Patient flow in emergency departments: a comprehensive umbrella review of solutions and challenges across the health system.

BACKGROUND: Globally, emergency departments (EDs) are overcrowded and unable to meet an ever-increasing demand for care. The aim of this study is to comprehensively review and synthesise literature on potential solutions and challenges throughout the entire health system, focusing on ED patient flow. METHODS: An umbrella review was conducted to comprehensively summarise and synthesise the available evidence from multiple research syntheses. A comprehensive search strategy was employed in four databases alongside government or organisational websites in March 2023. Gray literature and reports were also searched. Quality was assessed using the JBI critical appraisal checklist for systematic reviews and research syntheses. We summarised and classified findings using qualitative synthesis, the Population-Capacity-Process (PCP) model, and the input/throughput/output (I/T/O) model of ED patient flow and synthesised intervention outcomes based on the Quadruple Aim framework. RESULTS: The search strategy yielded 1263 articles, of which 39 were included in the umbrella review. Patient flow interventions were categorised into human factors, management-organisation interventions, and infrastructure and mapped to the relevant component of the patient journey from pre-ED to post-ED interventions. Most interventions had mixed or quadruple nonsignificant outcomes. The majority of interventions for enhancing ED patient flow were primarily related to the 'within-ED' phase of the patient journey. Fewer interventions were identified for the 'post-ED' phase (acute inpatient transfer, subacute inpatient transfer, hospital at home, discharge home, or residential care) and the 'pre-ED' phase. The intervention outcomes were aligned with the aim (QAIM), which aims to improve patient care experience, enhance population health, optimise efficiency, and enhance staff satisfaction. CONCLUSIONS: This study found that there was a wide range of interventions used to address patient flow, but the effectiveness of these interventions varied, and most interventions were focused on the ED. Interventions for the remainder of the patient journey were largely neglected. The metrics reported were mainly focused on efficiency measures rather than addressing all quadrants of the quadruple aim. Further research is needed to investigate and enhance the effectiveness of interventions outside the ED in improving ED patient flow. It is essential to develop interventions that relate to all three phases of patient flow: pre-ED, within-ED, and post-ED.

Emergency Department Demand and the First Year of the COVID-19 Pandemic.

We present a retrospective analysis of Emergency Department daily patient flow across 84 hospitals in Queensland, Australia over a four-year period from 2017 - 2020, leading up to and including the start of the COVID-19 pandemic. Daily ED demand significantly increased year-on-year over the study period, though significant increases in 2020 were likely attributed to ED fever screening clinics. Compliance against a four-hour ED Length of Stay target had been slightly decreasing since 2017, and the first year of the pandemic showed significant improvements in target compliance compared to previous years for all patients including the cohort admitted from ED. The length of stay for ED patients was also significantly less in 2020 (mean = 3.1 hours) compared to previous years. As an area of topical interest, a special focus on influenza-like illness presentations to ED helps quantify changes in volume of this cohort. This knowledge assists hospitals in planning and responding to variations in hospital demand.

A mapping review of refinements to laboratory rat housing and husbandry.

Refining the housing and husbandry of laboratory rats is an important goal, both for ethical reasons and to allow better quality research. We conducted a mapping review of 1,017 studies investigating potential refinements of housing and husbandry of the laboratory rat to assess what refinements have, and have not, been studied, and to briefly assess whether there is evidence to support any impact on rat welfare. Among the many refinements studied, the majority involve changes to the cage, but some also involve alterations to the wider environment. The effects of these refinements were assessed using a range of readouts, many of which are difficult to interpret from a welfare perspective. Preference studies, which are easier to interpret, provide evidence that rats prefer complex environments, including shelters and multiple objects, which offer different areas/resources allowing the rat to engage in diverse behaviors. The reporting of methodology in papers was often poor, indicating that studies were potentially subject to biases. Given that many refinements co-occurred, it was often difficult to tease apart which ones were most beneficial for rat welfare. Effects of refinements were also moderated by a number of factors including age, sex, strain and photoperiod. Altogether our findings show that a one-size-fits-all approach to refinements is not appropriate, because different refinements will impact different rats in different ways. Our review has also produced a database of >1,000 articles that can be used for further and more detailed analyses. Our findings have also highlighted areas where future research is likely to be valuable, including refinements to rat transport, handling and the use of training.

Ambulance Arrivals and ED Flow - A Queensland Perspective.

While it is widely accepted that whole of hospital solutions are necessary to reduce the ever-increasing burden on the public health system, little research has focussed on understanding the relationship between ambulance arrival related flow metrics and emergency department (ED) crowding. Queensland Ambulance Service (QAS) shares patient load across multiple hospitals, and receiving facilities strive to meet a Patient Off Stretcher Time (POST) target of 30 minutes. We examine ambulance arrival data from the QAS and ED patient arrival data from 15 major metropolitan hospitals across Queensland, to understand temporal variations in POST performance and examine the relationship between POST performance and ED crowding. The findings suggest a relationship between ED occupancy levels and both ambulances waiting at the ED door and average POST at larger hospitals. No relationship between POST and ED length of stay was found, perhaps due to competing ED National Emergency Access Targets (NEAT). Further modelling is recommended to formally test these observations.

Improved Prediction of Procedure Duration for Elective Surgery.

Accurate surgery duration estimation is essential for efficient use of hospital operating theatres and the scheduling of elective patients. This study focuses on analysing the performance of previously developed surgery duration prediction algorithms at a specialty level to gain further insight on their performance. We also evaluate algorithm performance after applying filtering to exclude unreliable data from modelling, and develop and validate new ensemble approaches for prediction. These are shown to significantly improve the prediction accuracy of the algorithms. Employing filtered data delivers a reduction in overall prediction error of 44% (Mean Absolute Percentage Error from 0.68 to 0.38) employing the Random Forests algorithm, while using the newly developed ensemble approach delivers a Mean Absolute Percentage Error of 0.31, a reduction of 55% when compared to the original error, and a reduction of 18% when compared to the Random Forests performance on filtered data.

Analysing the emergency department patient journey: Discovery of bottlenecks to emergency department patient flow.

OBJECTIVE: Despite significant workflow reform to comply with the federally mandated National Emergency Access Target (NEAT), Australian public hospitals continue to face significant barriers in achieving good ED patient flow. This study was undertaken to identify and analyse the impact of individual waypoints on an ED patient's journey and identify which waypoints act as bottlenecks to a hospital's 4 h ED disposition performance. METHODS: This study involves retrospective analysis and simulation employing 2 years of ED administrative data from a sample of two major and two large metropolitan hospitals in Queensland, Australia. The main outcome measures included waypoint wait times (Treatment Delay and Departure Delay), ED length of stay (EDLOS) and compliance with the NEAT target, measured for all (overall NEAT) and admitted (Admitted NEAT) patients. Variations in outcome measures were analysed as functions of hour of day, day of week, departure status and triage category. Simulations identified the impact of potential ED workflow changes in the context of NEAT performance. RESULTS: Departure Delay accounted for 60 and 20% of EDLOS across large and major metropolitan hospitals, respectively. Higher gains in NEAT compliance are associated with improvements in departure delay rather than treatment delay. Simulation identified that halving Departure Delay improves Admitted NEAT by up to 22 and 4% at large and major metropolitan hospitals, respectively. CONCLUSIONS: The results reinforces the need for a whole-of-hospital effort to address flow bottlenecks, and identify moving a patient from emergency to inpatient care as the critical bottleneck in ED system performance.

The National Emergency Access Target (NEAT) and the 4-hour rule: time to review the target.

OBJECTIVE: We explored the relationship between the National Emergency Access Target (NEAT) compliance rate, defined as the proportion of patients admitted or discharged from emergency departments (EDs) within 4 hours of presentation, and the risk-adjusted in-hospital mortality of patients admitted to hospital acutely from EDs. DESIGN, SETTING AND PARTICIPANTS: Retrospective observational study of all de-identified episodes of care involving patients who presented acutely to the EDs of 59 Australian hospitals between 1 July 2010 and 30 June 2014. MAIN OUTCOME MEASURE: The relationship between the risk-adjusted mortality of inpatients admitted acutely from EDs (the emergency hospital standardised mortality ratio [eHSMR]: the ratio of the numbers of observed to expected deaths) and NEAT compliance rates for all presenting patients (total NEAT) and admitted patients (admitted NEAT). RESULTS: ED and inpatient data were aggregated for 12.5 million ED episodes of care and 11.6 million inpatient episodes of care. A highly significant (P < 0.001) linear, inverse relationship between eHSMR and each of total and admitted NEAT compliance rates was found; eHSMR declined to a nadir of 73 as total and admitted NEAT compliance rates rose to about 83% and 65% respectively. Sensitivity analyses found no confounding by the inclusion of palliative care and/or short-stay patients. CONCLUSION: As NEAT compliance rates increased, in-hospital mortality of emergency admissions declined, although this direct inverse relationship is lost once total and admitted NEAT compliance rates exceed certain levels. This inverse association between NEAT compliance rates and in-hospital mortality should be considered when formulating targets for access to emergency care.

Users' experiences of an emergency department patient admission predictive tool: A qualitative evaluation.

Emergency department overcrowding is an increasing issue impacting patients, staff and quality of care, resulting in poor patient and system outcomes. In order to facilitate better management of emergency department resources, a patient admission predictive tool was developed and implemented. Evaluation of the tool's accuracy and efficacy was complemented with a qualitative component that explicated the experiences of users and its impact upon their management strategies, and is the focus of this article. Semi-structured interviews were conducted with 15 pertinent users, including bed managers, after-hours managers, specialty department heads, nurse unit managers and hospital executives. Analysis realised dynamics of accuracy, facilitating communication and enabling group decision-making Users generally welcomed the enhanced potential to predict and plan following the incorporation of the patient admission predictive tool into their daily and weekly decision-making processes. They offered astute feedback with regard to their responses when faced with issues of capacity and communication. Participants reported an growing confidence in making informed decisions in a cultural context that is continually moving from reactive to proactive. This information will inform further patient admission predictive tool development specifically and implementation processes generally.

The Implementation and Evaluation of the Patient Admission Prediction Tool: Assessing Its Impact on Decision-Making Strategies and Patient Flow Outcomes in 2 Australian Hospitals.

STUDY OBJECTIVES: To evaluate the implementation of a Patient Admission Prediction Tool (PAPT) in terms of patient flow outcomes and decision-making strategies. SETTING: The PAPT was implemented in 2 Australian public teaching hospitals during October-December 2010 (hospital A) and October-December 2011 (hospital B). DESIGN: A multisite prospective, comparative (before and after) design was used. Patient flow outcomes measured included access block and hospital occupancy. Daily and weekly data were collected from patient flow reports and routinely collected emergency department information by the site champion and researchers. RESULTS: Daily decision-making strategies ranged from business as usual to use of overcensus beds. Weekly strategies included advanced approval to use of overcensus beds and prebooking nursing staff. These strategies resulted in improved weekend discharges to manage incoming demand for the following week. Following the introduction of the PAPT and workflow guidelines, patient access and hospital occupancy levels could be maintained despite increases in patient presentations (hospital A). CONCLUSIONS: The use of a PAPT, embedded in patient flow management processes and championed by a manager, can benefit bed and staff management. Further research that incorporates wider evaluation of the use of the tool at other sites is warranted.

Improved outcomes for emergency department patients whose ambulance off-stretcher time is not delayed.

OBJECTIVE: To describe and compare characteristics and outcomes of patients who arrive by ambulance to the ED. We aimed to (i) compare patients with a delayed ambulance offload time (AOT) >30 min with those who were not delayed; and (ii) identify predictors of an ED length of stay (LOS) of >4 h for ambulance-arriving patients. METHODS: A retrospective, multi-site cohort study was undertaken in Australia using 12 months of linked health data (September 2007-2008). Outcomes of AOT delayed and non-delayed presentations were compared. Logistic regression analysis was undertaken to identify predictors of an ED LOS of >4 h. RESULTS: Of the 40 783 linked, analysable ambulance presentations, AOT delay of >30 min was experienced by 15%, and 63% had an ED LOS of >4 h. Patients with an AOT <30 min had better outcomes for: time to triage; ambulance time at hospital; time to see healthcare professional; proportion seen within recommended triage time frame; and ED LOS for both admitted and non-admitted patients. In-hospital mortality did not differ. Strong predictors of an ED LOS >4 h included: hospital admission, older age, triage category, and offload delay >30 min. CONCLUSION: Patients arriving to the ED via ambulance and offloaded within 30 min experience better outcomes than those delayed. Given that offload delay is a modifiable predictor of an ED LOS of >4 h, targeted improvements in the ED arrival process for ambulance patients might be useful.

Mid-term NEAT review: analysing the improvements in hospital ED performance.

Introduced with a promise to reduce overcrowding in the Emergency Department (ED) and the associated morbidity and mortality linked to bed access difficulties, the National Emergency Access Target (NEAT) is now over halfway through transitionary arrangements towards a target of 90% of patients that visit a hospital ED being admitted or discharged within 4 hours. Facilitation and reward funding has ensured hospitals around the country are remodelling workflows to ensure compliance. Recent reports however show that the majority of hospitals are still far from being able to meet this target. We investigate the NEAT journey of 30 Queensland hospitals over the past two years and compare this performance to a previous study that investigated the 4 hour ED discharge performance of these hospitals at various times of day and under varying occupancy conditions. Our findings reveal that, while most hospitals have made significant improvements to their 4 hour discharge performance in 2013, the underlying flow patterns and periods of poor NEAT compliance remain largely unchanged. The work identifies areas for targeted improvement to inform system redesign and workflow planning.

Expanding emergency department capacity: a multisite study.

OBJECTIVES: The aims of the present study were to identify predictors of admission and describe outcomes for patients who arrived via ambulance to three Australian public emergency departments (EDs), before and after the opening of 41 additional ED beds within the area. METHODS: The present study was a retrospective comparative cohort study using deterministically linked health data collected between 3 September 2006 and 2 September 2008. Data included ambulance offload delay, time to see doctor, ED length of stay (LOS), admission requirement, access block, hospital LOS and in-hospital mortality. Logistic regression analysis was undertaken to identify predictors of hospital admission. RESULTS: Almost one-third of all 286037 ED presentations were via ambulance (n=79196) and 40.3% required admission. After increasing emergency capacity, the only outcome measure to improve was in-hospital mortality. Ambulance offload delay, time to see doctor, ED LOS, admission requirement, access block and hospital LOS did not improve. Strong predictors of admission before and after increased capacity included age >65 years, Australian Triage Scale (ATS) Category 1-3, diagnoses of circulatory or respiratory conditions and ED LOS >4h. With additional capacity, the odds ratios for these predictors increased for age >65 years and ED LOS >4h, and decreased for ATS category and ED diagnoses. CONCLUSIONS: Expanding ED capacity from 81 to 122 beds within a health service area impacted favourably on mortality outcomes, but not on time-related service outcomes such as ambulance offload time, time to see doctor and ED LOS. To improve all service outcomes, when altering (increasing or decreasing) ED bed numbers, the whole healthcare system needs to be considered.

New emergency department quality measure: from access block to National Emergency Access Target compliance.

OBJECTIVES: The study aims to investigate the effect of time of day and ED occupancy on the ability of EDs to admit or discharge patients within 4 h in accordance with the National Emergency Access Target (NEAT), and to compare this with corresponding levels of access block, the measure for ED performance before NEAT. METHODS: This is a retrospective analysis of 5 years of ED data from 30 reporting public hospitals in Queensland, Australia. Relationships between these and variations in time of day and occupancy were explored using a Poisson generalised linear model. The main outcome measures are cases of NEAT non-compliance (ED length of stay >4 h for all patients [i.e. admitted and non-admitted] leaving the ED) and access block (ED length of stay >8 h for admitted patients). RESULTS: NEAT performance is found to be dependent on hospital size, and levels vary significantly for admitted and non-admitted patients. A higher proportion of patients breach NEAT during early mornings and low occupancy periods, a trend not observed with the previous access block metric. NEAT non-compliance is also found to rise between 13.00 hours and 17.00 hours, a period when the proportion of access block cases typically drops. CONCLUSIONS: EDs face rising levels of NEAT non-compliance at times when corresponding access block levels have traditionally not been a concern. A higher proportion of patients breach the target during periods that would intuitively not be flagged as flow bottlenecks. The findings support the need for service level analysis and new solutions to guide workflow reform and maximise NEAT compliance.

Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block.

OBJECTIVES: To investigate the effect of hospital occupancy levels on inpatient and ED patient flow parameters, and to simulate the impact of shifting discharge timing on occupancy levels. METHODS: Retrospective analysis of hospital inpatient data and ED data from 23 reporting public hospitals in Queensland, Australia, across 30 months. Relationships between outcome measures were explored through the aggregation of the historic data into 21 912 hourly intervals. Main outcome measures included admission and discharge rates, occupancy levels, length of stay for admitted and emergency patients, and the occurrence of access block. The impact of shifting discharge timing on occupancy levels was quantified using observed and simulated data. RESULTS: The study identified three stages of system performance decline, or choke points, as hospital occupancy increased. These choke points were found to be dependent on hospital size, and reflect a system change from 'business-as-usual' to 'crisis'. Effecting early discharge of patients was also found to significantly (P < 0.001) impact overcrowding levels and improve patient flow. CONCLUSIONS: Modern hospital systems have the ability to operate efficiently above an often-prescribed 85% occupancy level, with optimal levels varying across hospitals of different size. Operating over these optimal levels leads to performance deterioration defined around occupancy choke points. Understanding these choke points and designing strategies around alleviating these flow bottlenecks would improve capacity management, reduce access block and improve patient outcomes. Effecting early discharge also helps alleviate overcrowding and related stress on the system.

Early discharge and its effect on ED length of stay and access block.

Effecting early discharge is a widely recommended strategy for improving patient flow in acute hospitals. This paper analyses the impact of inpatient discharge timing on Emergency Department (ED) flow parameters such as access block and length of stay, while comparing this to the effect on hospital occupancy, to arrive at an understanding of a 'whole of hospital' response to discharge timing. The impact of hospital size is also investigated. The analysis reveals that, on days when the discharge peak lags the peak in inpatient admissions, hospitals of all sizes exhibit increased levels of occupancy, inpatient and ED length of stay, and access block. The findings corroborate the efficacy of early discharge initiatives and 'whole of hospital' flow improvement initiatives for addressing overcrowding and efficiency issues in hospitals.

Predicting emergency department admissions.

OBJECTIVE: To develop and validate models to predict emergency department (ED) presentations and hospital admissions for time and day of the year. METHODS: Initial model development and validation was based on 5 years of historical data from two dissimilar hospitals, followed by subsequent validation on 27 hospitals representing 95% of the ED presentations across the state. Forecast accuracy was assessed using the mean average percentage error (MAPE) between forecasts and observed data. The study also determined a daily sample size threshold for forecasting subgroups within the data. RESULTS: Presentations to the ED and subsequent admissions to hospital beds are not random and can be predicted. Forecast accuracy worsened as the forecast time intervals became smaller: when forecasting monthly admissions, the best MAPE was approximately 2%, for daily admissions, 11%; for 4-hourly admissions, 38%; and for hourly admissions, 50%. Presentations were more easily forecast than admissions (daily MAPE ∼7%). When validating accuracy at additional hospitals, forecasts for urban facilities were generally more accurate than regional forecasts (accuracy is related to sample size). Subgroups within the data with more than 10 admissions or presentations per day had forecast errors statistically similar to the entire dataset. The study also included a software implementation of the models, resulting in a data dashboard for bed managers. CONCLUSIONS: Valid ED prediction tools can be generated from access to de-identified historic data, which may be used to assist elective surgery scheduling and bed management. The paper provides forecasting performance levels to guide similar studies.

Time based clustering for analyzing acute hospital patient flow.

This paper describes a novel approach employing time based clustering of health data for visualization and analysis of patient flow. Clustering inpatient and emergency department patient episodes into hourly slots based on recorded timestamps, and then grouping them on required parameters, the technique provides a powerful tool for visualizing and analyzing interactions and interdependencies between hospital patient flow parameters. To demonstrate the efficacy of the approach, we employ time based clustering to address some typical patient flow related queries and discuss the findings.

Impact of influenza across 27 public emergency departments in Australia: a 5-year descriptive study.

OBJECTIVE: To describe the incidence, characteristics and outcomes of patients with influenza-like symptoms presenting to 27 public hospital emergency departments (EDs) in Queensland, Australia. METHODS: A descriptive retrospective study covering 5 years (2005-9) of historical data from 27 hospital EDs was undertaken. State-wide hospital ED Information System data were analysed. Annual comparisons between influenza and non-influenza cases were made across the southern hemisphere influenza season (June-September) each year. RESULTS: Influenza-related presentations increased significantly over the 5 years from 3.4% in 2005 to 9.4% in 2009, reflecting a 276% relative increase. Differences over time regarding characteristics of patients with influenza-like symptoms, based on the influenza season, occurred for admission rate (decreased over time from 28% in 2005 to 18% in 2009), length of stay (decreased over time from a median of 210 min in 2005 to 164 min in 2009) and access block (increased over time from 33% to 41%). Also, every year there was a significantly (p<0.001) higher percentage of access block in the influenza cohort than in the non-influenza cohort. CONCLUSIONS: Although there was a large increase over time in influenza-related ED presentations, most patients were discharged home from the ED. Special consideration of health service delivery management (eg, establishing an 'influenza clinic border protection and public rollout of vaccination, beginning with those most at risk') for this group of patients is warranted but requires evaluation. These results may inform planning for service delivery models during the influenza season.

Impact of admission and discharge peak times on hospital overcrowding.

The ability of hospital staff to get a patient to the right bed at the right time is dependent on bed occupancy, and is a key issue in all acute hospitals. This paper seeks to identify the impact of admission and discharge timing on hospital occupancy with reference to the peak in daily admissions and discharges. Patient admissions data from 23 Queensland public hospitals was classified into categories based on the relative timing of daily admission and discharge curves. We found statistically significant differences in mean and peak occupancy and patient length of stay between categories (one-way univariate ANOVA p<0.0001). The results support early patient discharge initiatives to reduce hospital occupancy rates.

Prediction and surveillance of influenza epidemics.

OBJECTIVE: To describe the use of surveillance and forecasting models to predict and track epidemics (and, potentially, pandemics) of influenza. METHODS: We collected 5 years of historical data (2005-2009) on emergency department presentations and hospital admissions for influenza-like illnesses (International Classification of Diseases [ICD-10-AM] coding) from the Emergency Department Information System (EDIS) database of 27 Queensland public hospitals. The historical data were used to generate prediction and surveillance models, which were assessed across the 2009 southern hemisphere influenza season (June-September) for their potential usefulness in informing response policy. Three models are described: (i) surveillance monitoring of influenza presentations using adaptive cumulative sum (CUSUM) plan analysis to signal unusual activity; (ii) generating forecasts of expected numbers of presentations for influenza, based on historical data; and (iii) using Google search data as outbreak notification among a population. RESULTS: All hospitals, apart from one, had more than the expected number of presentations for influenza starting in late 2008 and continuing into 2009. (i) The CUSUM plan signalled an unusual outbreak in December 2008, which continued in early 2009 before the winter influenza season commenced. (ii) Predictions based on historical data alone underestimated the actual influenza presentations, with 2009 differing significantly from previous years, but represent a baseline for normal ED influenza presentations. (iii) The correlation coefficients between internet search data for Queensland and statewide ED influenza presentations indicated an increase in correlation since 2006 when weekly influenza search data became available. CONCLUSION: This analysis highlights the value of health departments performing surveillance monitoring to forewarn of disease outbreaks. The best system among the three assessed was a combination of routine forecasting methods coupled with an adaptive CUSUM method.