Review article: Emergency department crowding measures associations with quality of care: A systematic review

Vital signs monitoring in Australasian emergency departments: Development of a consensus statement from ACEM and CENA

BACKGROUND

Emergency Department (ED) care is provided for a diverse range of patients, clinical acuity and conditions. This diversity often calls for different vital signs monitoring requirements. Requirements often change depending on the circumstances that patients experience during episodes of ED care.

AIM

To describe expert consensus on vital signs monitoring during ED care in the Australasian setting to inform the content of a joint Australasian College for Emergency Medicine (ACEM) and College of Emergency Nursing Australasia (CENA) position statement on vital signs monitoring in the ED.

METHOD

A 4-hour online nominal group technique workshop with follow up surveys.

RESULTS

Twelve expert ED nurses and doctors from adult, paediatric and mixed metropolitan and regional ED and research facilities spanning four Australian states participated in the workshop and follow up surveys. Consensus building generated 14 statements about vital signs monitoring in ED. Good consensus was reached on whether vital signs should be assessed for 15 of 19 circumstances that patients may experience.

CONCLUSION

This study informed the creation of a joint position statement on vital signs monitoring in the Australasian ED setting, endorsed by CENA and ACEM. Empirical evidence is needed for optimal, safe and achievable policy on this fundamental practice.

Being a patient in a crowded emergency department: a qualitative service evaluation

BACKGROUND

Emergency department (ED) crowding causes increased mortality. Professionals working in crowded departments feel unable to provide high-quality care and are predisposed to burnout. Awareness of the impact on patients, however, is limited to metrics and surveys rather than understanding perspectives. This project investigated patients' experiences and identified mitigating interventions.

METHODS

A qualitative service evaluation was undertaken in a large UK ED. Adults were recruited during periods of high occupancy or delayed transfers. Semi-structured interviews explored experience during these attendances. Participants shared potential mitigating interventions. Analysis was based on the interpretative phenomenological approach. Verbatim transcripts were read, checked for accuracy, re-read and discussed during interviewer debriefing. Reflections about positionality informed the interpretative process.

RESULTS

Seven patients and three accompanying partners participated. They were aged 24-87 with characteristics representing the catchment population. Participants' experiences were characterised by 'loss of autonomy', 'unmet expectations' and 'vulnerability'. Potential mitigating interventions centred around information provision and better identification of existing ED facilities for personal needs.

CONCLUSION

Participants attending a crowded ED experienced uncertainty, helplessness and discomfort. Recommendations included process and environmental orientation.

An ensemble model for predicting dispositions of emergency department patients

OBJECTIVE

The healthcare challenge driven by an aging population and rising demand is one of the most pressing issues leading to emergency department (ED) overcrowding. An emerging solution lies in machine learning's potential to predict ED dispositions, thus leading to promising substantial benefits. This study's objective is to create a predictive model for ED patient dispositions by employing ensemble learning. It harnesses diverse data types, including structured and unstructured information gathered during ED visits to address the evolving needs of localized healthcare systems.

METHODS

In this cross-sectional study, 80,073 ED patient records were amassed from a major southern Taiwan hospital in 2018-2019. An ensemble model incorporated structured (demographics, vital signs) and pre-processed unstructured data (chief complaints, preliminary diagnoses) using bag-of-words (BOW) and term frequency-inverse document frequency (TF-IDF). Two random forest base-learners for structured and unstructured data were employed and then complemented by a multi-layer perceptron meta-learner.

RESULTS

The ensemble model demonstrates strong predictive performance for ED dispositions, achieving an area under the receiver operating characteristic curve of 0.94. The models based on unstructured data encoded with BOW and TF-IDF yield similar performance results. Among the structured features, the top five most crucial factors are age, pulse rate, systolic blood pressure, temperature, and acuity level. In contrast, the top five most important unstructured features are pneumonia, fracture, failure, suspect, and sepsis.

CONCLUSIONS

Findings indicate that utilizing ensemble learning with a blend of structured and unstructured data proves to be a predictive method for determining ED dispositions.

Reducing the length of stay for patients stranded in the emergency department: A single-center prospective study of 18,631 patients in China

The purpose of this study was to reduce the length of stay (LOS) for patients stranded in the emergency department (ED) of a Grade III A hospital in China, and to improve patient flow and increase bed capacity. We utilized a pre-/postintervention design and employed the Six Sigma methodology, which is based on the DMAIC cycle (define, measure, analyze, improve, and control), to evaluate and improve the existing process. Data from 18,631 patients who were stranded in the ED were collected and analyzed. The median LOS for stranded patients decreased from 17.21 (6.22, 27.36) hours to 13.45 (5.56, 25.85) hours (P < .05). Similarly, the median LOS for admitted patients decreased from 19.64 (7.77, 27.68) hours to 15.92 (6.19, 26.24) hours (P < .05). The median LOS for patients with an ED triage Level IV decreased from 16.15 (5.80, 26.62) hours to 12.59 (5.20, 24.97) hours (P < .05). In addition, the average hospitalization days of hospitalized patients decreased from 0.92 days to 0.82 days (P < .05). Furthermore, the bed utilization rate increased from 66.79% to 72.29% (P < .05). The number of bed turnovers in the ED resuscitation room increased from 20.30 to 21.96 (P < .05). We had effectively met our goal of minimizing ED patient LOS. Six Sigma method can effectively shorten patient LOS by measuring and analyzing the key factors affecting patient LOS, and by implementing measures such as strict implementation of emergency classification and triage system, establishment of multidisciplinary cooperative team, reasonable allocation of human resources, information management of bed resources, and improvement of performance appraisal scheme to improve and control the effectiveness of patient LOS.

Overcrowding in emergency departments: an overview of reviews describing global solutions and their outcomes

Emergency Department (ED) crowding is defined as a situation wherein the demands of emergency services overcome the ability of a department to provide high-quality care within an appropriate time frame. There is a need for solutions, as the harms of crowding impact patients, staff, and healthcare spending. An overview of ED crowding was previously published by our group, which outlines these global issues. The problem of overcrowding in emergency departments has emerged as a global public health concern, and several healthcare agencies have addressed the issue and proposed possible solutions at each level of emergency care. There is no current literature summarizing the extensive research on interventions and solutions, thus there is a need for data synthesis to inform policymakers in this field. The aim of this overview was to summarize the interventions at each level of emergency care: input, throughput, and output. The methodology was supported by the current PRIOR statement for an overview of reviews. The study summarized twenty-seven full-text systematic reviews, which encompassed three hundred and eight primary studies. The results of the summary displayed a requirement for increasing studies in input and output interventions, as these showed the best outcomes with regard to ED crowding metrics. Moreover, the results displayed heterogeneous results at each level of ED care; these reflected that generally solutions have not been matched to specific problems facing regional centres. Thus, individual factors need to be considered when implementing solutions in Emergency Departments.

Impact of sequential capacity building on emergency department organisational flow during COVID-19 pandemic: a quasi-experimental study in a low-resource, tertiary care centre

INTRODUCTION

A quasi-experimental study was conducted to estimate the impact of sequential emergency department (ED) capacity building interventions on key performance indicators such as patients' length of stay (LOS) and wait time (WT) during the COVID-19 pandemic. This was achieved through augmenting personnel education and head count, space restructuring and workflow reorganisation.

SETTING AND PARTICIPANTS

This study included 268 352 patients presenting from January 2019 to December 2020 at Indus Hospital and Health network Karachi, a philanthropic tertiary healthcare facility in a city of 20 million residents. A follow-up study was undertaken from January to December 2021 with 123 938 participants.

PRIMARY AND SECONDARY OUTCOME MEASURES

These included mean and median ED-LOS and WT for participants presenting in different cohorts. The results of the pre-COVID-19 year 2019 (phase 0) were compared with that of the COVID-19 year, 2020 (phases 1-3 corresponding to peaks, and phase 4 corresponding to reduction in caseloads). The follow-up was conducted in 2021 to see the sustainability of the sequential capacity building.

RESULTS

Phases 1, 2 and 3 had a lower mean adjusted LOS (4.42, 3.92 and 4.40 hours) compared with phase 0 (4.78 hours, p<0.05) with the lowest numbers seen in phase 2. The same held true for WT with 45.1, 23.8 and 30.4 min in phases 1-3 compared with 49.9 in phase 0. However, phase 4 had a higher LOS but a lower WT when compared with phase 0 with a p<0.05.

CONCLUSION

Sequential capacity building and improving the operational flow through stage appropriate interventions can be used to off-load ED patients and improve process flow metrics. This shows that models created during COVID-19 can be used to develop sustainable solutions and investment is needed in ideas such as ED-based telehealth to improve patient satisfaction and outcomes.

Emergency department crowding: an overview of reviews describing measures causes, and harms

Crowding in Emergency Departments (EDs) has emerged as a global public health crisis. Current literature has identified causes and the potential harms of crowding in recent years. The way crowding is measured has also been the source of emerging literature and debate. We aimed to synthesize the current literature of the causes, harms, and measures of crowding in emergency departments around the world. The review is guided by the current PRIOR statement, and involved Pubmed, Medline, and Embase searches for eligible systematic reviews. A risk of bias and quality assessment were performed for each review, and the results were synthesized into a narrative overview. A total of 13 systematic reviews were identified, each targeting the measures, causes, and harms of crowding in global emergency departments. Key among the results is that the measures of crowding were heterogeneous, even in geographically proximate areas, and that temporal measures are being utilized more frequently. It was identified that many measures are associated with crowding, and the literature would benefit from standardization of these metrics to promote improvement efforts and the generalization of research conclusions. The major causes of crowding were grouped into patient, staff, and system-level factors; with the most important factor identified as outpatient boarding. The harms of crowding, impacting patients, healthcare staff, and healthcare spending, highlight the importance of addressing crowding. This overview was intended to synthesize the current literature on crowding for relevant stakeholders, to assist with advocacy and solution-based decision making.

Acute abdominal pain at referral emergency departments: an analysis of performance of three time-dependent quality indicators

BACKGROUND

Abdominal pain is one of the most frequent causes for emergency department (ED) visits. The quality of care and outcomes are determined by time-dependent interventions with barriers to implementation at crowded EDs.

OBJECTIVES

The study aimed to analyze three prominent quality indicators (QI) including pain assessment (QI1), analgesia in patients reporting severe pain (QI2), and ED length of stay (LOS) (QI3) in adult patients requiring immediate or urgent care due to acute abdominal pain. We aimed to characterize current practice regarding pain management, and we hypothesized that extended ED LOS (≥ 360 min) is associated with poor outcomes in this cohort of ED referrals.

METHODS

This is a retrospective cohort study enrolling all patients with acute abdominal pain as the main cause of ED presentation, triage category red, orange, or yellow, and age ≥ 30 years during two months period. Univariate and multivariable analyses were deployed to determine independent risk factors for QIs performance. For QI1 and QI2, compliance with the QIs were analyzed, while 30-day mortality was set as primary outcome for QI3.

RESULTS

Overall, 965 patients were analyzed including 501 (52%) males with a mean age of 61.8 years. Seventeen percent (167/965) of the patients had immediate or very urgent triage category. Age ≥ 65 years, and red and orange triage categories were risk factors for non-compliance with pain assessment. Seventy four per cent of patients with severe pain (numeric rating scale ≥ 7) received analgesia during the ED visit, in median within 64 min (IQR 35-105 min). Age ≥ 65 years and need for surgical consultation were risk factors for prolonged ED stay. After adjustment to age, gender and triage category, ED LOS ≥ 360 min proved to be independent risk factor for 30-day mortality (HR 1.89, 95% CI 1.71-3.40, p = 0.034).

CONCLUSION

Our investigation identified that non-compliance with pain assessment, analgesia and ED length of stay among patients presenting with abdominal pain to ED results in poor quality of care and detrimental outcomes. Our data support enhanced quality-assessment initiatives for this subset of ED patients.

Diagnostic performance of S100B as a rule-out test for intracranial pathology in head-injured patients presenting to the emergency department who meet NICE Head Injury Guideline criteria for CT-head scan

BACKGROUND

Traumatic brain injury is a common ED presentation. CT-head utilisation is escalating, exacerbating resource pressure in the ED. The biomarker S100B could assist clinicians with CT-head decisions by excluding intracranial pathology. Diagnostic performance of S100B was assessed in patients meeting National Institute of Health and Clinical Excellence Head Injury Guideline (NICE HIG) criteria for CT-head within 6 and 24 hours of injury.

METHODS

This multicentre prospective observational study included adult patients presenting to the ED with head injuries between May 2020 and June 2021. Informed consent was obtained from patients meeting NICE HIG CT-head criteria. A venous blood sample was collected and serum was tested for S100B using a Cobas Elecsys-S100 module; >0.1 µg/mL was the threshold used to indicate a positive test. Intracranial pathology reported on CT-head scan by the duty radiologist was used as the reference standard to review diagnostic performance.

RESULTS

This study included 265 patients of whom 35 (13.2%) had positive CT-head findings. Within 6 hours of injury, sensitivity of S100B was 93.8% (95% CI 69.8% to 99.8%) and specificity was 30.8% (22.6% to 40.0%). Negative predictive value (NPV) was 97.3% (95% CI 84.2% to 99.6%) and area under the curve (AUC) was 0.73 (95% CI 0.61 to 0.85; p=0.003). Within 24 hours of injury, sensitivity was 82.9% (95% CI 66.4% to 93.44%) and specificity was 43.0% (95% CI 36.6% to 49.7%). NPV was 94.29% (95% CI 88.7% to 97.2%) and AUC was 0.65 (95% CI 0.56 to 0.74; p=0.046). Theoretically, use of S100B as a rule-out test would have reduced CT-head scans by 27.1% (95% CI 18.9% to 36.8%) within 6 hours and 37.4% (95% CI 32.0% to 47.2%) within 24 hours. The risk of missing a significant injury with this approach would have been 0.75% (95% CI 0.0% to 2.2%) within 6 hours and 2.3% (95% CI 0.5% to 4.1%) within 24 hours.

CONCLUSION

Within 6 hours of injury, S100B performed well as a diagnostic test to exclude significant intracranial pathology in low-risk patients presenting with head injury. In theory, if used in addition to NICE HIGs, CT-head rates could reduce by one-quarter with a potential miss rate of <1%.

Effects of process changes on emergency department crowding in a changing world: an interrupted time-series analysis

BACKGROUND

During a 6-year period, several process changes were introduced at the emergency department (ED) to decrease crowding, such as the implementation of a general practitioner cooperative (GPC) and additional medical staff during peak hours. In this study, we assessed the effects of these process changes on three crowding measures: patients' length of stay (LOS), the modified National ED OverCrowding Score (mNEDOCS), and exit block while taking into account changing external circumstances, such as the COVID-19 pandemic and centralization of acute care.

METHODS

We determined time points of the various interventions and external circumstances and built an interrupted time-series (ITS) model per outcome measure. We analyzed changes in level and trend before and after the selected time points using ARIMA modeling, to account for autocorrelation in the outcome measures.

RESULTS

Longer patients' ED LOS was associated with more inpatient admissions and more urgent patients. The mNEDOCS decreased with the integration of the GPC and the expansion of the ED to 34 beds and increased with the closure of a neighboring ED and ICU. More exit blocks occurred when more patients with shortness of breath and more patients > 70 years of age presented to the ED. During the severe influenza wave of 2018-2019, patients' ED LOS and the number of exit blocks increased.

CONCLUSIONS

In the ongoing battle against ED crowding, it is pivotal to understand the effect of interventions, corrected for changing circumstances and patient and visit characteristics. In our ED, interventions which were associated with decreased crowding measures included the expansion of the ED with more beds and the integration of the GPC on the ED.

Impact of the 24-hour time target policy for emergency departments in South Korea: a mixed method study in a single medical center

BACKGROUND

In South Korea, after the spread of the Middle East Respiratory Syndrome epidemic was aggravated by long stays in crowded emergency departments (EDs), a 24-hour target policy for EDs was introduced to prevent crowding and reduce patients' length of stay (LOS). The policy requires at least 95% of all patients to be admitted, discharged or transferred from an ED within 24 hours of arrival. This study analyzes the effects of the 24-hour target policy on ED LOS and compliance rates and describes the consequences of the policy.

METHODS

A mixed-methods approach was applied to a retrospective observational study of ED visits combined with a survey of medical professionals. The primary measure was ED LOS, and the secondary measure was policy compliance rate which refers to the proportion of patient visits with a LOS shorter than 24 hours. Patient flow, quality of care, patient safety, staff workload, and staff satisfaction were also investigated through surveys. Mann-Whitney U and χ2 tests were used to compare variables before and after the introduction of the policy.

RESULTS

The median ED LOS increased from 3.9 hours (interquartile range [IQR] = 2.1-7.6) to 4.5 hours (IQR = 2.5-8.5) after the policy was introduced. This was likely influenced by the average monthly number of patients, which greatly increased from 4819 (SD = 340) to 5870 (SD = 462) during the same period. The proportion of patients with ED LOS greater than 24 hours remained below5% only after 6 months of policy implementation, but the number of patients whose disposition was decided at 23 hours increased by 4.84 times. Survey results suggested that patient flow and quality of care improved slightly, while the workload of medical staff worsened.

CONCLUSIONS

After implementing the 24-hour target policy, the proportion of patients whose ED LOS exceeded 24 hours decreased, even though the median ED LOS increased. However, the unintended consequences of the policy were observed such as increased medical professional workload and abrupt expulsion of patients before 24 hours.

Assessing data gathering of chatbot based symptom checkers - a clinical vignettes study

BACKGROUND

The burden on healthcare systems is mounting continuously owing to population growth and aging, overuse of medical services, and the recent COVID-19 pandemic. This overload is also causing reduced healthcare quality and outcomes. One solution gaining momentum is the integration of intelligent self-assessment tools, known as symptom-checkers, into healthcare-providers' systems. To the best of our knowledge, no study so far has investigated the data-gathering capabilities of these tools, which represent a crucial resource for simulating doctors' skills in medical-interviews.

OBJECTIVES

The goal of this study was to evaluate the data-gathering function of currently available chatbot symptom-checkers.

METHODS

We evaluated 8 symptom-checkers using 28 clinical vignettes from the repository of MSD-Manual case studies. The mean number of predefined pertinent findings for each case was 31.8 ± 6.8. The vignettes were entered into the platforms by 3 medical students who simulated the role of the patient. For each conversation, we obtained the number of pertinent findings retrieved and the number of questions asked. We then calculated the recall-rates (pertinent-findings retrieved out of all predefined pertinent-findings), and efficiency-rates (pertinent-findings retrieved out of the number of questions asked) of data-gathering, and compared them between the platforms.

RESULTS

The overall recall rate for all symptom-checkers was 0.32(2,280/7,112;95 %CI 0.31-0.33) for all pertinent findings, 0.37(1,110/2,992;95 %CI 0.35-0.39) for present findings, and 0.28(1140/4120;95 %CI 0.26-0.29) for absent findings. Among the symptom-checkers, Kahun platform had the highest recall rate with 0.51(450/889;95 %CI 0.47-0.54). Out of 4,877 questions asked overall, 2,280 findings were gathered, yielding an efficiency rate of 0.46(95 %CI 0.45-0.48) across all platforms. Kahun was the most efficient tool 0.74 (95 %CI 0.70-0.77) without a statistically significant difference from Your.MD 0.69(95 %CI 0.65-0.73).

CONCLUSION

The data-gathering performance of currently available symptom checkers is questionable. From among the tools available, Kahun demonstrated the best overall performance.

Ethnic Disparities in CT Aortography Use for Diagnosing Acute Aortic Syndrome

Purpose

To determine whether CT aortography was performed in proportion to patient risk for acute aortic syndrome (AAS) and incidence of AAS for different ethnic groups.

Materials and Methods

All atraumatic thoracic aorta CT aortographic examinations performed in adults (age > 15 years) suspected of having AAS between January 2009 and December 2019 at Auckland City Hospital (New Zealand) were included. Patients were risk stratified using the aortic dissection detection risk score (ADD-RS). The primary outcomes were the ratio of CT aortography rates to rates of positive CT aortographic examinations and the incidence of AAS. Population census data were used to determine age-standardized incidence of AAS in the emergency department (ED).

Results

In total, 1646 CT aortographic examinations were performed in 1543 patients (mean age, 62 years ± 16 [SD]; 877 male patients). Māori (34% [68 of 203]) and Pacific Islanders (35% [80 of 229]) were more likely to be at high risk of AAS (ADD-RS > 1) compared with patients from other ethnic groups (25% [308 of 1214]); in the ED catchment population, age-standardized AAS incidence was significantly higher in Māori (6.9 per 100 000 person-years [95% CI: 4.3, 10.4]) and Pacific Islanders (5.3 [95% CI: 3.4, 7.8]) than in other ethnic groups (2.3 [95% CI: 1.8, 2.8]). Despite this higher incidence, disproportionately fewer CT aortographic examinations were requested in the ED for Māori (9.2 CT aortographic examinations per AAS diagnosis) and Pacific Islanders (9.2 CT aortographic examinations per AAS diagnosis) compared with other ethnic groups (13.8 CT aortographic examinations per AAS diagnosis).

Conclusion

Māori and Pacific Islanders were at disproportionately higher risk of AAS but had fewer requested CT aortographic examinations compared with other ethnic groups. This increased risk of AAS in Pacific Islander and indigenous Māori patients should be considered by clinicians when investigating AAS.Keywords: Ethnicity, Māori, Pacific Islander, Aortic Dissection Detection Risk Score, Acute Aortic Syndrome, Aortic Dissection, CT Angiography Supplemental material is available for this article. © RSNA, 2022.

Can serum biomarkers be used to rule out significant intracranial pathology in emergency department patients with mild traumatic brain injury? A Systemic Review & Meta-Analysis

BACKGROUND

Interest has mounted into the use of objective clinical biomarkers for traumatic brain injury (TBI). This systematic review and meta-analysis aimed to synthesise the existing evidence investigating the use of serum & plasma biomarkers to exclude significant intracranial injuries seen on CT head scans in patients that present to ED with TBI.

METHODS

The primary outcome was to review the diagnostic accuracy (sensitivity & specificity) of S100B, GFAP and UCH-L1 to exclude significant intracranial pathology on CT head scan in adults presenting with TBI. Secondary outcomes investigated biomarker performance at different time points, in isolated TBI and multi-trauma and with pre-specified cut offs. Systematic searches were conducted on MEDLINE ® (via PubMed), Cochrane electronic databases and EMBASE from 1^st January 2000 until June 2020. Bias was assessed using QUADAS 2 tool. A narrative synthesis and meta-analysis were performed. PROSPERO registration number CRD42020212206.

RESULTS

After screening, 22 papers were included. The total number of patients with TBI was 9,416. There was significant variation regarding study design, population selection and the clinical threshold/decision rule for CT head request. The diagnostic accuracy of S100B as measured by the range of individual sensitivities and specificities were 63-100% and 5-58%, respectively. Individual sensitivities and specificities for GFAP were 67-100% and 0-89% and for UCH-L1 were 61-100% and 21-63.7% respectively. When measured within 3 hours individual sensitivities & specificities for S100B were 98-100% & 20-58% respectively. The quality of evidence for the primary outcome overall was low. The quality of evidence was low for all secondary outcomes apart from studies that used a pre-specified cut off for S100B which had a moderate strength of evidence.

CONCLUSION

The overall quality of evidence regarding the diagnostic accuracy of single biomarkers as a rule out for significant intracranial injury seen on CT head scans in ED patients with TBI is low. Based on current evidence, S100B is the only single biomarker with a validated clinical platform, pre-determined cut off threshold and moderate quality evidence; at this stage making it the biomarker of choice. More robust clinical outcome and economic impact data is required to support its incorporation into clinical decision tools.

Examining emergency department inequities in Aotearoa New Zealand: Findings from a national retrospective observational study examining Indigenous emergency care outcomes

OBJECTIVE

There is increasing evidence that EDs may not operate equitably for all patients, with Indigenous and minoritised ethnicity patients experiencing longer wait times for assessment, differential pain management and less evaluation and treatment of acute conditions.

METHODS

This retrospective observational study used a Kaupapa Māori framework to investigate ED admissions into 18/20 District Health Boards in Aotearoa New Zealand (2006-2012). Key pre-admission variable was ethnicity (Māori:non-Māori), and outcome variables included: ED self-discharge; ED arrival to assessment time; hospital re-admission within 72 h; ED re-presentation within 72 h; ED length of stay; ward length of stay; access block and mortality (in ED or within 10 days of ED departure). Generalised linear regression models controlled for year of presentation, sex, age, deprivation, triage category and comorbidity.

RESULTS

Despite some ED process measures favouring Māori, for example arrival to assessment time (mean difference -2.14 min; 95% confidence interval [CI] -2.42 to -1.86) and access block (odds ratio [OR] 0.89, 95% CI 0.87-0.91), others showed no difference, for example self-discharge (OR 0.98, 95% CI 0.97-1.00). Despite this, Māori mortality (OR 1.60, 95% CI 1.50-1.71) and ED re-presentation (OR 1.11, 95% CI 1.09-1.12) were higher than non-Māori.

CONCLUSION

To our knowledge, this is the most comprehensive investigation of acute outcomes by ethnicity to date in New Zealand. We found ED mortality inequities that are unlikely to be explained by ED process measures or comorbidities. Our findings reinforce the need to investigate health professional bias and institutional racism within an acute care context.