformed structured data into text form and used convolutional neural networks combined with recurrent neural networks and attention mechanisms to accomplish the classification task. We evaluated our performance using area under the receiver operating characteristic curve (AUROC).

Results

A total of 118,602 patients from the National Hospital Ambulatory Medical Care Survey were included in this study for predicting hospitalization, and the accuracy and AUROC were 0.83 and 0.87, respectively. On the other hand, an external experiment was to use our own data set from the National Taiwan University Hospital that included 745,441 patients, where the accuracy and AUROC were similar, that is, 0.83 and 0.88, respectively. Moreover, to effectively evaluate the prediction quality of our proposed system, we also applied the model to other clinical outcomes, including mortality and admission to the intensive care unit, and the results showed that our proposed method was approximately 3% to 5% higher in accuracy than other conventional methods.

Conclusions

Our proposed method achieved better performance than the traditional method, and its implementation is relatively easy, it includes commonly used variables, and it is better suited for real-world clinical settings. It is our future work to validate our novel deep learning–based triage algorithm with prospective clinical trials, and we hope to use it to guide resource allocation in a busy ED once the validation succeeds.

Likelihood of admission to hospital from the emergency department is not universally associated with hospital bed occupancy at the time of admission

Background

The decision to admit into the hospital from the emergency department (ED) is considered to be important and challenging. The aim was to assess whether previously published results suggesting an association between hospital bed occupancy and likelihood of hospital admission from the ED can be reproduced in a different study population.

Methods

A retrospective cohort study of attendances at two Swedish EDs in 2015 was performed. Admission to hospital was assessed in relation to hospital bed occupancy together with other clinically relevant variables. Hospital bed occupancy was categorized and univariate and multivariate logistic regression were performed.

Results

In total 89,503 patient attendances were included in the final analysis. Of those, 29.1% resulted in admission within 24 h. The mean hospital bed occupancy by the hour of the two hospitals was 87.1% (SD 7.6). In both the univariate and multivariate analysis, odds ratio for admission within 24 h from the ED did not decrease significantly with an increasing hospital bed occupancy.

Conclusions

A negative association between admission to hospital and occupancy level, as reported elsewhere, was not replicated. This suggests that the previously shown association might not be universal but may vary across sites due to setting specific circumstances.

The "two-step four-level+ " pediatric triage method in a medical center in Southern China

PURPOSE

Because the quality of medical resources is extremely uneven across China, it is nearly impossible to implement a unified emergency triage program. The aim of the study is to examine triage using the "two-step four-level⁺ " triage model in a hospital in Southern China, with an emphasis on hand, foot, and mouth disease.

DESIGN AND METHODS

This was a retrospective study of all patients seen in the pediatric emergency room (ER) between January 1, 2012 and December 31, 2018, at the Guangzhou Women and Children's Medical Center. The "two-step and four-level⁺ " was manually implemented in 2012, and an electronic triage system was developed and applied since 2015. Emergency quality control indicators were analyzed.

RESULTS

There were 645,473 patients triaged at the pediatric ER between January 1, 2015 and December 31, 2018. After the first step, 17,444 patients were classified as unstable, including 6546 (1.01%) Level I patients, 10,898 (1.69%) Level II patients, 210,368 (32.5%) Level III patients, and 417,661 (64.8%) Level IV patients. After triage implementation, the stay time of the patient in the pediatric ER decreased each year (all p < .05) and shortened to 20.3 ± 2.2 h in 2018. Compared with 2012-2014, the mortality of 2015-2018 decreased by 21.1%, the rate of unexpected resuscitation was 0%, and the complaints of overcrowding decreased (all p < .05).

PRACTICE IMPLICATIONS

This "two-step four-level⁺ " triage method can improve the medical care quality of pediatric ER in China.

Association between potential primary care emergency service and general practitioner care utilisation in New South Wales

OBJECTIVE

To examine patterns of potential primary care (PPC) ED presentations and any association between PPC ED presentations and frequency of general practitioner (GP) care utilisation in New South Wales, Australia.

METHODS

Retrospective cross-sectional study of 6 221 762 New South Wales patients who had at least one service in public hospitals, EDs or Medical Benefit Schedule claimable for GP service between 2013/2014 and 2014/2015 is conducted to examine association between PPC ED presentations and GP care utilisation using logistic regression adjusting for comorbidity index and a number of other covariates. Data over 2010/2011 to 2014/2015 are included for analyses of trends and patterns in PPC ED and GP care utilisation.

RESULTS

Forty-one percent of the ED presentations were PPC ED presentations over the 5 years 2010/2011 to 2014/2015. Population rates of PPC ED presentations and GP care both increased over the period, with higher PPC ED presentation rates in regional areas, and higher GP care rates in major cities. GP care utilisation was associated with reduced odds for PPC ED presentations, with the adjusted odds ratios ranging from 0.28 for patients with one GP care service to 0.48 for patients with five or more GP care services compared with patients with none. Increased comorbidity index was also associated with increased risk of PPC ED presentations.

CONCLUSION

GP care utilisation was associated with reduced risk for any PPC ED presentations after adjusting for comorbidity index and the other factors.

Association entre mortalité et attente aux urgences chez les adultes à hospitaliser pour étiologies médicales

Introduction : Notre objectif principal est de comparer, dans un centre hospitalier universitaire (CHU) français et chez les patients hospitalisés pour étiologies médicales à partir de la structure des urgences (SU), le taux de mortalité intrahospitalière entre ceux qui n’attendent pas faute de place en service et ceux en attente (boarding).

Méthode : Il s’agit d’une étude quasi expérimentale, monocentrique, observationnelle, rétrospective, par recueil d’informations à partir des dossiers patients informatisés. Nous avons appliqué un score de propension pour ajuster les critères de jugement aux variables mesurées dans les deux groupes, c’est-à-dire les données : 1) démographiques (âge et sexe) ; 2) médicales (niveau de triage) ; 3) biologiques (numération leucocytaire, hémoglobinémie, natrémie, kaliémie, taux sérique de CRP, créatininémie) ; 4) d’imageries (réalisation ou non de radiographie, d’échographie, d’imagerie par résonance magnétique, de tomodensitométrie).

Résultats : En 2017, la SU du CHU a admis 60 062 patients adultes. Sur les 15 496 patients hospitalisés après admission en SU, 6 997 l’ont été pour une étiologie médicale, dont 2 546 (36 %) sans attente et 4 451 (64 %) après une attente. Après pondération, le taux de mortalité intrahospitalière était plus important dans le groupe en attente : 7,8 vs 6,3 % ; p < 0,05. De même, la durée médiane d’hospitalisation était plus importante dans le groupe en attente : 7,6 [4,7– 12,0] vs 7,1 j [4,3–11,5] ; p < 0,01.

Discussion : Les taux de mortalité et de la durée de séjour intrahospitaliers sont plus importants chez les patients étudiés qui attendent en SU faute de place en service. Nos résultats sont concordants avec la littérature internationale. Il est nécessaire de trouver des solutions pour réduire cette surmortalité.

Emergency department crowding: A systematic review of causes, consequences and solutions

BACKGROUND

Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions.

AIM

The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding.

METHOD

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439).

RESULTS

From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions.

CONCLUSIONS

The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.

Beyond expectations: Post-implementation data shows rotavirus vaccination is likely cost-saving in Australia

BACKGROUND

Universal vaccination against rotavirus was included in the funded Australian National Immunisation Program in July 2007. Predictive cost-effectiveness models assessed the program before introduction.

METHODS

We conducted a retrospective economic evaluation of the Australian rotavirus program using national level post-implementation data on vaccine uptake, before-after measures of program impact and published estimates of excess intussusception cases. These data were used as inputs into a multi-cohort compartmental model which assigned cost and quality of life estimates to relevant health states, adopting a healthcare payer perspective. The primary outcome was discounted cost per quality adjusted life year gained, including or excluding unspecified acute gastroenteritis (AGE) hospitalisations.

RESULTS

Relative to the baseline period (1997-2006), over the 6years (2007-2012) after implementation of the rotavirus program, we estimated that ∼77,000 hospitalisations (17,000 coded rotavirus and 60,000 unspecified AGE) and ∼3 deaths were prevented, compared with an estimated excess of 78 cases of intussusception. Approximately 90% of hospitalisations prevented were in children <5years, with evidence of herd protection in older age groups. The program was cost-saving when observed changes (declines) in both hospitalisations coded as rotavirus and as unspecified AGE were attributed to the rotavirus vaccine program. The adverse impact of estimated excess cases of intussusception was far outweighed by the benefits of the program.

CONCLUSION

The inclusion of herd impact and declines in unspecified AGE hospitalisations resulted in the value for money achieved by the Australian rotavirus immunisation program being substantially greater than predicted bypre-implementation models, despite the potential increased cases of intussusception. This Australian experience is likely to be relevant to high-income countries yet to implement rotavirus vaccination programs.

Calculating the proportion of avoidable attendances at UK emergency departments: analysis of the Royal College of Emergency Medicine's Sentinel Site Survey data

INTRODUCTION

Avoidable attendances (AAs; defined as non-urgent, self-referred patients who could be managed more effectively and efficiently by other services) have been identified as a contributor to ED crowding. Internationally, AAs have been estimated to constitute 10%-90% of ED attendances, with the UK 2013 Urgent and Emergency Care Review suggesting a figure of 40%.

METHODS

This pilot study used data from the Royal College of Emergency Medicine's Sentinel Site Survey to estimate the proportion of AAs in 12 EDs across England on a standard day (20 March 2014). AAs were defined by an expert panel using questions from the survey. All patients attending the EDs were recorded with details of investigations and treatments received, and the proportion of patients meeting criteria for AA was calculated.

RESULTS

Visits for 3044 patients were included. Based on these criteria, a mean of 19.4% (95% CI 18.0% to 20.8%) of attendances could be deemed avoidable. The lowest proportion of AAs reported was 10.7%, while the highest was 44.3%. Younger age was a significant predictor of AA with mean age of 38.6 years for all patients attending compared with 24.6 years for patients attending avoidably (p≤0.001).

DISCUSSION

The proportion of AAs in this study was lower than many estimates in the literature, including that reported by the 2013 Urgent and Emergency Care Review. This suggests the ED is the most appropriate healthcare setting for many patients due to comprehensive investigations, treatments and capability for urgent referrals.The proportion of AAs is dependent on the defining criteria used, highlighting the need for a standardised, universal definition of an appropriate/avoidable ED attendance. This is essential to understanding how AAs contribute to the overall issue of crowding.

Influenza-associated delays in patient throughput and premature patient departure in emergency departments in New South Wales, Australia: A time series analysis

OBJECTIVES

Influenza outbreaks cause overcrowding in EDs. We aimed to quantify the impact of influenza on the National Emergency Access Targets and premature patient departure in New South Wales, Australia.

METHODS

This was a retrospective observational study of 11 million presentations to 115 hospitals during 2010-2014, using routinely collected administrative records. A time series generalised additive regression model was used to assess the correlation between weekly influenza activity and the weekly proportion of patients leaving the ED in >4 h and the proportion that departed before commencing or completing treatment ('did not wait'), after controlling for background winter and holiday effects.

RESULTS

During 2011-2014, peak annual circulating influenza was associated with the peak weekly proportion of presentations that left in >4 h. The maximum estimated absolute weekly change in that proportion was 3.88 (95% confidence interval 3.02-4.74) percentage points in 2014. For presentations that did not wait, influenza circulation was associated with statistically significant increases in all years, with a maximum weekly value of 2.68 (95% confidence interval 2.31-3.06) percentage points in 2012.

CONCLUSIONS

Circulating influenza was associated with sustained increases and peaks in delayed patient throughput and premature patient departures. Influenza surveillance information may assist with development of health system and hospital workforce planning and bed management activities.

Patterns of low acuity patient presentations to emergency departments in New South Wales, Australia

OBJECTIVE

To explore the patterns of low acuity patient (LAP) presentations to EDs in New South Wales (NSW), Australia.

METHODS

Retrospective study of NSW public hospital ED presentations between January 2013 and December 2014 that were registered in the NSW Emergency Department Data Collection (n = 409 035). LAPs were defined according to the Australian Institute of Health and Welfare (AIHW), Sprivulis and multiple ACEM methods. Multivariable logistic regression was used to assess the adjusted odds of LAP ED presentation by a suite of sociodemographic factors.

RESULTS

The percentage of LAPs varied considerably by definition, being as high as 54.7% (inner regional areas) and as low as 3.2% (major cities) using revised ACEM methods modified to contain unlimited consultation times or consultation times of 15 min or less, respectively. For each method, higher proportions of LAPs were observed in inner regional and remote/very remote areas relative to major cities. LAP ED presentations, based on ACEM definition with 1 h or 15 min consultation times, were greater in younger patients, increased during out of business hours and weekends, and decreased with increasing general practitioner (GP) density.

CONCLUSION

The percentage of LAPs varied substantially by definition, and further work is required to validate the methods, particularly around the appropriateness of length of consultation time with ACEM, between different hospitals and remoteness areas. Age was strongly associated with low acuity, with substantial effects also observed for GP density, and attendances during out of hours and weekends.

The Sydney Triage to Admission Risk Tool (START) to predict Emergency Department Disposition: A derivation and internal validation study using retrospective state-wide data from New South Wales, Australia

Background

Disposition decisions are critical to the functioning of Emergency Departments. The objectives of the present study were to derive and internally validate a prediction model for inpatient admission from the Emergency Department to assist with triage, patient flow and clinical decision making.

Methods

This was a retrospective analysis of State-wide Emergency Department data in New South Wales, Australia. Adult patients (age ≥ 16 years) were included if they presented to a Level five or six (tertiary level) Emergency Department in New South Wales, Australia between 2013 and 2014. The outcome of interest was in-patient admission from the Emergency Department. This included all admissions to short stay and medical assessment units and being transferred out to another hospital. Analyses were performed using logistic regression. Discrimination was assessed using area under curve and derived risk scores were plotted to assess calibration.

Results

1,721,294 presentations from twenty three Level five or six hospitals were analysed. Of these 49.38% were male and the mean (sd) age was 49.85 years (22.13). Level 6 hospitals accounted for 47.70% of cases and 40.74% of cases were classified as an in-patient admission based on their mode of separation. The final multivariable model including age, arrival by ambulance, triage category, previous admission and presenting problem had an AUC of 0.82 (95% CI 0.81, 0.82).

Conclusion

By deriving and internally validating a risk score model to predict the need for in-patient admission based on basic demographic and triage characteristics, patient flow in ED, clinical decision making and overall quality of care may be improved. Further studies are now required to establish clinical effectiveness of this risk score model.

Statewide retrospective study of low acuity emergency presentations in New South Wales, Australia: who, what, where and why?

OBJECTIVE

The present study aims to use a statewide population-based registry to assess the prevalence of low acuity emergency department (ED) presentations, describe the trend in presentation rates and to determine whether they were associated with various presentation characteristics such as the type of hospital as well as clinical and demographic variables.

DESIGN AND SETTING

This was a retrospective analysis of a population-based registry of ED presentations in New South Wales (NSW). Generalised estimating equations with log links were used to determine factors associated with low acuity presentations to account for repeat presentations and the possibility of clustering of outcomes.

PARTICIPANTS

Patients were included in this analysis if they presented to an ED between January 2010 and December 2014. The outcomes of interest were low acuity presentation, defined as those who self-presented (were not transported by ambulance), were assigned a triage category of 4 or 5 (semiurgent or non-urgent) and discharged back to usual residence from ED.

RESULTS

There were 10.7 million ED presentations analysed. Of these, 45% were classified as a low acuity presentation. There was no discernible increase in the rate of low acuity presentations across NSW between 2010 and 2014. The strongest predictors of low acuity ED presentation were age <40 years of age (OR 1.77); injury or musculoskeletal administrative and non-urgent procedures (OR 2.96); ear, nose and throat, eye or oral (OR 5.53); skin or allergy-type presenting problems (OR 2.84).

CONCLUSIONS

Low acuity ED presentations comprise almost half of all ED presentations. Alternative emergency models of care may help meet the needs of these patients.