Planning for the future: Emergency department presentation patterns in Tasmania, Australia

A qualitative system model to describe the causes and drivers of frequent potentially avoidable presentations to the emergency department

Frequent potentially avoidable presentations to Emergency Departments (EDs) represent a complex problem, driven by multiple interdependent and interacting factors that change over time and influence one another. We sought to describe and map the drivers of frequent potentially avoidable presentations to a regional ED, servicing regional and rural areas, and identify possible solutions from the perspectives of key stakeholders. This study used a qualitative, community-based systems dynamics approach utilising Group Model Building (GMB). Data were collected from two 3-h online workshops embedded with small-group discussions and conducted with stakeholder groups operating within a regional health system. Stakeholders were guided through a series of participatory tasks to develop a causal loop diagram (CLD) using Systems Thinking in Community Knowledge Exchange software (n=29, workshop one), identify potential action points and generate a prioritised action list to intervene in the system (n=21, workshop two). Data were collected through note taking, real-time system mapping, and recording the workshops. Each action was considered against the Public Health 12 framework describing twelve leverage points to intervene in a system. A CLD illustrating the complex and interrelated factors that drive frequent potentially avoidable ED presentations was developed and classified into four categories: (1) access to services; (2) coordination; (3) patient needs; and (4) knowledge and skills. Nine action areas were identified, with many relating to care and service coordination. Most actions aligned with lower-level system impact actions. This study provides an in-depth understanding of influencing factors and potential solutions for frequent potentially avoidable ED presentations across a regional health system. The CLD demonstrates frequent potentially avoidable ED presentations are a complex problem and identified that a prevention response should engage with system- and individual-level solutions. Further work is needed to prioritise actions to support the implementation of higher-level system impacts.

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%.

Hospital Readmission Due to Chronic Obstructive Pulmonary Disease: A Longitudinal Study

BACKGROUND

This study aimed to investigate the prevalence of hospital readmission for chronic obstructive pulmonary disease (COPD) at 30, 90 and 365 days, and to determine demographic and socioeconomic risk factors for 30-day and 90-day readmission and time to COPD-related readmission within 365 days in Tasmania.

METHODS

Patients ≥40 years admitted for COPD between 2011 and 2015 were identified using administrative data from all major public hospitals in Tasmania, Australia. Factors associated with readmission and time to readmission were identified using logistic and Cox regression, respectively.

RESULTS

The rates of COPD-related readmission were 6.7% within 30 days, 12.2% within 90 days and 23.7% within 365 days. Being male (odds ratio [OR]: 1.49, CI: 1.06-2.09), Indigenous (OR: 2.47, CI: 1.31-4.66) and living in the lower socioeconomic North-West region of Tasmania (OR: 1.80, CI: 1.20-2.69) were risk factors for 30-day readmission. Increased COPD-related (OR: 1.48, CI: 1.22-1.80; OR: 1.52, CI: 1.29-1.78) and non-COPD-related (OR: 1.12, CI: 1.03- 1.23; OR: 1.11, CI: 1.03-1.21) emergency department (ED) visits in the preceding six months were risk factors for both 30-day and 90-day readmissions. Being Indigenous (hazard ratio [HR]: 1.61, CI: 1.10-2.37) and previous COPD-related ED visits (HR: 1.30, CI: 1.21-1.39) decreased, while a higher Charlson Comorbidity Index (CCI) (OR: 0.91, CI: 0.83- 0.99) increased the time to readmission within 365 days.

CONCLUSION

Being male, Indigenous, living in the North-West region and previous ED visits were associated with increased risk of COPD readmission in Tasmania. Interventions to improve access to primary healthcare for these groups may reduce COPD-related readmissions.

Evaluating a Novel Extended Scope of Occupational Therapy Service Aimed at Hospital Avoidance in Tasmania, Australia, from the Perspective of Stakeholders

The Australian state of Tasmania has seen a spike in Emergency Department presentations in recent years, particularly among the elderly. A novel extended scope occupational therapy (ESOT) service was implemented by the Tasmanian Health Service, aimed at supporting hospital avoidance. Clients were referred to the ESOT service by other services after being assessed as having a high risk of imminent hospital presentation. Occupational Therapists provided short-term interventions related to falls, mobility, nutrition, and initiated onward referrals to other services. A convergent parallel mixed methods design was used to evaluate the ESOT service. Quantitative data from routinely collected administrative records and a purpose-built survey of referring clinicians were used alongside qualitative data from semi-structured interviews with clients/carers, to enable the triangulation of data. Quantitative data were analysed using descriptive statistics, while qualitative data collected in interviews were thematically analysed. A total of 104 extended scope interventions were provided to 100 clients. Most clients were able to stay at home. Qualitative data revealed that mobility, support, and facilitating access to support services were factors which added value to the client and carer experience. In conclusion, the ESOT program contributed to potentially avoiding hospital admissions and to improving the quality of life of participating clients.

The “better data, better planning” census: a cross-sectional, multi-centre study investigating the factors influencing patient attendance at the emergency department in Ireland

Background

Internationally Emergency Department (ED) crowding is a significant health services delivery issue posing a major risk to population health. ED crowding affects both the quality and access of health services and is associated with poorer patient outcomes and increased mortality rates. In Ireland the practising of “Corridor Medicine” and “Trolley Crises” have become prevalent. The objectives of this study are to describe the demographic and clinical profile of patients attending regional EDs and to investigate the factors influencing ED utilisation in Ireland.

Methods

This was a multi-centre, cross-sectional study and recruitment occurred at a selection of urban and rural EDs (n = 5) in Ireland throughout 2020. At each site all adults presenting over a 24 h census period were eligible for inclusion. Clinical data were collected via electronic records and a questionnaire provided information on demographics, healthcare utilisation, service awareness and factors influencing the decision to attend the ED.

Results

Demographics differed significantly between ED sites in terms of age (p ≤ 0.05), socioeconomic status (p ≤ 0.001), and proximity of health services (p ≤ 0.001). Prior to ED attendance 64% of participants accessed community health services. Most participants (70%) believed the ED was the “best place” for emergency care or attended due to lack of awareness of other services (30%). Musculoskeletal injuries were the most common reason for presentation to the ED in this study (24%) and almost a third of patients (31%) reported presenting to the ED for an x-ray or scan.

Conclusions

This study has identified regional and socioeconomic differences in the drivers of ED presentations and factors influencing ED attendance in Ireland from the patient perspective. Improved awareness of, and provision of alternative care pathways could potentially decrease ED attendances, which would be important in the context of reducing ED crowding during the COVID-19 pandemic. New strategies for integration of acute care in the community must acknowledge and plan for these issues as a universal approach is unlikely to be implemented successfully due to regional factors.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07841-6.

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.

The Tasmanian Conception to Community (C2C) Study Database 2008-09 to 2013-14: Using linked health administrative data to address each piece in the puzzle

BACKGROUND

Tasmania, Australia has a small widely dispersed regional and rural population. The Conception to Community (C2C) Study Database was established as a research platform to inform service planning and policy development and improve health outcomes for Tasmanian mothers and children. The aims of this study were to establish by maternal socio-demographic characteristics: 1) the distribution of births in Tasmania; 2) hospital utilisation for children from birth to 5-years; and 3) the association between child and maternal emergency department (ED) presentation rates.

METHODS

Perinatal and public hospital ED and admitted patient data were linked for every child born in Tasmania between 2008-09 to 2013-14, and their mothers. Individualised rates of ED presentations and hospital admissions were calculated from birth to 5-years. Frequent presenters to ED were defined as having at least four presentations per annum. Ratios of ED presentation and hospital admission rates by sociodemographic characteristics (region (north, north-west, south), rurality, maternal age, and area socioeconomic disadvantage) were estimated using mixed-effects negative binomial models, with random intercepts for each child and family.

RESULTS

The C2C Database is comprised of records for 37,041 children and 27,532 mothers. One-in-ten Tasmanian babies lived in a remote area. The mean yearly rate of ED presentations per child varied by sex, age, region and rurality. Frequent presenters were more likely to reside in the north-west or north, in urban areas, have mothers under 20- years, be male, and live in more disadvantaged areas, with 2.3% of children frequent presenters in their first year of life. The odds of a child being a frequent presenter during their first-year was 6.1- times higher if the mother was a frequent presenter during this period.

CONCLUSION

Associations between maternal and child health service use and combined effects of regionality and rurality highlight opportunities for targeted intervention and service innovations.

Impact of the modifiable areal unit problem in assessing determinants of emergency department demand

OBJECTIVE

To examine the impact of the modifiable areal unit problem (MAUP) in an investigation of factors associated with ED demand in Perth, Western Australia, in 2016. Furthermore, to advocate a means of avoiding this impact.

METHODS

ED presentations were classified as: urgent medical, non-urgent medical, urgent trauma or non-urgent trauma. In each group, sex-stratified, age-adjusted multivariate associations with socio-economic status and distance to the nearest ED and general practitioner (GP) were estimated. Modelling was undertaken using different sets of spatial units: Australian Bureau of Statistics (ABS) Statistical Areas Level 1 (SA1s) and numerous aggregate-level zonations of SA1s (ABS SA2s and others).

RESULTS

Estimates obtained using the different units often varied widely: for seven (30%) of 24 strata defined by combinations of sex, ED type and covariate, the smallest and largest effect sizes differed in terms of direction; further, for 11 (65%) of the remaining 17 strata, the largest effect size was at least twice as high as the smallest. This demonstrates the MAUP's impact and that analyses based on a single set of spatial units are unreliable. To resolve the observed variation, we highlight the SA1-level estimates.

CONCLUSIONS

When formulating interventions targeting reduced ED utilisation, policy planners should be guided by evidence based on analysis of appropriate spatial units. This ideal is undermined by the widespread lack of acknowledgement of the MAUP in studies examining drivers of ED demand using spatially aggregated data. To avoid the MAUP, only estimates obtained through examining a minimal geographic unit should be relied upon.

Delayed flow is a risk to patient safety: A mixed method analysis of emergency department patient flow

INTRODUCTION

Increasing emergency department (ED) demand and crowding has heightened focus on the need for better understanding of patient flow.

AIM

This study aimed to identify input, throughput and output factors contributing to ED patient flow bottlenecks and extended ED length of stay (EDLOS).

METHOD

Concurrent nested mixed method study based on retrospective analysis of attendance data, patient flow observational data and a focus group in an Australian regional ED.

RESULTS

Analysis of 89 013 ED presentations identified increased EDLOS, particularly for patients requiring admission. Mapping of 382 patient journeys identified delays in time to triage assessment (0-39 mins) and extended waiting room stays (0-348 mins). High proportions of patients received care outside ED cubicles. Four qualitative themes emerged: coping under pressure, compromising care and safety, makeshift spaces, and makeshift roles.

CONCLUSION

Three key findings emerged: i) hidden waits such as extended triage-queuing occur during the input phase; ii) makeshift spaces are frequently used to assess and treat patients during times of crowding; and iii) access block has an adverse effect on output flow. Data suggests arrival numbers may not be a key predictor of EDLOS. This research contributes to our understanding of ED crowding and patient flow, informing service delivery and planning.

Maternal Smoking in Pregnancy and Child's Hospital Use up to 5 Years of Age in a Data Linkage Birth Cohort

OBJECTIVES

To examine if exposure to maternal smoking during pregnancy is associated with emergency department (ED) presentation and admission through the ED in children up to 5 years after birth.

METHODS

Antenatal records of all children up to 5 years of age who were born in Tasmania, Australia, between July 2008 and June 2014 were linked to health service use (ED presentations and hospital admissions). Negative binomial regression was used to estimate the incidence rate ratio (IRR) and 95% confidence intervals (CIs) at ≤1 year and ≤5 years for ED presentations and admissions to the hospital through the ED for any reason and by 9 major disease categories for children exposed versus children not exposed to maternal smoking during pregnancy. Models were adjusted for sex, socioeconomic position, maternal age at birth, and region of residence. Presentations and admissions for poisoning and injuries were used as a negative control.

RESULTS

Among 36 630 infants, 21% were exposed to maternal smoking during pregnancy. Exposed children had a 26% higher rate of presentation to the ED (IRR_adjusted 1.26; 95% CI 1.23-1.29) and a 45% higher rate of admission (IRR_adjusted 1.45; 95% CI 1.39-1.51) at up to 5 years of age. Compared with the negative control, higher presentation and admission rates were evident in respiratory; eyes, ears, nose, and throat; psychosocial; and infectious disease categories.

CONCLUSIONS

Higher health care service use was observed in children exposed to maternal smoking during pregnancy for a range of conditions associated with exposure to smoking. The findings reinforce the need to reduce smoking among people in their childbearing years.

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.

An integrated approach for designing in-time and economically sustainable emergency care networks: A case study in the public sector

Emergency Care Networks (ECNs) were created as a response to the increased demand for emergency services and the ever-increasing waiting times experienced by patients in emergency rooms. In this sense, ECNs are called to provide a rapid diagnosis and early intervention so that poor patient outcomes, patient dissatisfaction, and cost overruns can be avoided. Nevertheless, ECNs, as nodal systems, are often inefficient due to the lack of coordination between emergency departments (EDs) and the presence of non-value added activities within each ED. This situation is even more complex in the public healthcare sector of low-income countries where emergency care is provided under constraint resources and limited innovation. Notwithstanding the tremendous efforts made by healthcare clusters and government agencies to tackle this problem, most of ECNs do not yet provide nimble and efficient care to patients. Additionally, little progress has been evidenced regarding the creation of methodological approaches that assist policymakers in solving this problem. In an attempt to address these shortcomings, this paper presents a three-phase methodology based on Discrete-event simulation, payment collateral models, and lean six sigma to support the design of in-time and economically sustainable ECNs. The proposed approach is validated in a public ECN consisting of 2 hospitals and 8 POCs (Point of Care). The results of this study evidenced that the average waiting time in an ECN can be substantially diminished by optimizing the cooperation flows between EDs.

Socioeconomic disadvantage as a driver of non-urgent emergency department presentations: A retrospective data analysis

Background

Globally, emergency departments (EDs) are struggling to meet the service demands of their local communities. Across Australia, EDs routinely collect data for every presentation which is used to determine the ability of EDs to meet key performance indicators. This data can also be used to provide an overall picture of service demand and has been used by healthcare planners to identify local needs and inform service provision, thus, using ED presentations as a microcosm of the communities they serve. The aim of this study was to use ED presentation data to identify who, when and why people accessed a regional Australian ED with non-urgent conditions.

Method and materials

A retrospective data analysis of routinely collected ED data was undertaken. This included data obtained over a seven-year period (July 2009 to June 2016) in comparison with the Australian Bureau of Statistics census data. Analysis included descriptive statistics to identify the profile of non-urgent attendees and linear regression to identify trends in ED usage.

Results

This study revealed a consistently high demand for ED services by people with non-urgent conditions (54.1% of all presentations). People living in the most disadvantaged socioeconomic decile contributed to 36.8% of these non-urgent presentations while those under 25 years of age contributed to 41.1%. Diagnoses of mental health and behavioural issues and of non-specific symptoms significantly increased over the study period (p < 0.001) for both diagnostic groups.

Conclusion

The over-representation by those from the most socioeconomically disadvantaged areas highlights an inequity in access to services. The over-representation by those younger in age indicates behavioural patterns based on age. These key issues faced by our local community and the disparity in current service provision will be used to inform future health policy and service planning.

Ambulance Transport of Patients with Mild Conditions in Hokkaido, Japan

Understanding the epidemiological distributions of ambulance transport for patients with mild conditions according to age, disease, and geographic region could help in achieving optimal use of ambulance services. In the present study, we explored the descriptive epidemiology of ambulance transports in Hokkaido, the northernmost prefecture of Japan, identifying potential factors that determine the frequency of transports for mild diseases. Of the total 153,667 ambulance transports in Hokkaido during 2016, we found that two-thirds were for older people, of which about 60% resulted in hospital admission. There were 74,485 transports for mild cases, which were most commonly for psychiatric disorders among working-age adults (n = 4805), heart diseases among older people (n = 4246), and sensory organ diseases among older people (n = 3589). Examining the ecological correlations over 58 geographic units of ambulance services, the total unemployment rate and distance to the nearest tertiary care hospital were, respectively, positively and negatively correlated with the standardized transport ratio for multiple mild diseases. The proportion of working-age adults was uniquely identified as a possible positive predictor in mild cases of psychiatric disorders. As the identified potential predictors could be helpful in considering countermeasures, the causal links should be examined in future studies.

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

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

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.

Investigating the referral of patients with non-urgent conditions to a regional Australian emergency department: a study protocol

Background

Australia’s only island state, Tasmania, experiences one of the nation’s highest incidences of non-urgent emergency department (ED) presentations in a healthcare system regularly faced with service demands that exceed resource availability. Service-demand mismatches are acknowledged to contribute to ED crowding which in turn, has been documented to have a correlation with poorer patient outcomes. Crowding within EDs is complex, non-urgent presentations alone are not the primary cause, but have been reported to be a contributing factor. In 2015–16 Tasmania recorded over 153,000 ED attendances, 55% of these fell into the two least urgent triage categories. Recent research in the State’s North established that 29% of non-urgent presentations were referred, formally or informally, from primary healthcare providers and that, for many patients (39%), the ED was not their first choice of service provider. This study aims to identify the service needs of patients referred to a regional Australian ED and subsequently triaged as non-urgent.

Method

In order to achieve this aim, three objectives have been identified. The first two objectives use an explanatory sequential mixed-method approach while the third objective will incorporate an implementation science approach. These three objectives are: first, a retrospective analysis of seven years of routinely collected hospital data to identify trends in referral of patients with non-urgent conditions; second, focus group interviews with patients and primary care providers to further understand perceived need and service requirements of those referred to the ED, and third, translation of findings into local health service recommendations.

Discussion

Identification of the needs of patients referred to the ED with non-urgent conditions will inform future service planning aiming to facilitate access to the right service at the right time and in the right place.